Prevalence of Bacterial Meningitis Among Febrile Infants Aged 29-60 Days With Positive Urinalysis Results: A Systematic Review and Meta-analysis | Emergency Medicine | JAMA Network Open | JAMA Network
[Skip to Navigation]
Sign In
Figure 1.  Flow Diagram of Search Results
Flow Diagram of Search Results

Title-abstract agreement: almost perfect for the initial 2018 search (93.1%, κ = 0.86) and the 2019 search update (92.7%, κ = 0.83). Full-text agreement: moderate for 2018 search (85.7%, κ = 0.58) and perfect for 2019 search (100.0%, κ = 1.00). LP indicates lumbar puncture.

Figure 2.  Forest Plots of Pooled Prevalence of Culture-Proven Bacterial Meningitis
Forest Plots of Pooled Prevalence of Culture-Proven Bacterial Meningitis

For the pooled odds ratio (OR) analysis (C), the arrow indicates that the upper confidence limit falls beyond the x-axis; diamond, the overall estimate from the meta-analysis and its confidence interval, with the center of the diamond representing the pooled estimate; and the bar below the diamond, the prediction interval.

Figure 3.  Forest Plots of Pooled Prevalence of Bacterial Meningitis Determined by Cerebrospinal Fluid Testing or Clinical Follow-up
Forest Plots of Pooled Prevalence of Bacterial Meningitis Determined by Cerebrospinal Fluid Testing or Clinical Follow-up

For the pooled odds ratio (OR) analysis (C), the arrow indicates that the upper confidence limit falls beyond the x-axis; diamond, the overall estimate from the meta-analysis and its confidence interval, with the center of the diamond representing the pooled estimate; and the bar below the diamond, the prediction interval.

Table 1.  Description of Included Data Sets
Description of Included Data Sets
Table 2.  Summary of Sensitivity Analyses
Summary of Sensitivity Analyses
Supplement.

eFigure 1. Search Strategies for MEDLINE and Embase

eFigure 2. Newcastle-Ottawa Scale Critical Appraisal Tool

eFigure 3. Funnel Plots for Primary Outcomes (A-C; Pooled Prevalence of Bacterial Meningitis Among Urinalysis-Positive Infants, Urinalysis-Negative Infants and Pooled Odds Ratio) and Secondary Outcomes (D-F; Pooled Prevalence of Bacterial Meningitis Among Urinalysis-Positive Infants, Urinalysis-Negative Infants and Pooled Odds Ratio)

eFigure 4. Forest Plots of Sensitivity Analysis; Pooled Prevalence of Bacterial Meningitis Among Urinalysis-Positive Infants, Urinalysis-Negative Infants and Pooled Odds Ratio for Primary (A-C) and Secondary (D-F) Outcome Measures, Excluding Studies at High Risk of Bias

eFigure 5. Forest Plots of Sensitivity Analysis; Pooled Prevalence of Bacterial Meningitis Among Urinalysis-Positive Infants, Urinalysis-Negative Infants and Pooled Odds Ratio for Primary (A-C) and Secondary (D-F) Outcome Measures, Including Prospective Studies Only

eFigure 6. Forest Plots of Sensitivity Analysis; Pooled Prevalence of Bacterial Meningitis Among Urinalysis-Positive Infants, Urinalysis-Negative Infants and Pooled Odds Ratio for Primary (A-C) and Secondary (D-F) Outcome Measures, Including Studies With ≥7 Days Clinical Follow-up

eFigure 7. Forest Plots of Sensitivity Analysis; Pooled Prevalence of Bacterial Meningitis Among Urinalysis-Positive Infants, Urinalysis-Negative Infants and Pooled Odds Ratio for Primary (A-C) and Secondary (D-F) Outcome Measures, Including Studies With ≥30 Days Clinical Follow-up

eTable 1. Description of Studies Excluded After Primary Author Contact

eTable 2. Results of Critical Appraisal Checklist for Studies Included in Meta-analysis

eReferences

1.
Greenhow  TL, Hung  YY, Pantell  RH.  Management and outcomes of previously healthy, full-term, febrile infants ages 7 to 90 days.   Pediatrics. 2016;138(6):e20160270-e20160270. doi:10.1542/peds.2016-0270 PubMedGoogle ScholarCrossref
2.
Aronson  PL, Thurm  C, Alpern  ER,  et al; Febrile Young Infant Research Collaborative.  Variation in care of the febrile young infant <90 days in US pediatric emergency departments.   Pediatrics. 2014;134(4):667-677. doi:10.1542/peds.2014-1382 PubMedGoogle ScholarCrossref
3.
Aronson  PL, McCulloh  RJ, Tieder  JS,  et al; Febrile Young Infant Research Collaborative.  Application of the Rochester Criteria to identify febrile infants with bacteremia and meningitis.   Pediatr Emerg Care. 2019;35(1):22-27. doi:10.1097/PEC.0000000000001421 PubMedGoogle ScholarCrossref
4.
Tzimenatos  L, Mahajan  P, Dayan  PS,  et al; Pediatric Emergency Care Applied Research Network (PECARN).  Accuracy of the urinalysis for urinary tract infections in febrile infants 60 days and younger.   Pediatrics. 2018;141(2):e20173068. doi:10.1542/peds.2017-3068 PubMedGoogle Scholar
5.
Baskin  MN, O’Rourke  EJ, Fleisher  GR.  Outpatient treatment of febrile infants 28 to 89 days of age with intramuscular administration of ceftriaxone.   J Pediatr. 1992;120(1):22-27. doi:10.1016/S0022-3476(05)80591-8 PubMedGoogle ScholarCrossref
6.
Baraff  LJ, Bass  JW, Fleisher  GR,  et al; Agency for Health Care Policy and Research.  Practice guideline for the management of infants and children 0 to 36 months of age with fever without source.   Ann Emerg Med. 1993;22(7):1198-1210. doi:10.1016/S0196-0644(05)80991-6 PubMedGoogle ScholarCrossref
7.
Baker  MD, Bell  LM, Avner  JR.  Outpatient management without antibiotics of fever in selected infants.   N Engl J Med. 1993;329(20):1437-1441. doi:10.1056/NEJM199311113292001 PubMedGoogle ScholarCrossref
8.
Bonadio  WA, Hagen  E, Rucka  J, Shallow  K, Stommel  P, Smith  D.  Efficacy of a protocol to distinguish risk of serious bacterial infection in the outpatient evaluation of febrile young infants.   Clin Pediatr (Phila). 1993;32(7):401-404. doi:10.1177/000992289303200703 PubMedGoogle ScholarCrossref
9.
Jaskiewicz  JA, McCarthy  CA, Richardson  AC,  et al; Febrile Infant Collaborative Study Group.  Febrile infants at low risk for serious bacterial infection: an appraisal of the Rochester criteria and implications for management.   Pediatrics. 1994;94(3):390-396.PubMedGoogle Scholar
10.
Bachur  RG, Harper  MB.  Predictive model for serious bacterial infections among infants younger than 3 months of age.   Pediatrics. 2001;108(2):311-316. doi:10.1542/peds.108.2.311 PubMedGoogle ScholarCrossref
11.
Bressan  S, Gomez  B, Mintegi  S,  et al.  Diagnostic performance of the lab-score in predicting severe and invasive bacterial infections in well-appearing young febrile infants.   Pediatr Infect Dis J. 2012;31(12):1239-1244. doi:10.1097/INF.0b013e318266a9aa PubMedGoogle Scholar
12.
Gomez  B, Mintegi  S, Bressan  S, Da Dalt  L, Gervaix  A, Lacroix  L; European Group for Validation of the Step-by-Step Approach.  Validation of the “Step-by-Step” approach in the management of young febrile infants.   Pediatrics. 2016;138(2):e20154381. doi:10.1542/peds.2015-4381 PubMedGoogle Scholar
13.
Leroy  S, Bressan  S, Lacroix  L,  et al.  Refined lab-score, a risk score predicting serious bacterial infection in febrile children less than 3 years of age.   Pediatr Infect Dis J. 2018;37(5):387-393. doi:10.1097/INF.0000000000001915 PubMedGoogle ScholarCrossref
14.
Kuppermann  N, Dayan  PS, Levine  DA,  et al; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network (PECARN).  A Clinical prediction rule to identify febrile infants 60 days and younger at low risk for serious bacterial infections.   JAMA Pediatr. 2019;173(4):342-351. doi:10.1001/jamapediatrics.2018.5501 PubMedGoogle ScholarCrossref
15.
Biondi  EA, McCulloh  R, Staggs  VS,  et al; American Academy Of Pediatrics’ Revise Collaborative.  Reducing Variability in the Infant Sepsis Evaluation (REVISE): a national quality initiative.   Pediatrics. 2019;144(3):e20182201. doi:10.1542/peds.2018-2201 PubMedGoogle Scholar
16.
McCulloh  RJ, Fouquet  SD, Herigon  J,  et al.  Development and implementation of a mobile device-based pediatric electronic decision support tool as part of a national practice standardization project.   J Am Med Inform Assoc. 2018;25(9):1175-1182. doi:10.1093/jamia/ocy069 PubMedGoogle ScholarCrossref
17.
Greenhow  TL, Hung  Y-Y, Herz  AM, Losada  E, Pantell  RH.  The changing epidemiology of serious bacterial infections in young infants.   Pediatr Infect Dis J. 2014;33(6):595-599. doi:10.1097/INF.0000000000000225 PubMedGoogle ScholarCrossref
18.
Biondi  EA, Lee  B, Ralston  SL,  et al.  Prevalence of bacteremia and bacterial meningitis in febrile neonates and infants in the second month of life: a systematic review and meta-analysis.   JAMA Netw Open. 2019;2(3):e190874. doi:10.1001/jamanetworkopen.2019.0874 PubMedGoogle Scholar
19.
Berkwitt  AK, Grossman  MR, Aronson  PL.  Is it time to stop classifying febrile infants with positive urinalyses as high-risk for meningitis?   Hosp Pediatr. 2018;8(8):506-508. doi:10.1542/hpeds.2018-0064 PubMedGoogle ScholarCrossref
20.
Goldman  RD, Matlow  A, Linett  L, Scolnik  D.  What is the risk of bacterial meningitis in infants who present to the emergency department with fever and pyuria?   CJEM. 2003;5(6):394-399. doi:10.1017/S1481803500008630 PubMedGoogle ScholarCrossref
21.
Young  BR, Nguyen  THP, Alabaster  A, Greenhow  TL.  The prevalence of bacterial meningitis in febrile infants 29-60 days with positive urinalysis.   Hosp Pediatr. 2018;8(8):450-457. doi:10.1542/hpeds.2017-0254 PubMedGoogle ScholarCrossref
22.
Wang  ME, Biondi  EA, McCulloh  RJ,  et al.  Testing for meningitis in febrile well-appearing young infants with a positive urinalysis.   Pediatrics. 2019;144(3):e20183979. doi:10.1542/peds.2018-3979 PubMedGoogle Scholar
23.
Liberati  A, Altman  DG, Tetzlaff  J,  et al.  The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration.   BMJ. 2009;339:b2700. doi:10.1136/bmj.b2700 PubMedGoogle ScholarCrossref
24.
Roberts  KB, Wald  ER.  The diagnosis of UTI: colony count criteria revisited.   Pediatrics. 2018;141(2):e20173239. doi:10.1542/peds.2017-3239 PubMedGoogle Scholar
25.
Hui  C, Neto  G, Tsertsvadze  A,  et al.  Diagnosis and management of febrile infants (0-3 months).   Evid Rep Technol Assess (Full Rep). 2012;(205):1-297.PubMedGoogle Scholar
26.
Nigrovic  LE, Mahajan  PV, Blumberg  SM,  et al; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network (PECARN).  The Yale Observation Scale Score and the risk of serious bacterial infections in febrile infants.   Pediatrics. 2017;140(1):e20170695. doi:10.1542/peds.2017-0695 PubMedGoogle Scholar
27.
Glissmeyer  EW, Korgenski  EK, Wilkes  J,  et al.  Dipstick screening for urinary tract infection in febrile infants.   Pediatrics. 2014;133(5):e1121-e1127. doi:10.1542/peds.2013-3291 PubMedGoogle ScholarCrossref
28.
SUBCOMMITTEE ON URINARY TRACT INFECTION.  Reaffirmation of AAP clinical practice guideline: the diagnosis and management of the initial urinary tract infection in febrile infants and young children 2-24 months of age.   Pediatrics. 2016;138(6):e20163026-e20163026. doi:10.1542/peds.2016-3026 PubMedGoogle ScholarCrossref
29.
Wells  GA, Shea  B, O’Connell  D,  et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Accessed january 1, 2020. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp
30.
Stang  A.  Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses.   Eur J Epidemiol. 2010;25(9):603-605. doi:10.1007/s10654-010-9491-z PubMedGoogle ScholarCrossref
31.
Nugent  J, Childers  M, Singh-Miller  N, Howard  R, Allard  R, Eberly  M.  Risk of meningitis in infants aged 29 to 90 days with urinary tract infection: a systematic review and meta-analysis.   J Pediatr. 2019;212:102-110.e5. doi:10.1016/j.jpeds.2019.04.053 PubMedGoogle ScholarCrossref
32.
Stijnen  T, Hamza  TH, Ozdemir  P.  Random effects meta-analysis of event outcome in the framework of the generalized linear mixed model with applications in sparse data.   Stat Med. 2010;29(29):3046-3067. doi:10.1002/sim.4040 PubMedGoogle ScholarCrossref
33.
IntHout  J, Ioannidis  JP, Rovers  MM, Goeman  JJ.  Plea for routinely presenting prediction intervals in meta-analysis.   BMJ Open. 2016;6(7):e010247. doi:10.1136/bmjopen-2015-010247 PubMedGoogle Scholar
34.
Balduzzi  S, Rücker  G, Schwarzer  G.  How to perform a meta-analysis with R: a practical tutorial.   Evid Based Ment Health. 2019;22(4):153-160. doi:10.1136/ebmental-2019-300117 PubMedGoogle ScholarCrossref
35.
Bonilla  L, Gomez  B, Pintos  C, Benito  J, Mintegi  S.  Prevalence of bacterial infection in febrile infant 61-90 days old compared with younger infants.   Pediatr Infect Dis J. 2019;38(12):1163-1167. doi:10.1097/INF.0000000000002461 PubMedGoogle ScholarCrossref
36.
Gomez  B, Diaz  H, Carro  A, Benito  J, Mintegi  S.  Performance of blood biomarkers to rule out invasive bacterial infection in febrile infants under 21 days old.   Arch Dis Child. 2019;104(6):547-551. doi:10.1136/archdischild-2018-315397 PubMedGoogle ScholarCrossref
37.
Mintegi  S, Gomez  B, Carro  A, Diaz  H, Benito  J.  Invasive bacterial infections in young afebrile infants with a history of fever.   Arch Dis Child. 2018;103(7):665-669. doi:10.1136/archdischild-2017-313578 PubMedGoogle Scholar
38.
Mintegi  S, Gomez  B, Martinez-Virumbrales  L, Morientes  O, Benito  J.  Outpatient management of selected young febrile infants without antibiotics.   Arch Dis Child. 2017;102(3):244-249. doi:10.1136/archdischild-2016-310600 PubMedGoogle ScholarCrossref
39.
Martinez  E, Mintegi  S, Vilar  B,  et al.  Prevalence and predictors of bacterial meningitis in young infants with fever without a source.   Pediatr Infect Dis J. 2015;34(5):494-498. doi:10.1097/INF.0000000000000629 PubMedGoogle ScholarCrossref
40.
Gomez  B, Mintegi  S, Rubio  MC, Garcia  D, Garcia  S, Benito  J.  Clinical and analytical characteristics and short-term evolution of enteroviral meningitis in young infants presenting with fever without source.   Pediatr Emerg Care. 2012;28(6):518-523. doi:10.1097/PEC.0b013e3182587d47 PubMedGoogle ScholarCrossref
41.
Garcia  S, Mintegi  S, Gomez  B,  et al.  Is 15 days an appropriate cut-off age for considering serious bacterial infection in the management of febrile infants?   Pediatr Infect Dis J. 2012;31(5):455-458. doi:10.1097/INF.0b013e318247b9f2 PubMedGoogle ScholarCrossref
42.
Gomez  B, Mintegi  S, Lopez  E, Romero  A, Paniagua  N, Benito  J.  Diagnostic value of leukopenia in young febrile infants.   Pediatr Infect Dis J. 2012;31(1):92-95. doi:10.1097/INF.0b013e3182337ddb PubMedGoogle ScholarCrossref
43.
Gómez  B, Mintegi  S, Benito  J, Egireun  A, Garcia  D, Astobiza  E.  Blood culture and bacteremia predictors in infants less than three months of age with fever without source.   Pediatr Infect Dis J. 2010;29(1):43-47. doi:10.1097/INF.0b013e3181c6dd14 PubMedGoogle ScholarCrossref
44.
Mintegi  S, Benito  J, Astobiza  E, Capapé  S, Gomez  B, Eguireun  A.  Well appearing young infants with fever without known source in the emergency department: are lumbar punctures always necessary?   Eur J Emerg Med. 2010;17(3):167-169. doi:10.1097/MEJ.0b013e3283307af9 PubMedGoogle ScholarCrossref
45.
Mintegi  S, Garcia-Garcia  JJ, Benito  J,  et al.  Rapid influenza test in young febrile infants for the identification of low-risk patients.   Pediatr Infect Dis J. 2009;28(11):1026-1028. doi:10.1097/INF.0b013e3181ab603c PubMedGoogle ScholarCrossref
46.
Benito-Fernández  J, Vázquez-Ronco  MA, Morteruel-Aizkuren  E, Mintegui-Raso  S, Sánchez-Etxaniz  J, Fernández-Landaluce  A.  Impact of rapid viral testing for influenza A and B viruses on management of febrile infants without signs of focal infection.   Pediatr Infect Dis J. 2006;25(12):1153-1157. doi:10.1097/01.inf.0000246826.93142.b0 PubMedGoogle ScholarCrossref
47.
Ramgopal  S, Janofsky  S, Zuckerbraun  NS,  et al.  Risk of serious bacterial infection in infants aged ≤60 days presenting to emergency departments with a history of fever only.   J Pediatr. 2019;204:191-195. doi:10.1016/j.jpeds.2018.08.043 PubMedGoogle ScholarCrossref
48.
Rogers  AJ, Kuppermann  N, Anders  J,  et al; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network (PECARN).  Practice variation in the evaluation and disposition of febrile infants ≤60 days of age.   J Emerg Med. 2019;56(6):583-591. doi:10.1016/j.jemermed.2019.03.003 PubMedGoogle ScholarCrossref
49.
Mahajan  P, Browne  LR, Levine  DA,  et al; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network (PECARN).  Risk of bacterial coinfections in febrile infants 60 days old and younger with documented viral infections.   J Pediatr. 2018;203:86-91.e2. doi:10.1016/j.jpeds.2018.07.073 PubMedGoogle ScholarCrossref
50.
Powell  EC, Mahajan  PV, Roosevelt  G,  et al; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network (PECARN).  Epidemiology of bacteremia in febrile infants aged 60 days and younger.   Ann Emerg Med. 2018;71(2):211-216. doi:10.1016/j.annemergmed.2017.07.488 PubMedGoogle ScholarCrossref
51.
Cruz  AT, Mahajan  P, Bonsu  BK,  et al; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network.  Accuracy of complete blood cell counts to identify febrile infants 60 days or younger with invasive bacterial infections.   JAMA Pediatr. 2017;171(11):e172927. doi:10.1001/jamapediatrics.2017.2927 PubMedGoogle Scholar
52.
Mahajan  P, Kuppermann  N, Mejias  A,  et al; Pediatric Emergency Care Applied Research Network (PECARN).  Association of RNA biosignatures with bacterial infections in febrile infants aged 60 days or younger.   JAMA. 2016;316(8):846-857. doi:10.1001/jama.2016.9207 PubMedGoogle ScholarCrossref
53.
Kasmire  KE, Hoppa  EC, Patel  PP, Boch  KN, Sacco  T, Waynik  IY.  Reducing invasive care for low-risk febrile infants through implementation of a clinical pathway.   Pediatrics. 2019;143(3):e20181610. doi:10.1542/peds.2018-1610 PubMedGoogle Scholar
54.
Blaschke  AJ, Korgenski  EK, Wilkes  J,  et al.  Rhinovirus in febrile infants and risk of bacterial infection.   Pediatrics. 2018;141(2):e20172384. doi:10.1542/peds.2017-2384 PubMedGoogle Scholar
55.
Byington  CL, Reynolds  CC, Korgenski  K,  et al.  Costs and infant outcomes after implementation of a care process model for febrile infants.   Pediatrics. 2012;130(1):e16-e24. doi:10.1542/peds.2012-0127 PubMedGoogle ScholarCrossref
56.
Yaeger  JP, Moore  KA, Melly  SJ, Lovasi  GS.  Associations of neighborhood-level social determinants of health with bacterial infections in young, febrile infants.   J Pediatr. 2018;203:336-344.e1. doi:10.1016/j.jpeds.2018.08.020 PubMedGoogle ScholarCrossref
57.
Scarfone  R, Murray  A, Gala  P, Balamuth  F.  Lumbar puncture for all febrile infants 29-56 days old: a retrospective cohort reassessment study.   J Pediatr. 2017;187:200-205.e1. doi:10.1016/j.jpeds.2017.04.003 PubMedGoogle ScholarCrossref
58.
Gomez  B, Mintegi  S, Benito  J; Group for the Study of Febrile Infant of the RiSeuP-SPERG Network.  A prospective multicenter study of leukopenia in infants younger than ninety days with fever without source.   Pediatr Infect Dis J. 2016;35(1):25-29. doi:10.1097/INF.0000000000000919 PubMedGoogle ScholarCrossref
59.
Velasco  R, Benito  H, Mozun  R,  et al; Group for the Study of Febrile Infant of the RiSEUP-SPERG Network.  Importance of urine dipstick in evaluation of young febrile infants with positive urine culture: a Spanish Pediatric Emergency Research Group study.   Pediatr Emerg Care. 2016;32(12):851-855. doi:10.1097/PEC.0000000000000935 PubMedGoogle ScholarCrossref
60.
Velasco  R, Benito  H, Mozun  R,  et al; Group for the Study of Febrile Infant of the RiSEUP-SPERG Network.  Using a urine dipstick to identify a positive urine culture in young febrile infants is as effective as in older patients.   Acta Paediatr. 2015;104(1):e39-e44. doi:10.1111/apa.12789 PubMedGoogle ScholarCrossref
61.
Milcent  K, Faesch  S, Gras-Le Guen  C,  et al.  Use of procalcitonin assays to predict serious bacterial infection in young febrile infants.   JAMA Pediatr. 2016;170(1):62-69. doi:10.1001/jamapediatrics.2015.3210 PubMedGoogle ScholarCrossref
62.
Mintegi  S, Bressan  S, Gomez  B,  et al.  Accuracy of a sequential approach to identify young febrile infants at low risk for invasive bacterial infection.   Emerg Med J. 2014;31(e1):e19-e24. doi:10.1136/emermed-2013-202449 PubMedGoogle ScholarCrossref
63.
Gomez  B, Bressan  S, Mintegi  S,  et al.  Diagnostic value of procalcitonin in well-appearing young febrile infants.   Pediatrics. 2012;130(5):815-822. doi:10.1542/peds.2011-3575 PubMedGoogle ScholarCrossref
64.
Manzano  S, Bailey  B, Gervaix  A, Cousineau  J, Delvin  E, Girodias  JB.  Markers for bacterial infection in children with fever without source.   Arch Dis Child. 2011;96(5):440-446. doi:10.1136/adc.2010.203760 PubMedGoogle ScholarCrossref
65.
Manzano  S, Bailey  B, Girodias  J-B, Galetto-Lacour  A, Cousineau  J, Delvin  E.  Impact of procalcitonin on the management of children aged 1 to 36 months presenting with fever without source: a randomized controlled trial.   Am J Emerg Med. 2010;28(6):647-653. doi:10.1016/j.ajem.2009.02.022 PubMedGoogle ScholarCrossref
66.
Paquette  K, Cheng  MP, McGillivray  D, Lam  C, Quach  C.  Is a lumbar puncture necessary when evaluating febrile infants (30 to 90 days of age) with an abnormal urinalysis?   Pediatr Emerg Care. 2011;27(11):1057-1061. doi:10.1097/PEC.0b013e318235ea18 PubMedGoogle ScholarCrossref
67.
De  S, Williams  GJ, Hayen  A,  et al.  Republished: value of white cell count in predicting serious bacterial infection in febrile children under 5 years of age.   Postgrad Med J. 2015;91(1073):493-499. doi:10.1136/postgradmedj-2013-304754rep PubMedGoogle ScholarCrossref
68.
De  S, Williams  GJ, Hayen  A,  et al. Accuracy of the “traffic light” clinical decision rule for serious bacterial infections in young children with fever: a retrospective cohort study. BMJ. 2013;346(1):f866. doi:10.1016/j.jemermed.2013.04.013
69.
Craig  JC, Williams  GJ, Jones  M,  et al.  The accuracy of clinical symptoms and signs for the diagnosis of serious bacterial infection in young febrile children: prospective cohort study of 15 781 febrile illnesses.   BMJ. 2010;340:c1594. doi:10.1136/bmj.c1594 PubMedGoogle ScholarCrossref
70.
Krief  WI, Levine  DA, Platt  SL,  et al; Multicenter RSV-SBI Study Group of the Pediatric Emergency Medicine Collaborative Research Committee of the American Academy of Pediatrics.  Influenza virus infection and the risk of serious bacterial infections in young febrile infants.   Pediatrics. 2009;124(1):30-39. doi:10.1542/peds.2008-2915 PubMedGoogle ScholarCrossref
71.
Levine  DA, Platt  SL, Dayan  PS,  et al; Multicenter RSV-SBI Study Group of the Pediatric Emergency Medicine Collaborative Research Committee of the American Academy of Pediatrics.  Risk of serious bacterial infection in young febrile infants with respiratory syncytial virus infections.   Pediatrics. 2004;113(6):1728-1734. doi:10.1542/peds.113.6.1728 PubMedGoogle ScholarCrossref
72.
Chen  H-L, Hung  C-H, Tseng  H-I, Yang  R-C.  Circulating chemokine levels in febrile infants with serious bacterial infections.   Kaohsiung J Med Sci. 2009;25(12):633-639. doi:10.1016/S1607-551X(09)70568-6 PubMedGoogle ScholarCrossref
73.
Pediatric Emergency Care Applied Research Network (PECARN). Public Use Data Sets. Published 2019. Accessed September 15, 2019. https://pecarn.org/studyDatasets/
74.
Mahajan  P, Borgialli  D, Cator  A,  et al. Prevalence of bacteremia and meningitis in febrile infants ≥60 days with positive urinalyses in a multicenter network [meeting abstract]. Pediatrics. 2021;147(3):509-510. doi:10.1542/peds.147.3
75.
DeAngelis  C, Joffe  A, Wilson  M, Willis  E.  Iatrogenic risks and financial costs of hospitalizing febrile infants.   AJDC. 1983;137(12):1146-1149. doi:10.1001/archpedi.1983.02140380006003 PubMedGoogle Scholar
76.
Friedrich  JO, Adhikari  NK, Beyene  J.  Inclusion of zero total event trials in meta-analyses maintains analytic consistency and incorporates all available data.   BMC Med Res Methodol. 2007;7:5. doi:10.1186/1471-2288-7-5 PubMedGoogle ScholarCrossref
77.
Schnadower D, Kuppermann N, Macias CG, et al. Febrile infants with urinary tract infections at very low risk for adverse events and bacteremia. Pediatrics. 2010;126:1074-1083. doi:10.1542/peds.2010-0479
78.
Byington  CL, Kendrick  J, Sheng  X.  Normative cerebrospinal fluid profiles in febrile infants.   J Pediatr. 2011;158(1):130-134. doi:10.1016/j.jpeds.2010.07.022 PubMedGoogle ScholarCrossref
79.
Kestenbaum  LA, Ebberson  J, Zorc  JJ, Hodinka  RL, Shah  SS.  Defining cerebrospinal fluid white blood cell count reference values in neonates and young infants.   Pediatrics. 2010;125(2):257-264. doi:10.1542/peds.2009-1181 PubMedGoogle ScholarCrossref
80.
Thomson  J, Sucharew  H, Cruz  AT,  et al; Pediatric Emergency Medicine Collaborative Research Committee (PEM CRC) HSV Study Group.  Cerebrospinal fluid reference values for young infants undergoing lumbar puncture.   Pediatrics. 2018;141(3):e20173405. doi:10.1542/peds.2017-3405 PubMedGoogle Scholar
Limit 200 characters
Limit 25 characters
Conflicts of Interest Disclosure

Identify all potential conflicts of interest that might be relevant to your comment.

Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.

Err on the side of full disclosure.

If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response.

Not all submitted comments are published. Please see our commenting policy for details.

Limit 140 characters
Limit 3600 characters or approximately 600 words
    Original Investigation
    Pediatrics
    May 12, 2021

    Prevalence of Bacterial Meningitis Among Febrile Infants Aged 29-60 Days With Positive Urinalysis Results: A Systematic Review and Meta-analysis

    Author Affiliations
    • 1Division of Pediatric Emergency Medicine, Department of Pediatrics, Montreal Children's Hospital, McGill University Health Centre, Montreal, Quebec, Canada
    • 2Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
    • 3Division of Pediatric Emergency Medicine, Department of Pediatrics, British Columbia Children’s Hospital, University of British Columbia, Vancouver, British Columbia, Canada
    • 4British Columbia Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
    • 5Department Obstetrics and Gynaecology, University of British Columbia, Vancouver, British Columbia, Canada
    • 6Division of Pediatric Emergency Medicine, Department of Emergency Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
    JAMA Netw Open. 2021;4(5):e214544. doi:10.1001/jamanetworkopen.2021.4544
    Key Points

    Question  Are well-appearing febrile infants 29 to 60 days of age with positive urinalysis results at increased risk for bacterial meningitis?

    Findings  In a systematic review and meta-analysis of 17 distinct international data sets (25 374 infants), the pooled prevalence of bacterial meningitis among infants with positive urinalysis results ranged from 0.25% (by cerebrospinal fluid [CSF] cultures or clinical definition) to 0.44% (by CSF cultures only). Prevalence estimates were not higher compared with infants who had negative urinalysis results (0.28% by CSF cultures or clinical definition and 0.50% by CSF cultures only).

    Meaning  These findings suggest that, contrary to all published guidelines, invasive CSF testing in well-appearing febrile infants in the second month of life based on a positive urinalysis result alone is not supported by differential risk ratios.

    Abstract

    Importance  Fever in the first months of life remains one of the most common pediatric problems. Urinary tract infections are the most frequent serious bacterial infections in this population. All published guidelines and quality initiatives for febrile young infants recommend lumbar puncture (LP) and cerebrospinal fluid (CSF) testing on the basis of a positive urinalysis result to exclude bacterial meningitis as a cause. For well infants older than 28 days with an abnormal urinalysis result, LP remains controversial.

    Objective  To assess the prevalence of bacterial meningitis among febrile infants 29 to 60 days of age with a positive urinalysis result to evaluate whether LP is routinely required.

    Data Sources  MEDLINE and Embase were searched for articles published from January 1, 2000, to July 25, 2018, with deliberate limitation to recent studies. Before analysis, the search was repeated (October 6, 2019) to ensure that new studies were included.

    Study Selection  Studies that reported on healthy, full-term, well-appearing febrile infants 29 to 60 days of age for whom patient-level data could be ascertained for urinalysis results and meningitis status were included.

    Data Extraction and Synthesis  Data were extracted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines and used the Newcastle-Ottawa Scale to assess bias. Pooled prevalences and odds ratios (ORs) were estimated using random-effect models.

    Main Outcomes and Measures  The primary outcome was the prevalence of culture-proven bacterial meningitis among infants with positive urinalysis results. The secondary outcome was the prevalence of bacterial meningitis, defined by CSF testing or suggestive history at clinical follow-up.

    Results  The parent search yielded 3227 records; 48 studies were included (17 distinct data sets of 25 374 infants). The prevalence of culture-proven meningitis was 0.44% (95% CI, 0.25%-0.78%) among 2703 infants with positive urinalysis results compared with 0.50% (95% CI, 0.33%-0.76%) among 10 032 infants with negative urinalysis results (OR, 0.74; 95% CI, 0.39-1.38). The prevalence of bacterial meningitis was 0.25% (95% CI, 0.14%-0.45%) among 4737 infants with meningitis status ascertained by CSF testing or clinical follow-up and 0.28% (95% CI, 0.21%-0.36%) among 20 637 infants with positive and negative urinalysis results (OR, 0.89; 95% CI, 0.48-1.68).

    Conclusions and Relevance  In this systematic review and meta-analysis, the prevalence of bacterial meningitis in well-appearing febrile infants 29 to 60 days of age with positive urinalysis results ranged from 0.25% to 0.44% and was not higher than that in infants with negative urinalysis results. These results suggest that for these infants, the decision to use LP should not be guided by urinalysis results alone.

    Introduction

    Fever among infants in the first months of life remains among the most common problems in pediatric health care.1 These infants are at increased risk for potentially life-threatening serious bacterial infections (SBIs), specifically urinary tract infections (UTIs), bacteremia, and bacterial meningitis.2 Approximately 10% of febrile infants 60 days or younger have underlying UTIs,2 which presents a theoretical risk of hematogenous spread to the meninges. Consequently, infants with UTIs have historically been considered at increased risk for bacterial meningitis. To avoid missing 1 case of bacterial meningitis, nearly 400 infants will routinely undergo invasive cerebrospinal fluid (CSF) testing by lumbar puncture (LP), hospitalization, and broad-spectrum antibiotic therapy.3

    Failure to detect concomitant meningitis among infants with UTIs is associated with serious sequalae. Modern urinalyses accurately predict UTIs among young infants.4 A presumptive diagnosis of UTI relies entirely on urinalysis results at initial evaluation before urine culture results are available. To date, all published risk-stratification strategies5-14 and large-scale quality improvement initiatives15,16 for febrile young infants include a positive urinalysis result as a high-risk feature, prompting LP, hospitalization, and empirical antibiotic treatment.

    Given the changing epidemiology of SBIs17 and risks that decrease with infant age,2,18 the necessity of LP for infants older than 28 days with a presumptive UTI has been questioned for decades.19,20 Previous studies21,22 suggest that a presumptive UTI is not associated with an increased risk of bacterial meningitis among well-appearing infants older than 28 days and that urinalysis results should not alter decisions regarding CSF testing. However, given the low overall prevalence of bacterial meningitis in this age group (approximately 0.4%),18 no single study has been powered to determine the true risk of meningitis among well infants with a positive urinalysis result. The objectives of this study were to estimate the prevalence of bacterial meningitis among well-appearing febrile infants 29 to 60 days of age with positive urinalysis results and to compare this prevalence with that of infants with negative urinalysis results to inform whether routine LP is required.

    Methods

    This study was registered prospectively in the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42019122218) and followed Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline.23 The British Columbia Children’s Hospital Research Ethics Board determined that ethics approval was not required.

    Search Strategy

    We performed a comprehensive search of MEDLINE and Ovid Embase for articles published from January 1, 2000, to July 25, 2018. Before analysis, the search was repeated (October 6, 2019) to ensure new studies were included. Results were limited to articles published in English or French. The search was deliberately limited to studies published on or after January 1, 2000, to account for evolving clinical practice standards related to (1) changing epidemiology of SBIs attributable to widespread vaccination programs and group B Streptococcus prenatal screening and prophylaxis17,18 and (2) more uniform and stringent definitions of UTI.24

    The search strategy was conceptualized by all study authors with the assistance of a medical librarian guided by published Medical Subject Heading terms and keywords.25 Broadly, the search combined the terms fever AND (urinary tract infection OR lumbar puncture OR meningitis) AND infant (eFigure 1 in the Supplement). Additional studies were identified through searching references of qualifying studies and systematic reviews. We included both prospective and retrospective studies with primary data. Narrative reviews, case reports, editorials, and guidelines were excluded.

    Study Selection and Definitions

    Studies were eligible if they reported on previously healthy, full-term (≥37 weeks’ gestation), well-appearing (documented by unstructured physician assessment or validated observation score26) infants 29 to 60 days of age and evaluated for fever (documented rectal temperature of ≥38 °C). Results of urinalysis by microscopy or dipstick were eligible for inclusion.27 A positive urinalysis result was defined as any finding of leukocyte esterase or nitrites, a white blood cell count of 10/μL (0.01 × 109/L) or higher on an uncentrifuged specimen (or ≥5/μL [0.01 × 109/L] per high-power field on a centrifuged specimen), or a positive Gram stain result.28 Studies enrolling only infants with proven infections (viral or bacterial) or abnormal laboratory test results (eg, only infants with a positive urinalysis result) were excluded.

    We contacted authors for patient-level data from studies that reported aggregate data only, those that reported UTI prevalence rather than urinalysis data specifically, and those enrolling with broader inclusion criteria. We included only studies from which we could ascertain both urinalysis results and meningitis status and only if meningitis status was determined by CSF testing or clinical follow-up when CSF was not obtained. We excluded studies in which we could not ascertain the number of infants with positive urinalysis results who underwent LP or whether meningitis status was based solely on CSF pleocytosis. To avoid double counting individual infants, publications that originated from the same source population were consolidated and analyzed as a single data set and cited by the most recent publication.

    The primary outcome measure was the prevalence of definite meningitis among infants with positive urinalysis results, proven by CSF culture yielding pathogenic bacteria. The secondary outcome measure was the prevalence of meningitis among infants with positive urinalysis results, using a pragmatic clinical definition: a positive CSF culture result, bacteremia with CSF pleocytosis, or a suggestive history at clinical follow-up if CSF was not obtained.

    Identification and Data Extraction

    Titles and abstracts were screened independently by 3 study investigators (V.S., F.F.M., and G.D.M.), and potentially eligible studies were evaluated for inclusion by full-text review (B.B. and F.F.M. or V.S. and G.D.M.) using standardized criteria determined a priori, with discrepancies resolved by an additional study investigator. Interreviewer agreement was tested using the Light or Cohen κ.

    Data extraction was performed by 1 study investigator (B.B.) using standardized data extraction criteria, and 2 additional investigators (V.S. and G.D.M) reviewed data extraction to validate accuracy. Extracted data included study characteristics (country, methodological design, method of recruitment, study years, publication year, study definitions, and follow-up duration when applicable) and participant characteristics (age, urinalysis results, and meningitis status).

    Appraisal of Methodological Quality

    Studies were assessed for methodological quality and risk of bias using the Newcastle-Ottawa Scale (NOS) checklist for nonrandomized cohort studies,29 as recommended by the Cochrane Collaborative.30 The NOS was adapted for this appraisal, and studies were considered at high risk for bias if they received less than 4 of 10 points (eFigure 2 in the Supplement).31 Because the data of interest were often not the primary outcomes of the included studies, items on the scale were scored on the quality of the design relative to the outcomes of this analysis rather than that of the original study objective. Two study investigators (V.S. and G.D.M.) independently appraised all data sets for methods, and discrepancies were resolved by a third (B.B.).

    Statistical Analysis

    Meta-analyses were performed to assess the pooled prevalence of bacterial meningitis and to estimate odds ratios (ORs) comparing infants with positive urinalysis results and infants with negative urinalysis results. Meta-analyses were conducted using a random-effects model because substantial heterogeneity was anticipated based on differing study designs. Pooled proportions and ORs were estimated after being transformed with the logit function using generalized logistic regression models, which perform well for sparse data.32 Results were summarized in forest plots. To assess the robustness of pooled estimates, sensitivity analyses were planned a priori: (1) excluding studies at high risk for bias (NOS score <4), (2) analyzing only prospectively collected data sets, and (3) considering only studies with clinical follow-up of 7 days or more and those with follow-up of 30 days or more. Heterogeneity was estimated using I2 statistics and prediction intervals.33 A continuity correction of 0.05 was added to studies with 0 events to allow inclusion in funnel plots. Pooled proportions were assessed for publication bias by graphical inspection of funnel plots and by using the Egger test for OR estimates because there were few events per study. All analyses were performed using the meta package in R software, version 3.5.3 (R Foundation for Statistical Computing).34

    Results

    Search of the electronic databases yielded 3227 unique publications, with an additional 12 identified by searching references of relevant studies. After removing 588 duplicates, screening by title and abstract identified 134 studies for full-text review; 34 did not meet inclusion, and 100 required author contact for patient-level data. Following contact with primary authors, 52 additional studies were excluded, 36 because authors could not be reached or were unable to provide required data (description of excluded studies in eTable 1 in the Supplement). In total, 48 individual studies1,4,11,12,14,15,17,21,22,26,35-72 were included for meta-analysis, with all data confirmed by the original authors for accuracy. Studies that originated from the same cohort were consolidated into a single data set for analysis. Ultimately, 17 distinct data sets were included in the analysis (Figure 1).

    Descriptive characteristics of included studies are presented in Table 1, including years, study design, setting, follow-up duration, and number of eligible infants. Complete urinalysis data and meningitis status were available for 25 374 previously healthy, well-appearing full-term infants 29 to 60 days of age. All studies were published in peer-reviewed journals. Eight of 17 data sets enrolled infants in the US.14,21,22,53,54,56,57,70 Nine data sets were prospectively collected,12,14,35,58,61,64,67,70,72 and 1 study53 used a pre/post intervention design in which only infants from the postintervention period were analyzed prospectively. Two additional data sets were retrospective analyses22,54 of infants managed in the context of quality improvement initiatives. These 2 data sets were included among the sensitivity analysis of prospective studies because all relevant covariates were collected prospectively. Methodological quality of included data sets varied widely, with NOS scores ranging from 3 to 8, and 1 study66 at high risk for bias (eTable 2 in the Supplement).

    Among included data sets, meningitis status was determined by CSF testing for 12 735 infants and by CSF testing or clinical follow-up for 25 374 infants. For both the primary and secondary outcomes, the unweighted proportion of infants with bacterial meningitis was higher among infants with negative urinalysis results in 9 data sets,14,21,22,35,53,54,58,66,70 higher among infants with positive urinalysis results in a single data set,61 and 0 in both groups in 7 data sets.12,56,57,62,64,67,72 The 7 data sets reporting 0 cases of meningitis in both groups did not contribute to the pooled OR, and several data sets had estimated ORs greater than 1 despite 0 events in the group with positive urinalysis results because of imbalanced sample sizes.

    For the primary outcome measure (Figure 2), there were 12 cases of culture-proven meningitis among 2703 infants with positive urinalysis results (95% CI, 0.25%-0.78%) and 56 cases among 10 032 infants with negative urinalysis results (OR, 0.74; 95% CI, 0.39-1.38). The pooled prevalence of bacterial meningitis was 0.44% (95% CI, 0.25%-0.78%; I2 = 0%) (Figure 2A) among infants with positive urinalysis results and 0.50% (95% CI, 0.33%-0.76%; I2 = 14%) (Figure 2B) among infants with negative urinalysis results (pooled OR, 0.74; 95% CI, 0.39%-1.38%; I2 = 0%) (Figure 2C).

    For the secondary outcome measure of bacterial meningitis status determined by CSF testing or clinical follow-up (Figure 3), there were 12 cases among 4737 infants with positive urinalysis results and 57 cases among 20 637 infants with negative urinalysis results. The pooled prevalence was 0.25% (95% CI, 0.14%-0.45%; I2 = 0%) (Figure 3A) among infants with positive urinalysis results and 0.28% (95% CI, 0.21%-0.36%; I2 = 0%) (Figure 3B) among infants with negative urinalysis results (pooled OR, 0.89; 95% CI, 0.48%-1.68%; I2 = 0%) (Figure 3C).

    Funnel plots for both outcome measures demonstrated symmetrical distributions around all pooled estimates, graphically not suggestive of publication bias (eFigure 3 in the Supplement). The Egger test for the primary and secondary outcome OR estimates were similarly not suggestive of publication bias.

    We conducted sensitivity analyses (1) excluding studies at high risk for bias, (2) analyzing only prospectively collected data, and (3) considering only studies with clinical follow-up of 7 days or more and 30 days or more (eFigures 4, 5, 6, and 7 in the Supplement). The estimates for data sets with 30 days or more of follow-up (eFigure 7 in the Supplement) were most different from the full analysis because of inclusion of the fewest data sets (n = 5) but produced the lowest ORs. Overall, results of sensitivity analyses did not differ significantly, lending confidence to findings of the primary analyses (Table 2).

    Discussion

    This systematic review and meta-analysis is the largest and most comprehensive study, to our knowledge, to evaluate the risk among well-appearing febrile infants older than 28 days with a positive urinalysis result. Accurate prevalence estimates are essential for practitioners to quantify the risk of concomitant bacterial meningitis and to inform clinical decision-making. The present analysis combined data from 17 unique data sets with more than 25 000 infants from geographically diverse populations. The results suggest that infants with a positive urinalysis result are at no higher risk for bacterial meningitis than infants with a negative urinalysis result. This finding is contrary to the dogma held for nearly 30 years.6 Historically, all risk-stratification criteria, including very recently derived clinical decision rules,5-14 categorize a positive urinalysis result as a high-risk feature, prompting invasive testing, broad-spectrum antibiotic exposure, and hospitalization. Although this practice has been controversial for decades, the very low overall prevalence of bacterial meningitis has meant that no single study could reliably answer this clinical question.20-22,31,66 This large meta-analysis provides compelling evidence that decisions regarding LP for this subgroup of infants should not be guided by urinalysis results alone.

    The evaluation of febrile young infants is invasive, anxiety-provoking for parents, and associated with iatrogenic risk and significant system-wide resource use.75 Since 2016, improved care for febrile young infants has become the largest US-wide quality initiative ever endorsed by the American Academy of Pediatrics, including 124 independent hospitals across 38 US states.15 Widely disseminated clinical pathways and electronic decision-support tools have been developed, which classify infants 29 to 60 days of age with a positive urinalysis result at increased risk for bacterial meningitis and recommend LP; conversely, infants with a negative urinalysis result are classified as low risk, and LP is not required.16 Findings from this analysis are in contrast to these recommendations.

    Strengths and Limitations

    One strength of the current analysis is the calculation of pooled ORs rather than only prevalence estimates,31 which must be compared with historical controls.18 This analysis allows a direct comparison of prevalences and an estimation of odds among infants with positive and negative urinalysis results within included studies. Of note, the pooled ORs for the primary and secondary outcomes were below 1, supporting the conclusion that infants with positive urinalysis results are not at higher risk for bacterial meningitis. In fact, the prevalence of meningitis was higher among infants with positive urinalysis results in just a single medium-sized data set.61 Moreover, another large data set74 has since enrolled many additional infants with an even lower relative risk among those with positive urinalysis results than was available at the time of analysis. Furthermore, 3 data sets reported 0 cases of meningitis in the urinalysis-positive group and 1 case or more in the urinalysis-negative group but generated ORs greater than 1.35,66,70 Paradoxical ORs such as these are possible when there is an imbalance in sample sizes, and the smaller sample has 0 events. Inclusion of these studies is known to bias pooled ORs toward the null.76 Taken together, it is likely that pooled OR point estimates reported are, if anything, an overestimate.

    A novel contribution of this analysis was the purposeful exclusion of studies before the year 2000 to account for changing SBI epidemiology.17,18 The current analysis differs importantly from a recent small meta-analysis,31 which consisted primarily of retrospective studies using a culture-proven UTI case definition. Similar to estimates reported here, Nugent et al31 reported 11 cases of bacterial meningitis among 3868 infants 29 to 90 days of age with an abnormal urinalysis result or culture-confirmed UTI who underwent LP (pooled prevalence, 0.25%). However, their analysis did not estimate the prevalence among infants with negative urinalysis results; thus, no direct comparison could be made or OR calculated. In addition, results of this analysis were driven largely by a single study77 that contributed 1609 infants selected on the basis of a culture-confirmed UTI not urinalysis results. Of importance, clinical decisions about LP and hospitalization rely on initial urinalysis results not urine culture results. A urinalysis is highly sensitive (0.94; 95% CI, 0.91-0.97) and specific (0.91; 95% CI, 0.90-0.91) for UTIs in febrile young infants.4 A urinalysis is also the most universally used diagnostic test for risk stratification,2,48 and an abnormal urinalysis result is among the most frequent reasons that infants do not meet low-risk criteria.57

    There are several additional strengths of the current analysis. The study population does not include infants from studies that selected infants on the basis of a clear focus of infection and thus addresses the most common and challenging clinical conundrum when evaluating well-appearing febrile young infants. Authors were contacted to obtain patient-level data and to accurately consolidate overlapping studies to prevent repeat counting of individual infants. Sensitivity analyses were selected a priori and increase the confidence in the results of the main analysis. Measures were taken to assess the possibility of publication bias, which does not appear to have influenced the results to any significant degree.

    This analysis also has limitations. It is possible that the pooled prevalence of meningitis among infants with negative urinalysis results reported is falsely elevated because infants with a normal urinalysis result who did not undergo CSF testing would not be included in the denominator. However, studies with clinical follow-up of at least 7 and 30 days would capture these infants, and sensitivity analyses reveal OR point estimates that are still not higher among infants with positive urinalysis results. The secondary outcome used a pragmatic clinical definition of meningitis, and neither a threshold for CSF pleocytosis78-80 nor a definition of history suggestive of meningitis at follow-up was prespecified; rather, the outcomes were reported as classified by the primary study authors. Fifty-two studies were excluded (several with overlapping data sets), including 36 for which patient-level data were not available. Bias introduced by their exclusion is theoretically possible; however, it is unlikely that these infants were systematically different from those analyzed. In all studies, the decision to perform an LP was at the discretion of the treating physician; however, the sensitivity analysis limited to studies with follow-up of 30 days or more with the lowest pooled ORs mitigates the risk of missing cases of bacterial meningitis among infants without CSF testing or a short clinical follow-up. Although every attempt has been made to not double count infants, the possibility cannot be completely excluded given that several included studies were large national or multinational studies, although most data sets did not overlap temporally or geographically. Only studies published in English or French were included, and most were conducted in emergency departments; therefore, estimates may not be generalizable to other settings (ie, ambulatory clinics or unrepresented countries). In addition, pooled prevalence estimates are associated with the urinalysis status in isolation, and the risk when other diagnostic biomarkers are also within normal limits was not assessed (ie, C-reactive protein and procalcitonin). Studies with 0 events provide challenges in estimation with traditional meta-analytic methods; as such, generalized linear mixed-effects models were used to compensate. High heterogeneity across studies was expected, and qualitatively this was true based on study methods. Despite this, for some outcomes, the I2 statistics could not be accurately estimated because of the small (and 0) event rates in many studies.76 For these estimates, the prediction intervals must be relied on to provide a relevant alternative measure of the heterogeneity and are reported for all analyses.

    Conclusions

    Invasive CSF testing, hospitalization, and empirical antibiotic treatment of well-appearing febrile infants older than 28 days with a positive urinalysis result have been predicated for decades on the assumption of an increased risk of bacterial meningitis. Despite fever in young infants being a common clinical problem, no single study to date has been adequately large to reliably determine the true relative risk among infants with positive urinalysis results. Findings from this large meta-analysis suggest that well-appearing febrile infants 29 to 60 days of age with a positive urinalysis result are not at an elevated risk for bacterial meningitis compared with infants with negative urinalysis results. Overall, these results suggest that the rate of concomitant bacterial meningitis in this population is low, and LP should not be undertaken on the basis of a positive urinalysis result alone.

    Back to top
    Article Information

    Accepted for Publication: February 15, 2021.

    Published: May 12, 2021. doi:10.1001/jamanetworkopen.2021.4544

    Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Burstein B et al. JAMA Network Open.

    Corresponding Author: Brett Burstein, MD, CM, PhD, MPH, Division of Pediatric Emergency Medicine, Montreal Children’s Hospital, 1001 Decarie Blvd, Montreal, Quebec H4C 3J1, Canada (brett.burstein@mail.mcgill.ca).

    Author Contributions: Dr Burstein had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Burstein, Sabhaney, Doan, Meckler.

    Acquisition, analysis, or interpretation of data: All authors.

    Drafting of the manuscript: Burstein, Doan, Meckler.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Burstein, Bone, Doan.

    Administrative, technical, or material support: Sabhaney, Doan, Meckler.

    Supervision: Burstein, Sabhaney, Doan, Meckler.

    Conflict of Interest Disclosures: Dr Burstein is the recipient of a career award from the Québec Health Research Fund. No other disclosures reported.

    Additional Contributions: The medical librarians Mimi Doyle-Waters, MA, MLIS, Centre for Clinical Epidemiology and Evaluation, University of British Columbia, Vancouver, British Columbia, Canada, and Genevieve Gore, MLIS, Schulich Library of Physical Sciences, Life Sciences and Engineering, McGill University, Montreal, Quebec, Canada, assisted with the search strategies, Boris Kuzeljevic, MA, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada, provided statistical support, and Gregory Anderson, MSc, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada, provided technical support. B. Bailey, MD, Department of Pediatric Emergency Medicine, CHU Sainte-Justine, Montreal, Quebec, Canada, A. J. Blaschke, MD PhD, Department of Pediatrics, School of Medicine, University of Utah, Salt Lake City, Utah, C. L. Byington, MD, Department of Pediatrics, School of Medicine, University of Utah, Salt Lake City, Utah, H. L. Chen, MD, Division of Neonatology, Department of Pediatrics, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, B. Gomez, MD, PhD, Pediatric Emergency Department, Cruces University Hospital, University of the Basque Country, Basque Country, Spain, T. L. Greenhow, MD, Division of Infectious Diseases, Department of Pediatrics, Kaiser Permanente Northern California, San Francisco, California, K. E. Kasmire, MD, MS, Connecticut Children's Medical Center, University of Connecticut, Farmington, Connecticut, W. I. Krief, MD, Department of Pediatrics, Cohen Children’s Medical Center, Northwell Health, New Hyde Park, New York, N. Kuppermann, MD, MPH, Departments of Emergency Medicine and Pediatrics, University of California, Davis School of Medicine, Sacramento, California, S. Manzano, MD, Division of Pediatric Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland, K. Milcent, MD, MSc, Department of Pediatrics, Antoine Béclère University Hospital, Assistance Publique-Hôpitaux de Paris, Clamart, France, S. Mintegi, MD, PhD, Pediatric Emergency Department, Cruces University Hospital, University of the Basque Country, Basque Country, Spain, C. Quach, MD, MSc, Department of Microbiology, Infectious Diseases, and Immunology, Clinical Department of Laboratory Medicine, CHU Sainte-Justine, Université de Montréal, Montreal, Quebec, Canada, M. E. Wang, MD, PhD, Division of Pediatric Hospital Medicine, Department of Pediatrics, Lucile Packard Children’s Hospital Stanford, Stanford University, Palo Alto, California, G. J. Williams, BSc, MPH, PhD, Screening and Test Evaluation Program, School of Public Health, University of Sydney, Sydney, Australia, R. Velasco, MD, Pediatric Emergency Unit, Rio Hortega University Hospital, Valladolid, Spain, J. P. Yaeger, MD, MPH, Departments of Pediatrics and Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, New York, B. Young, MD, Department of Inpatient Pediatrics, Kaiser Permanente Northern California, Roseville, California, and their data managers shared and clarified the primary data from their respective studies. P.L. Aronson, MD, MHS, Departments Pediatrics and Emergency Medicine, Yale School of Medicine, Yale University, New Haven, Connecticut, and D. Schnadower, MD, MPH, Department of Pediatrics, Washington University School of Medicine in St Louis, St Louis, Missouri, shared data from studies that did not appear in the final analysis. Mimi Doyle-Waters, MA, MLIS, was compensated for her work.

    References
    1.
    Greenhow  TL, Hung  YY, Pantell  RH.  Management and outcomes of previously healthy, full-term, febrile infants ages 7 to 90 days.   Pediatrics. 2016;138(6):e20160270-e20160270. doi:10.1542/peds.2016-0270 PubMedGoogle ScholarCrossref
    2.
    Aronson  PL, Thurm  C, Alpern  ER,  et al; Febrile Young Infant Research Collaborative.  Variation in care of the febrile young infant <90 days in US pediatric emergency departments.   Pediatrics. 2014;134(4):667-677. doi:10.1542/peds.2014-1382 PubMedGoogle ScholarCrossref
    3.
    Aronson  PL, McCulloh  RJ, Tieder  JS,  et al; Febrile Young Infant Research Collaborative.  Application of the Rochester Criteria to identify febrile infants with bacteremia and meningitis.   Pediatr Emerg Care. 2019;35(1):22-27. doi:10.1097/PEC.0000000000001421 PubMedGoogle ScholarCrossref
    4.
    Tzimenatos  L, Mahajan  P, Dayan  PS,  et al; Pediatric Emergency Care Applied Research Network (PECARN).  Accuracy of the urinalysis for urinary tract infections in febrile infants 60 days and younger.   Pediatrics. 2018;141(2):e20173068. doi:10.1542/peds.2017-3068 PubMedGoogle Scholar
    5.
    Baskin  MN, O’Rourke  EJ, Fleisher  GR.  Outpatient treatment of febrile infants 28 to 89 days of age with intramuscular administration of ceftriaxone.   J Pediatr. 1992;120(1):22-27. doi:10.1016/S0022-3476(05)80591-8 PubMedGoogle ScholarCrossref
    6.
    Baraff  LJ, Bass  JW, Fleisher  GR,  et al; Agency for Health Care Policy and Research.  Practice guideline for the management of infants and children 0 to 36 months of age with fever without source.   Ann Emerg Med. 1993;22(7):1198-1210. doi:10.1016/S0196-0644(05)80991-6 PubMedGoogle ScholarCrossref
    7.
    Baker  MD, Bell  LM, Avner  JR.  Outpatient management without antibiotics of fever in selected infants.   N Engl J Med. 1993;329(20):1437-1441. doi:10.1056/NEJM199311113292001 PubMedGoogle ScholarCrossref
    8.
    Bonadio  WA, Hagen  E, Rucka  J, Shallow  K, Stommel  P, Smith  D.  Efficacy of a protocol to distinguish risk of serious bacterial infection in the outpatient evaluation of febrile young infants.   Clin Pediatr (Phila). 1993;32(7):401-404. doi:10.1177/000992289303200703 PubMedGoogle ScholarCrossref
    9.
    Jaskiewicz  JA, McCarthy  CA, Richardson  AC,  et al; Febrile Infant Collaborative Study Group.  Febrile infants at low risk for serious bacterial infection: an appraisal of the Rochester criteria and implications for management.   Pediatrics. 1994;94(3):390-396.PubMedGoogle Scholar
    10.
    Bachur  RG, Harper  MB.  Predictive model for serious bacterial infections among infants younger than 3 months of age.   Pediatrics. 2001;108(2):311-316. doi:10.1542/peds.108.2.311 PubMedGoogle ScholarCrossref
    11.
    Bressan  S, Gomez  B, Mintegi  S,  et al.  Diagnostic performance of the lab-score in predicting severe and invasive bacterial infections in well-appearing young febrile infants.   Pediatr Infect Dis J. 2012;31(12):1239-1244. doi:10.1097/INF.0b013e318266a9aa PubMedGoogle Scholar
    12.
    Gomez  B, Mintegi  S, Bressan  S, Da Dalt  L, Gervaix  A, Lacroix  L; European Group for Validation of the Step-by-Step Approach.  Validation of the “Step-by-Step” approach in the management of young febrile infants.   Pediatrics. 2016;138(2):e20154381. doi:10.1542/peds.2015-4381 PubMedGoogle Scholar
    13.
    Leroy  S, Bressan  S, Lacroix  L,  et al.  Refined lab-score, a risk score predicting serious bacterial infection in febrile children less than 3 years of age.   Pediatr Infect Dis J. 2018;37(5):387-393. doi:10.1097/INF.0000000000001915 PubMedGoogle ScholarCrossref
    14.
    Kuppermann  N, Dayan  PS, Levine  DA,  et al; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network (PECARN).  A Clinical prediction rule to identify febrile infants 60 days and younger at low risk for serious bacterial infections.   JAMA Pediatr. 2019;173(4):342-351. doi:10.1001/jamapediatrics.2018.5501 PubMedGoogle ScholarCrossref
    15.
    Biondi  EA, McCulloh  R, Staggs  VS,  et al; American Academy Of Pediatrics’ Revise Collaborative.  Reducing Variability in the Infant Sepsis Evaluation (REVISE): a national quality initiative.   Pediatrics. 2019;144(3):e20182201. doi:10.1542/peds.2018-2201 PubMedGoogle Scholar
    16.
    McCulloh  RJ, Fouquet  SD, Herigon  J,  et al.  Development and implementation of a mobile device-based pediatric electronic decision support tool as part of a national practice standardization project.   J Am Med Inform Assoc. 2018;25(9):1175-1182. doi:10.1093/jamia/ocy069 PubMedGoogle ScholarCrossref
    17.
    Greenhow  TL, Hung  Y-Y, Herz  AM, Losada  E, Pantell  RH.  The changing epidemiology of serious bacterial infections in young infants.   Pediatr Infect Dis J. 2014;33(6):595-599. doi:10.1097/INF.0000000000000225 PubMedGoogle ScholarCrossref
    18.
    Biondi  EA, Lee  B, Ralston  SL,  et al.  Prevalence of bacteremia and bacterial meningitis in febrile neonates and infants in the second month of life: a systematic review and meta-analysis.   JAMA Netw Open. 2019;2(3):e190874. doi:10.1001/jamanetworkopen.2019.0874 PubMedGoogle Scholar
    19.
    Berkwitt  AK, Grossman  MR, Aronson  PL.  Is it time to stop classifying febrile infants with positive urinalyses as high-risk for meningitis?   Hosp Pediatr. 2018;8(8):506-508. doi:10.1542/hpeds.2018-0064 PubMedGoogle ScholarCrossref
    20.
    Goldman  RD, Matlow  A, Linett  L, Scolnik  D.  What is the risk of bacterial meningitis in infants who present to the emergency department with fever and pyuria?   CJEM. 2003;5(6):394-399. doi:10.1017/S1481803500008630 PubMedGoogle ScholarCrossref
    21.
    Young  BR, Nguyen  THP, Alabaster  A, Greenhow  TL.  The prevalence of bacterial meningitis in febrile infants 29-60 days with positive urinalysis.   Hosp Pediatr. 2018;8(8):450-457. doi:10.1542/hpeds.2017-0254 PubMedGoogle ScholarCrossref
    22.
    Wang  ME, Biondi  EA, McCulloh  RJ,  et al.  Testing for meningitis in febrile well-appearing young infants with a positive urinalysis.   Pediatrics. 2019;144(3):e20183979. doi:10.1542/peds.2018-3979 PubMedGoogle Scholar
    23.
    Liberati  A, Altman  DG, Tetzlaff  J,  et al.  The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration.   BMJ. 2009;339:b2700. doi:10.1136/bmj.b2700 PubMedGoogle ScholarCrossref
    24.
    Roberts  KB, Wald  ER.  The diagnosis of UTI: colony count criteria revisited.   Pediatrics. 2018;141(2):e20173239. doi:10.1542/peds.2017-3239 PubMedGoogle Scholar
    25.
    Hui  C, Neto  G, Tsertsvadze  A,  et al.  Diagnosis and management of febrile infants (0-3 months).   Evid Rep Technol Assess (Full Rep). 2012;(205):1-297.PubMedGoogle Scholar
    26.
    Nigrovic  LE, Mahajan  PV, Blumberg  SM,  et al; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network (PECARN).  The Yale Observation Scale Score and the risk of serious bacterial infections in febrile infants.   Pediatrics. 2017;140(1):e20170695. doi:10.1542/peds.2017-0695 PubMedGoogle Scholar
    27.
    Glissmeyer  EW, Korgenski  EK, Wilkes  J,  et al.  Dipstick screening for urinary tract infection in febrile infants.   Pediatrics. 2014;133(5):e1121-e1127. doi:10.1542/peds.2013-3291 PubMedGoogle ScholarCrossref
    28.
    SUBCOMMITTEE ON URINARY TRACT INFECTION.  Reaffirmation of AAP clinical practice guideline: the diagnosis and management of the initial urinary tract infection in febrile infants and young children 2-24 months of age.   Pediatrics. 2016;138(6):e20163026-e20163026. doi:10.1542/peds.2016-3026 PubMedGoogle ScholarCrossref
    29.
    Wells  GA, Shea  B, O’Connell  D,  et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Accessed january 1, 2020. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp
    30.
    Stang  A.  Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses.   Eur J Epidemiol. 2010;25(9):603-605. doi:10.1007/s10654-010-9491-z PubMedGoogle ScholarCrossref
    31.
    Nugent  J, Childers  M, Singh-Miller  N, Howard  R, Allard  R, Eberly  M.  Risk of meningitis in infants aged 29 to 90 days with urinary tract infection: a systematic review and meta-analysis.   J Pediatr. 2019;212:102-110.e5. doi:10.1016/j.jpeds.2019.04.053 PubMedGoogle ScholarCrossref
    32.
    Stijnen  T, Hamza  TH, Ozdemir  P.  Random effects meta-analysis of event outcome in the framework of the generalized linear mixed model with applications in sparse data.   Stat Med. 2010;29(29):3046-3067. doi:10.1002/sim.4040 PubMedGoogle ScholarCrossref
    33.
    IntHout  J, Ioannidis  JP, Rovers  MM, Goeman  JJ.  Plea for routinely presenting prediction intervals in meta-analysis.   BMJ Open. 2016;6(7):e010247. doi:10.1136/bmjopen-2015-010247 PubMedGoogle Scholar
    34.
    Balduzzi  S, Rücker  G, Schwarzer  G.  How to perform a meta-analysis with R: a practical tutorial.   Evid Based Ment Health. 2019;22(4):153-160. doi:10.1136/ebmental-2019-300117 PubMedGoogle ScholarCrossref
    35.
    Bonilla  L, Gomez  B, Pintos  C, Benito  J, Mintegi  S.  Prevalence of bacterial infection in febrile infant 61-90 days old compared with younger infants.   Pediatr Infect Dis J. 2019;38(12):1163-1167. doi:10.1097/INF.0000000000002461 PubMedGoogle ScholarCrossref
    36.
    Gomez  B, Diaz  H, Carro  A, Benito  J, Mintegi  S.  Performance of blood biomarkers to rule out invasive bacterial infection in febrile infants under 21 days old.   Arch Dis Child. 2019;104(6):547-551. doi:10.1136/archdischild-2018-315397 PubMedGoogle ScholarCrossref
    37.
    Mintegi  S, Gomez  B, Carro  A, Diaz  H, Benito  J.  Invasive bacterial infections in young afebrile infants with a history of fever.   Arch Dis Child. 2018;103(7):665-669. doi:10.1136/archdischild-2017-313578 PubMedGoogle Scholar
    38.
    Mintegi  S, Gomez  B, Martinez-Virumbrales  L, Morientes  O, Benito  J.  Outpatient management of selected young febrile infants without antibiotics.   Arch Dis Child. 2017;102(3):244-249. doi:10.1136/archdischild-2016-310600 PubMedGoogle ScholarCrossref
    39.
    Martinez  E, Mintegi  S, Vilar  B,  et al.  Prevalence and predictors of bacterial meningitis in young infants with fever without a source.   Pediatr Infect Dis J. 2015;34(5):494-498. doi:10.1097/INF.0000000000000629 PubMedGoogle ScholarCrossref
    40.
    Gomez  B, Mintegi  S, Rubio  MC, Garcia  D, Garcia  S, Benito  J.  Clinical and analytical characteristics and short-term evolution of enteroviral meningitis in young infants presenting with fever without source.   Pediatr Emerg Care. 2012;28(6):518-523. doi:10.1097/PEC.0b013e3182587d47 PubMedGoogle ScholarCrossref
    41.
    Garcia  S, Mintegi  S, Gomez  B,  et al.  Is 15 days an appropriate cut-off age for considering serious bacterial infection in the management of febrile infants?   Pediatr Infect Dis J. 2012;31(5):455-458. doi:10.1097/INF.0b013e318247b9f2 PubMedGoogle ScholarCrossref
    42.
    Gomez  B, Mintegi  S, Lopez  E, Romero  A, Paniagua  N, Benito  J.  Diagnostic value of leukopenia in young febrile infants.   Pediatr Infect Dis J. 2012;31(1):92-95. doi:10.1097/INF.0b013e3182337ddb PubMedGoogle ScholarCrossref
    43.
    Gómez  B, Mintegi  S, Benito  J, Egireun  A, Garcia  D, Astobiza  E.  Blood culture and bacteremia predictors in infants less than three months of age with fever without source.   Pediatr Infect Dis J. 2010;29(1):43-47. doi:10.1097/INF.0b013e3181c6dd14 PubMedGoogle ScholarCrossref
    44.
    Mintegi  S, Benito  J, Astobiza  E, Capapé  S, Gomez  B, Eguireun  A.  Well appearing young infants with fever without known source in the emergency department: are lumbar punctures always necessary?   Eur J Emerg Med. 2010;17(3):167-169. doi:10.1097/MEJ.0b013e3283307af9 PubMedGoogle ScholarCrossref
    45.
    Mintegi  S, Garcia-Garcia  JJ, Benito  J,  et al.  Rapid influenza test in young febrile infants for the identification of low-risk patients.   Pediatr Infect Dis J. 2009;28(11):1026-1028. doi:10.1097/INF.0b013e3181ab603c PubMedGoogle ScholarCrossref
    46.
    Benito-Fernández  J, Vázquez-Ronco  MA, Morteruel-Aizkuren  E, Mintegui-Raso  S, Sánchez-Etxaniz  J, Fernández-Landaluce  A.  Impact of rapid viral testing for influenza A and B viruses on management of febrile infants without signs of focal infection.   Pediatr Infect Dis J. 2006;25(12):1153-1157. doi:10.1097/01.inf.0000246826.93142.b0 PubMedGoogle ScholarCrossref
    47.
    Ramgopal  S, Janofsky  S, Zuckerbraun  NS,  et al.  Risk of serious bacterial infection in infants aged ≤60 days presenting to emergency departments with a history of fever only.   J Pediatr. 2019;204:191-195. doi:10.1016/j.jpeds.2018.08.043 PubMedGoogle ScholarCrossref
    48.
    Rogers  AJ, Kuppermann  N, Anders  J,  et al; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network (PECARN).  Practice variation in the evaluation and disposition of febrile infants ≤60 days of age.   J Emerg Med. 2019;56(6):583-591. doi:10.1016/j.jemermed.2019.03.003 PubMedGoogle ScholarCrossref
    49.
    Mahajan  P, Browne  LR, Levine  DA,  et al; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network (PECARN).  Risk of bacterial coinfections in febrile infants 60 days old and younger with documented viral infections.   J Pediatr. 2018;203:86-91.e2. doi:10.1016/j.jpeds.2018.07.073 PubMedGoogle ScholarCrossref
    50.
    Powell  EC, Mahajan  PV, Roosevelt  G,  et al; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network (PECARN).  Epidemiology of bacteremia in febrile infants aged 60 days and younger.   Ann Emerg Med. 2018;71(2):211-216. doi:10.1016/j.annemergmed.2017.07.488 PubMedGoogle ScholarCrossref
    51.
    Cruz  AT, Mahajan  P, Bonsu  BK,  et al; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network.  Accuracy of complete blood cell counts to identify febrile infants 60 days or younger with invasive bacterial infections.   JAMA Pediatr. 2017;171(11):e172927. doi:10.1001/jamapediatrics.2017.2927 PubMedGoogle Scholar
    52.
    Mahajan  P, Kuppermann  N, Mejias  A,  et al; Pediatric Emergency Care Applied Research Network (PECARN).  Association of RNA biosignatures with bacterial infections in febrile infants aged 60 days or younger.   JAMA. 2016;316(8):846-857. doi:10.1001/jama.2016.9207 PubMedGoogle ScholarCrossref
    53.
    Kasmire  KE, Hoppa  EC, Patel  PP, Boch  KN, Sacco  T, Waynik  IY.  Reducing invasive care for low-risk febrile infants through implementation of a clinical pathway.   Pediatrics. 2019;143(3):e20181610. doi:10.1542/peds.2018-1610 PubMedGoogle Scholar
    54.
    Blaschke  AJ, Korgenski  EK, Wilkes  J,  et al.  Rhinovirus in febrile infants and risk of bacterial infection.   Pediatrics. 2018;141(2):e20172384. doi:10.1542/peds.2017-2384 PubMedGoogle Scholar
    55.
    Byington  CL, Reynolds  CC, Korgenski  K,  et al.  Costs and infant outcomes after implementation of a care process model for febrile infants.   Pediatrics. 2012;130(1):e16-e24. doi:10.1542/peds.2012-0127 PubMedGoogle ScholarCrossref
    56.
    Yaeger  JP, Moore  KA, Melly  SJ, Lovasi  GS.  Associations of neighborhood-level social determinants of health with bacterial infections in young, febrile infants.   J Pediatr. 2018;203:336-344.e1. doi:10.1016/j.jpeds.2018.08.020 PubMedGoogle ScholarCrossref
    57.
    Scarfone  R, Murray  A, Gala  P, Balamuth  F.  Lumbar puncture for all febrile infants 29-56 days old: a retrospective cohort reassessment study.   J Pediatr. 2017;187:200-205.e1. doi:10.1016/j.jpeds.2017.04.003 PubMedGoogle ScholarCrossref
    58.
    Gomez  B, Mintegi  S, Benito  J; Group for the Study of Febrile Infant of the RiSeuP-SPERG Network.  A prospective multicenter study of leukopenia in infants younger than ninety days with fever without source.   Pediatr Infect Dis J. 2016;35(1):25-29. doi:10.1097/INF.0000000000000919 PubMedGoogle ScholarCrossref
    59.
    Velasco  R, Benito  H, Mozun  R,  et al; Group for the Study of Febrile Infant of the RiSEUP-SPERG Network.  Importance of urine dipstick in evaluation of young febrile infants with positive urine culture: a Spanish Pediatric Emergency Research Group study.   Pediatr Emerg Care. 2016;32(12):851-855. doi:10.1097/PEC.0000000000000935 PubMedGoogle ScholarCrossref
    60.
    Velasco  R, Benito  H, Mozun  R,  et al; Group for the Study of Febrile Infant of the RiSEUP-SPERG Network.  Using a urine dipstick to identify a positive urine culture in young febrile infants is as effective as in older patients.   Acta Paediatr. 2015;104(1):e39-e44. doi:10.1111/apa.12789 PubMedGoogle ScholarCrossref
    61.
    Milcent  K, Faesch  S, Gras-Le Guen  C,  et al.  Use of procalcitonin assays to predict serious bacterial infection in young febrile infants.   JAMA Pediatr. 2016;170(1):62-69. doi:10.1001/jamapediatrics.2015.3210 PubMedGoogle ScholarCrossref
    62.
    Mintegi  S, Bressan  S, Gomez  B,  et al.  Accuracy of a sequential approach to identify young febrile infants at low risk for invasive bacterial infection.   Emerg Med J. 2014;31(e1):e19-e24. doi:10.1136/emermed-2013-202449 PubMedGoogle ScholarCrossref
    63.
    Gomez  B, Bressan  S, Mintegi  S,  et al.  Diagnostic value of procalcitonin in well-appearing young febrile infants.   Pediatrics. 2012;130(5):815-822. doi:10.1542/peds.2011-3575 PubMedGoogle ScholarCrossref
    64.
    Manzano  S, Bailey  B, Gervaix  A, Cousineau  J, Delvin  E, Girodias  JB.  Markers for bacterial infection in children with fever without source.   Arch Dis Child. 2011;96(5):440-446. doi:10.1136/adc.2010.203760 PubMedGoogle ScholarCrossref
    65.
    Manzano  S, Bailey  B, Girodias  J-B, Galetto-Lacour  A, Cousineau  J, Delvin  E.  Impact of procalcitonin on the management of children aged 1 to 36 months presenting with fever without source: a randomized controlled trial.   Am J Emerg Med. 2010;28(6):647-653. doi:10.1016/j.ajem.2009.02.022 PubMedGoogle ScholarCrossref
    66.
    Paquette  K, Cheng  MP, McGillivray  D, Lam  C, Quach  C.  Is a lumbar puncture necessary when evaluating febrile infants (30 to 90 days of age) with an abnormal urinalysis?   Pediatr Emerg Care. 2011;27(11):1057-1061. doi:10.1097/PEC.0b013e318235ea18 PubMedGoogle ScholarCrossref
    67.
    De  S, Williams  GJ, Hayen  A,  et al.  Republished: value of white cell count in predicting serious bacterial infection in febrile children under 5 years of age.   Postgrad Med J. 2015;91(1073):493-499. doi:10.1136/postgradmedj-2013-304754rep PubMedGoogle ScholarCrossref
    68.
    De  S, Williams  GJ, Hayen  A,  et al. Accuracy of the “traffic light” clinical decision rule for serious bacterial infections in young children with fever: a retrospective cohort study. BMJ. 2013;346(1):f866. doi:10.1016/j.jemermed.2013.04.013
    69.
    Craig  JC, Williams  GJ, Jones  M,  et al.  The accuracy of clinical symptoms and signs for the diagnosis of serious bacterial infection in young febrile children: prospective cohort study of 15 781 febrile illnesses.   BMJ. 2010;340:c1594. doi:10.1136/bmj.c1594 PubMedGoogle ScholarCrossref
    70.
    Krief  WI, Levine  DA, Platt  SL,  et al; Multicenter RSV-SBI Study Group of the Pediatric Emergency Medicine Collaborative Research Committee of the American Academy of Pediatrics.  Influenza virus infection and the risk of serious bacterial infections in young febrile infants.   Pediatrics. 2009;124(1):30-39. doi:10.1542/peds.2008-2915 PubMedGoogle ScholarCrossref
    71.
    Levine  DA, Platt  SL, Dayan  PS,  et al; Multicenter RSV-SBI Study Group of the Pediatric Emergency Medicine Collaborative Research Committee of the American Academy of Pediatrics.  Risk of serious bacterial infection in young febrile infants with respiratory syncytial virus infections.   Pediatrics. 2004;113(6):1728-1734. doi:10.1542/peds.113.6.1728 PubMedGoogle ScholarCrossref
    72.
    Chen  H-L, Hung  C-H, Tseng  H-I, Yang  R-C.  Circulating chemokine levels in febrile infants with serious bacterial infections.   Kaohsiung J Med Sci. 2009;25(12):633-639. doi:10.1016/S1607-551X(09)70568-6 PubMedGoogle ScholarCrossref
    73.
    Pediatric Emergency Care Applied Research Network (PECARN). Public Use Data Sets. Published 2019. Accessed September 15, 2019. https://pecarn.org/studyDatasets/
    74.
    Mahajan  P, Borgialli  D, Cator  A,  et al. Prevalence of bacteremia and meningitis in febrile infants ≥60 days with positive urinalyses in a multicenter network [meeting abstract]. Pediatrics. 2021;147(3):509-510. doi:10.1542/peds.147.3
    75.
    DeAngelis  C, Joffe  A, Wilson  M, Willis  E.  Iatrogenic risks and financial costs of hospitalizing febrile infants.   AJDC. 1983;137(12):1146-1149. doi:10.1001/archpedi.1983.02140380006003 PubMedGoogle Scholar
    76.
    Friedrich  JO, Adhikari  NK, Beyene  J.  Inclusion of zero total event trials in meta-analyses maintains analytic consistency and incorporates all available data.   BMC Med Res Methodol. 2007;7:5. doi:10.1186/1471-2288-7-5 PubMedGoogle ScholarCrossref
    77.
    Schnadower D, Kuppermann N, Macias CG, et al. Febrile infants with urinary tract infections at very low risk for adverse events and bacteremia. Pediatrics. 2010;126:1074-1083. doi:10.1542/peds.2010-0479
    78.
    Byington  CL, Kendrick  J, Sheng  X.  Normative cerebrospinal fluid profiles in febrile infants.   J Pediatr. 2011;158(1):130-134. doi:10.1016/j.jpeds.2010.07.022 PubMedGoogle ScholarCrossref
    79.
    Kestenbaum  LA, Ebberson  J, Zorc  JJ, Hodinka  RL, Shah  SS.  Defining cerebrospinal fluid white blood cell count reference values in neonates and young infants.   Pediatrics. 2010;125(2):257-264. doi:10.1542/peds.2009-1181 PubMedGoogle ScholarCrossref
    80.
    Thomson  J, Sucharew  H, Cruz  AT,  et al; Pediatric Emergency Medicine Collaborative Research Committee (PEM CRC) HSV Study Group.  Cerebrospinal fluid reference values for young infants undergoing lumbar puncture.   Pediatrics. 2018;141(3):e20173405. doi:10.1542/peds.2017-3405 PubMedGoogle Scholar
    ×