Risk Factors and Risk Stratification for Adverse Obstetrical Outcomes After Appendectomy or Cholecystectomy During Pregnancy | Gastrointestinal Surgery | JAMA Surgery | JAMA Network
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Figure 1.  Selection of the Study Sample
Selection of the Study Sample

NEOMAT indicates neonatal and/or maternal.

Figure 2.  Calibration Plots of the Scoring System by Risk Group
Calibration Plots of the Scoring System by Risk Group

The bold number indicates the number of adverse obstetrical outcomes and the italic number the number of women in each risk group. The predicted probability of adverse outcomes in each risk group is within the 95% CI of observed probability, indicating good calibration.

Table 1.  Adverse Obstetrical Outcomes Observed in Discharges Indicating Appendectomy or Cholecystectomy During Pregnancy
Adverse Obstetrical Outcomes Observed in Discharges Indicating Appendectomy or Cholecystectomy During Pregnancy
Table 2.  Multivariable Analysis of Risk Factors for Adverse Obstetrical Outcome in the Training Seta
Multivariable Analysis of Risk Factors for Adverse Obstetrical Outcome in the Training Seta
Table 3.  Points Used in the Score Based on Coefficients of the Logistic Regression Model Obtained in the Training Set
Points Used in the Score Based on Coefficients of the Logistic Regression Model Obtained in the Training Set
1.
Moore  HB, Juarez-Colunga  E, Bronsert  M,  et al.  Effect of pregnancy on adverse outcomes after general surgery.  JAMA Surg. 2015;150(7):637-643.PubMedGoogle ScholarCrossref
2.
Abbasi  N, Patenaude  V, Abenhaim  HA.  Management and outcomes of acute appendicitis in pregnancy-population-based study of over 7000 cases.  BJOG. 2014;121(12):1509-1514.PubMedGoogle ScholarCrossref
3.
Kuy  S, Roman  SA, Desai  R, Sosa  JA.  Outcomes following cholecystectomy in pregnant and nonpregnant women.  Surgery. 2009;146(2):358-366.PubMedGoogle ScholarCrossref
4.
Martin  JA, Hamilton  BE, Osterman  MJ, Curtin  SC, Matthews  TJ.  Births: final data for 2013.  Natl Vital Stat Rep. 2015;64(1):1-65.PubMedGoogle Scholar
5.
Cohen-Kerem  R, Railton  C, Oren  D, Lishner  M, Koren  G.  Pregnancy outcome following non-obstetric surgical intervention.  Am J Surg. 2005;190(3):467-473.PubMedGoogle ScholarCrossref
6.
Allaert  SE, Carlier  SP, Weyne  LP, Vertommen  DJ, Dutré  PE, Desmet  MB.  First trimester anesthesia exposure and fetal outcome: a review.  Acta Anaesthesiol Belg. 2007;58(2):119-123.PubMedGoogle Scholar
7.
Mazze  RI, Källén  B.  Appendectomy during pregnancy: a Swedish registry study of 778 cases.  Obstet Gynecol. 1991;77(6):835-840.PubMedGoogle Scholar
8.
Källén  B, Mazze  RI.  Neural tube defects and first trimester operations.  Teratology. 1990;41(6):717-720.PubMedGoogle ScholarCrossref
9.
Mazze  RI, Källén  B.  Reproductive outcome after anesthesia and operation during pregnancy: a registry study of 5405 cases.  Am J Obstet Gynecol. 1989;161(5):1178-1185.PubMedGoogle ScholarCrossref
10.
Erekson  EA, Brousseau  EC, Dick-Biascoechea  MA, Ciarleglio  MM, Lockwood  CJ, Pettker  CM.  Maternal postoperative complications after nonobstetric antenatal surgery.  J Matern Fetal Neonatal Med. 2012;25(12):2639-2644.PubMedGoogle ScholarCrossref
11.
Conron  RW  Jr, Abbruzzi  K, Cochrane  SO, Sarno  AJ, Cochrane  PJ.  Laparoscopic procedures in pregnancy.  Am Surg. 1999;65(3):259-263.PubMedGoogle Scholar
12.
Akira  S, Yamanaka  A, Ishihara  T, Takeshita  T, Araki  T.  Gasless laparoscopic ovarian cystectomy during pregnancy: comparison with laparotomy.  Am J Obstet Gynecol. 1999;180(3, pt 1):554-557.PubMedGoogle ScholarCrossref
13.
Andreoli  M, Sayegh  SK, Hoefer  R, Matthews  G, Mann  WJ.  Laparoscopic cholecystectomy for recurrent gallstone pancreatitis during pregnancy.  South Med J. 1996;89(11):1114-1115.PubMedGoogle ScholarCrossref
14.
Affleck  DG, Handrahan  DL, Egger  MJ, Price  RR.  The laparoscopic management of appendicitis and cholelithiasis during pregnancy.  Am J Surg. 1999;178(6):523-529.PubMedGoogle ScholarCrossref
15.
Lyass  S, Pikarsky  A, Eisenberg  VH, Elchalal  U, Schenker  JG, Reissman  P.  Is laparoscopic appendectomy safe in pregnant women?  Surg Endosc. 2001;15(4):377-379.PubMedGoogle ScholarCrossref
16.
Rojansky  N, Shushan  A, Fatum  M.  Laparoscopy versus laparotomy in pregnancy: a comparative study.  J Am Assoc Gynecol Laparosc. 2002;9(1):108-110.PubMedGoogle Scholar
17.
Black  M, Bhattacharya  S, Fairley  T, Campbell  DM, Shetty  A.  Outcomes of pregnancy in women using illegal drugs and in women who smoke cigarettes.  Acta Obstet Gynecol Scand. 2013;92(1):47-52.PubMedGoogle ScholarCrossref
18.
Saurel-Cubizolles  MJ, Prunet  C, Blondel  B.  Cannabis use during pregnancy in France in 2010.  BJOG. 2014;121(8):971-977.PubMedGoogle ScholarCrossref
19.
Aldous  MB, Edmonson  MB.  Maternal age at first childbirth and risk of low birth weight and preterm delivery in Washington state.  JAMA. 1993;270(21):2574-2577.PubMedGoogle ScholarCrossref
20.
Goldenberg  RL, Culhane  JF, Iams  JD, Romero  R.  Epidemiology and causes of preterm birth.  Lancet. 2008;371(9606):75-84.PubMedGoogle ScholarCrossref
21.
Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality. Nationwide Inpatient Sample redesign report. https://www.hcup-us.ahrq.gov/db/nation/nis/reports/NISRedesignFinalReport040914.pdf. Published June 4, 2014. Accessed December 11, 2016.
22.
Peabody  JW, Luck  J, Jain  S, Bertenthal  D, Glassman  P.  Assessing the accuracy of administrative data in health information systems.  Med Care. 2004;42(11):1066-1072.PubMedGoogle ScholarCrossref
23.
Roos  LL, Mustard  CA, Nicol  JP,  et al.  Registries and administrative data: organization and accuracy.  Med Care. 1993;31(3):201-212.PubMedGoogle ScholarCrossref
24.
Quan  H, Parsons  GA, Ghali  WA.  Validity of procedure codes in International Classification of Diseases, 9th revision, Clinical Modification administrative data.  Med Care. 2004;42(8):801-809.PubMedGoogle ScholarCrossref
25.
Bateman  BT, Mhyre  JM, Hernandez-Diaz  S,  et al.  Development of a comorbidity index for use in obstetric patients.  Obstet Gynecol. 2013;122(5):957-965.PubMedGoogle ScholarCrossref
Original Investigation
May 2017

Risk Factors and Risk Stratification for Adverse Obstetrical Outcomes After Appendectomy or Cholecystectomy During Pregnancy

Author Affiliations
  • 1Department of Anesthesiology, Hartford Hospital, Hartford, Connecticut
  • 2Department of Anesthesiology, University of Connecticut School of Medicine, Farmington
  • 3Department of Anesthesiology, Columbia University College of Physicians and Surgeons, New York, New York
  • 4Institut National de la Santé et de la Recherche Médicale, Unité Mixte de Recherche 1137, Infection, Antimicrobiens, Modélisation, Evolution, Paris, France
  • 5Department of Obstetrics and Gynecology, Columbia University College of Physicians and Surgeons, New York, New York
  • 6Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
JAMA Surg. 2017;152(5):436-441. doi:10.1001/jamasurg.2016.5045
Key Points

Question  What are the risk factors for adverse obstetrical outcomes after appendectomy and cholecystectomy during pregnancy?

Findings  In this cohort study of 19 926 women undergoing these procedures in the United States, the risk factors most associated with an adverse obstetrical outcome were cervical incompetence, preterm labor during the current pregnancy, vaginitis or vulvovaginitis, and sepsis.

Meaning  Obstetrical risk factors, instead of risk factors associated with maternal characteristics, disease severity, or surgical technique, are most associated with negative pregnancy outcomes after appendectomy and cholecystectomy.

Abstract

Importance  Identification of risk factors for adverse obstetrical outcomes after appendectomy and cholecystectomy during pregnancy is necessary for evidence-based risk reduction and adequate patient counseling.

Objectives  To identify risk factors for adverse obstetrical outcomes after appendectomy and cholecystectomy during pregnancy and stratify the risk of such outcomes.

Design, Setting, and Participants  A cohort study was conducted using the Nationwide Inpatient Sample, a nationally representative sample of patients discharged from community hospitals in the United States, from January 1, 2003, to December 31, 2012. Multivariable analysis of risk factors for adverse obstetric outcomes was performed for 19 926 women undergoing appendectomy or cholecystectomy during pregnancy and a scoring system for such risk factors was developed. Data analysis was conducted from January 1, 2015, to July 31, 2016.

Main Outcomes and Measures  A composite measure including 7 adverse obstetrical outcomes throughout pregnancy and occurring before hospital discharge.

Results  Of the 19 926 women (mean [SD] age, 26 [6] years) in the study, 1018 adverse obstetrical events were recorded in 953 pregnant women (4.8%). The 3 most frequent adverse events were preterm delivery (360 [35.4%]), preterm labor without preterm delivery (269 [26.4%]), and miscarriage (262 [25.7%]). The risk factors associated most strongly with an adverse obstetrical outcome included cervical incompetence (adjusted odds ratio, 24.29; 95% CI, 7.48-78.81), preterm labor during current pregnancy (adjusted odds ratio, 18.34; 95% CI, 4.95-67.96), vaginitis or vulvovaginitis (adjusted odds ratio, 5.17; 95% CI, 2.19-12.23), and sepsis (adjusted odds ratio, 3.39; 95% CI, 2.08-5.51). A scoring system based on statistically significant variables classified the study sample into 3 risk groups corresponding to predicted probabilities of adverse obstetrical outcomes of 2.5% (≤4 points), 8.2% (5-8 points), and 21.8% (≥9 points).

Conclusions and Relevance  Approximately 5% of women experience adverse obstetrical outcomes after appendectomy or cholecystectomy during pregnancy. The major risk factors for such outcomes are cervical incompetence, preterm labor during current pregnancy, vaginitis or vulvovaginitis, and sepsis.

Introduction

Nonobstetric surgery during pregnancy occurs in 2 per 1000 pregnant women,1 with the 2 most frequent procedures performed being appendectomy (0.7 per 1000 pregnancies)2 and cholecystectomy (0.5 per 1000 pregnancies).3 With approximately 4 million births per year in the United States, an estimated 2800 appendectomies and 2000 cholecystectomies are performed annually on pregnant women nationwide.4

Nonobstetric surgery during pregnancy is associated with risk to the fetus, including loss of pregnancy before viability, preterm labor, preterm delivery, and fetal death.5,6 Despite these concerns, studies on nonobstetric surgery during pregnancy focus largely on diagnosis and surgical management of appendicitis and cholecystitis rather than fetal or obstetrical outcomes.5 Previous research regarding obstetrical outcomes following nonobstetrical surgical procedures largely involve pregnancies from the 1970s, and these results may not be generalizable considering current obstetric and anesthesia practice.7-9 Owing to a lack of robust and recent data, risk stratification, preventative measure implementation, and accurate maternal counseling regarding anticipated outcomes following nonobstetric surgery during pregnancy remain challenging in clinical practice.

The objectives of this cohort study were to identify maternal risk factors including pregnancy-, surgery-, and disease-associated risk factors, for adverse obstetrical outcomes after appendectomy and cholecystectomy during pregnancy, and to stratify the risk of these adverse outcomes based on individual risk factors.

Methods

The study protocol was reviewed by the Columbia University Medical Center Institutional Review Board. It was granted exemption under title 45 Code of Federal Regulation part 46. No informed patient consent was obtained because the administrative data were deidentified.

Deidentified data were obtained from the Nationwide Inpatient Sample (NIS), which is part of the Healthcare Cost and Utilization Project sponsored by the Agency for Healthcare Research and Quality. The NIS is a stratified sample of 20% of all annual US community hospital discharge records. To create a representative national sample, hospitals are selected for inclusion in the NIS based on the following 5 characteristics: number of beds, teaching status, location (urban or rural), region, and ownership. For each discharge, the NIS includes patients’ characteristics and up to 15 procedural codes and up to 25 diagnostic codes defined in the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM). Detailed information on NIS data, methods, and variables is publicly available (http://www.hcup-us.ahrq.gov/nisoverview.jsp).

The study sample consisted of all women who underwent appendectomy, cholecystectomy, or combined procedures during pregnancy between January 1, 2003, and December 31, 2012. Discharges with neonatal and/or maternal diagnoses and procedures identified with a NEOMAT (neonatal and/or maternal) code of 1, 2, or 3 and female sex were first selected. The NEOMAT variable is provided by the NIS and is reported as a categorical variable as follows: 0 indicates no neonatal or maternal diagnosis or procedure on record, 1 indicates maternal diagnosis or procedure on record, 2 indicates neonatal diagnosis on record, and 3 indicates neonatal diagnosis and maternal diagnoses or procedures on the same record. Discharges indicating appendectomy or cholecystectomy were identified with ICD-9-CM procedure codes (eTable 1 in the Supplement) and divided into laparoscopic and open techniques. Procedures that used both laparoscopic and open techniques were defined as open. Patients were excluded if the pregnancy was ectopic, molar, or a voluntary termination (eTable 2 in the Supplement); the NEOMAT code was 2 or 3, which may indicate that the surgery was performed on the newborn; and the admission type was elective or missing.

The primary outcome was a composite measure consisting of 7 selected adverse obstetrical outcomes occurring before hospital discharge (eTable 3 in the Supplement). Components of the primary outcome were selected with the intent to include all possible complications throughout pregnancy that might plausibly be associated with the nonobstetrical surgical procedure or the underlying condition that prompted the surgery. The composite outcome included the following ICD-9-CM non–mutually exclusive diagnoses: miscarriage (fetal death prior to 22 weeks), placental abruption, premature rupture of membranes, preterm labor not associated with preterm delivery, preterm delivery (delivery prior to 37 weeks), infection of the amniotic cavity, and intrauterine fetal death. Because NIS data do not allow tracking of patients over time, adverse obstetrical outcomes occurring during a readmission could not be analyzed in this study.

Characteristics were recorded directly from the NIS data or identified with ICD-9-CM codes (eTable 4 in the Supplement). The following maternal characteristics were recorded: age, race/ethnicity, obesity, insurance status (categorized as Medicaid or non-Medicaid), annual household income, tobacco use, alcohol abuse, and illicit drug abuse. Obstetrical characteristics included multiple gestations, cervical incompetence, preterm labor during a previous pregnancy, preterm labor during the current pregnancy, vaginitis or vulvovaginitis, and urinary tract infection. The following surgical characteristics and disease-associated variables were recorded: type of surgery (appendectomy, cholecystectomy, or combined), technique used (laparoscopic or open), presence of peritonitis, and presence of sepsis.

Statistical analyses were performed from January 1, 2015, to July 31, 2016, with R, version 3.0.2 (R Foundation for Statistical Computing). Results are expressed as number and percentage or median and interquartile range. The sample study was randomly split into 1 training set (60% of the discharges) and 1 validation set (40% of the discharges). The training set was used to identify risk factors for the composite outcome and develop the prediction model for adverse obstetrical outcomes. The validation set was used to assess the performance of the prediction model (internal validation). Comparisons of discharges with and without the outcome used the unpaired Wilcoxon rank-sum test for continuous variables and the Fisher exact test for discrete variables. Unadjusted odds ratios (ORs) were obtained using univariable logistic regression. All variables in the univariable analysis with P < .20 and the year of surgery were entered in a logistic regression with backward selection. Missing values were estimated with multivariable imputation technique. Discrimination of the model was assessed with the concordance index (c-index) and calibration with a calibration plot. The model developed in the training set was applied to the validation set without re-estimating the coefficients, and discrimination was assessed with the c-index and calibration with a calibration plot.

A scoring system of the occurrence of the composite outcome was developed from the prediction model obtained in the training set. The score was the sum of the points corresponding to each variable. The number of points for each variable identified in the model was attributed after identification of a common denominator across regression coefficients. Based on the score, 3 risk groups were created, with a low, intermediate, or high risk of the outcome corresponding to a risk of adverse outcome less than 5%, between 5% and 10%, and greater than 10%, respectively. Discrimination of the 3 risk groups was assessed with the c-index and calibration with a calibration plot.

Results

The selection of the study sample is presented in Figure 1. From January 1, 2003, to December 31, 2012, a total of 19 926 pregnant women underwent appendectomy or cholecystectomy and were included in the analysis.

A total of 1018 adverse events were recorded in 953 discharges (4.8%; 95% CI, 4.5%-5.1%) (Table 1). The 3 most frequent adverse events, accounting for 891 of the total (87.5%), were preterm delivery (360 [35.4%]), preterm labor without preterm delivery (269 [26.4%]), and miscarriage (262 [25.7%]). Women with an adverse obstetrical outcome had a longer hospital stay (5 [interquartile range, 3-8] vs 3 [interquartile range, 2-4] days; P < .001) and a higher in-hospital mortality rate (0.31% vs 0.02%; P = .003).

Univariable analyses of risk factors for adverse obstetrical outcomes in the training set are presented in eTable 5 in the Supplement. In the final prediction model (Table 2), the following 10 factors were associated with an increased risk of adverse obstetrical outcomes: nonwhite race/ethnicity (adjusted OR [AOR], 1.55; 95% CI, 1.29-1.85), Medicaid coverage (AOR, 1.22; 95% CI, 1.02-1.46), drug abuse or dependence (AOR, 2.05; 95% CI, 1.05-4.00), vaginitis or vulvovaginitis (AOR, 5.17; 95% CI, 2.19-12.23), preterm labor during current pregnancy (AOR, 18.34; 95% CI, 4.95-67.96), cervical incompetence (AOR, 24.29; 95% CI, 7.48-78.81), multiple gestations (AOR, 3.31; 95% CI, 1.67-6.58), open surgery (AOR, 3.13; 95% CI, 2.59-3.78), peritonitis (AOR, 2.80; 95% CI, 2.22-3.53), and sepsis (AOR, 3.39; 95% CI, 2.08-5.51). In the training set, the c-index was 0.73 (95% CI, 0.71-0.75); in the validation set, it was 0.70 (95% CI, 0.67-0.73). Calibration was good in the training and validation sets, as illustrated by the calibration curves (eFigure 1 in the Supplement).

Scoring based on individual risk factors in the training set is presented in Table 3; 16 points were attributed to cervical incompetence, 15 to preterm labor during current pregnancy, 8 to vaginitis or vulvovaginitis, 6 to multiple gestations, 6 to sepsis, 5 to open surgery, 5 to peritonitis, 3 to drug abuse or dependence, 2 to nonwhite race/ethnicity, and 1 to Medicaid coverage. The median score in the training set was 2 (range, 0-24) and the median score in the validation set was 2 (range, 0-30) (eFigure 2 in the Supplement).

Based on the sum of points, women in the training set were categorized into 1 of 3 groups: a low-risk group (score, ≤4 points; 8883 of 11 955 [74.3%]), an intermediate-risk group (score, 5-8 points; 2449 [20.5%]), and a high-risk group (score, ≥9 points; 623 [5.2%]). Predicted probabilities of adverse obstetrical outcomes in the low-, intermediate-, and high-risk groups were 2.5%, 8.2%, and 21.8%, respectively. The c-index of the score divided into 3 risk groups was 0.70 (95% CI, 0.67-0.72); its calibration plot is shown in Figure 2. In the validation set, there were 5889 of 7971 women in the low-risk group (73.9%), 1679 in the intermediate-risk group (21.1%), and 403 in the high-risk group (5.1%). The c-index of the score divided into 3 risk groups was 0.68 (95% CI, 0.65-0.70), and the good calibration of the score was attested by the fact that predicted probability in each group was within the 95% CI of observed probability of adverse obstetrical outcomes (Figure 2).

Discussion

This study evaluated a representative national sample of 19 926 pregnant women undergoing appendectomy or cholecystectomy during pregnancy between 2003 and 2012. Ten risk factors for adverse obstetrical outcomes were identified, including maternal characteristics (nonwhite race/ethnicity, drug abuse or dependence, and Medicaid coverage), obstetrical factors (preterm labor during the current pregnancy, incompetent cervix, vaginitis or vulvovaginitis, and multiple gestation), surgical technique (open surgery), and disease severity (sepsis and peritonitis).

Using these findings, we developed a risk stratification scoring system, validated in a subset of the cohort, which can be used perioperatively to inform both health care practitioners and pregnant women about each woman’s risk for adverse obstetric outcomes after surgery. For each woman, the score is calculated by summing the points for each risk factor (Table 3) and then categorized into low (≤4 points), intermediate (5-8 points), or high risk (≥9 points) of adverse obstetrical outcomes, corresponding to a risk of 2.5%, 8.2%, and 21.8%, respectively.

Of the 10 risk factors identified, 4 were previously reported as increasing the risk for obstetric complications after appendectomy or cholecystectomy during pregnancy: open procedures conferred significantly more risk than laparoscopic procedures,10-16 the presence of systemic infection (sepsis or peritonitis) was associated with increased morbidity compared with local infection,2,5,10 and Medicaid beneficiaries have been shown to have an increased risk of adverse outcomes.3

To our knowledge, this is the first study to investigate and conclude that obstetrical conditions (cervical incompetence [AOR, 24.29; 95% CI, 7.48-78.81], preterm labor during current pregnancy [AOR, 18.34; 95% CI, 4.95-67.96], and vaginitis or vulvovaginitis [AOR, 5.17; 95% CI, 2.19-12.23]), rather than maternal-, surgery-, or disease-associated variables, have the strongest association with adverse obstetric outcomes after appendectomy or cholecystectomy.

In reference to the remaining risk factors not previously discussed, it is not surprising that drug abuse or dependence and nonwhite race/ethnicity were associated with an increased incidence of adverse outcomes, because these factors are also associated with poor obstetrical outcomes in pregnant women not undergoing surgery.17-20

Although it has been previously reported that appendectomy during pregnancy confers an increased risk of adverse obstetrical events when compared with cholecystectomy,10 this outcome was not evident in our study. We found that when disease severity (sepsis or peritonitis) and surgical approach (laparoscopic) for nonelective procedures are controlled for, then the actual procedure (appendectomy vs cholecystectomy) is not an independent risk factor for adverse outcomes.

Although most of the identified risk factors are nonmodifiable, several factors, such as surgical approach, the presence of vaginitis or vulvovaginitis, and cervical insufficiency, may possibly be modified. Based on these findings, we suggest that a laparoscopic approach to appendectomy or cholecystectomy during pregnancy be offered whenever feasible. Although treatment of vaginal infections around the time of surgery may additionally be considered, research is required to demonstrate if this intervention reduces the risk for adverse obstetrical outcomes. No specific recommendations can be provided based on these data regarding cervical cerclage placement or progesterone therapy in pregnant women with cervical insufficiency around the time of appendectomy or cholecystectomy.

Strengths and Limitations

To our knowledge, this is the largest population-based cohort of women undergoing appendectomies and cholecystectomies during pregnancy. Such data sets can be particularly useful in the identification and evaluation of relatively rare adverse events. Although the limitations of administrative databases, especially the accuracy of secondary diagnoses (which are used in this study), are reported, the NIS has a revised system, which is thought to improve random sampling, coding accuracy, and precision when compared with similar administrative databases.21-23 In addition, the use of ICD-9-CM codes was shown to accurately reflect various surgical procedures performed, including appendectomy and cholecystectomy.24

There are several additional limitations associated with this study. First, anesthetic modalities are not available in the NIS data; therefore, the effect on obstetric outcomes of general vs neuraxial anesthesia and other anesthesia-associated factors cannot be evaluated. Second, our model broadly incorporates the timing of surgery during pregnancy through use of ICD-9-CM codes, because the NIS does not specifically record gestational age. Including a specific parameter for gestational age in our scoring system would result in a more maternal-specific model. Third, outcomes were assessed at the time of hospitalization for surgery, which may have underestimated the overall number of adverse events, since additional complications and adverse outcomes may have occurred after discharge. Fourth, we evaluated the risks associated with appendectomies and cholecystectomies because these are the 2 most common nonobstetric surgical procedures performed during pregnancy; however, since we did not evaluate obstetric outcomes after other surgical procedures, our findings and scoring system may not be generalizable to other procedures, such as cardiac, neurosurgical, or orthopedic procedures. Fifth, while the ORs measure the strength of associations between the risk factors and adverse obstetrical outcomes, prospective randomized clinical trials are necessary to prove causation. Sixth, patients with the admission status “elective admission” were deliberately excluded to create a more homogeneous study sample, which should have enhanced the internal accuracy of the study findings at the expense of reduced generalizability. Finally, the c-index of 0.70 for the prediction model and the risk stratification system indicates moderate discrimination. However, in the absence of other available risk assessment for adverse obstetrical outcomes, even a moderately performing system can be clinically useful. In addition, this 0.70 value is in the high range of other prediction models based on administrative data. For instance, the c-index of the comorbidity index recently developed by Bateman et al25 for use in obstetric patients was 0.67.

Conclusions

Undergoing appendectomy or cholecystectomy during pregnancy confers a significant obstetric risk. Based on newly identified risk factors for adverse obstetric outcomes after nonobstetrical surgery during pregnancy, a scoring method has been developed and validated to assist in risk stratification and potentially counseling of pregnant women undergoing these procedures. Future research should focus on validation of the causation of these risk factors and identifying interventions to decrease obstetrical risk in women at a high risk of negative outcomes after nonobstetric surgery during pregnancy.

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Article Information

Accepted for Publication: October 16, 2016.

Corresponding Author: Adam Sachs, MD, Department of Anesthesiology, Hartford Hospital, Hartford, CT 06102 (asachs29@gmail.com).

Published Online: January 18, 2017. doi:10.1001/jamasurg.2016.5045

Author Contributions: Dr Sachs 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.

Study concept and design: Sachs, Guglielminotti, Miller, Smiley, Li.

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

Drafting of the manuscript: Sachs, Guglielminotti, Miller, Landau.

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

Statistical analysis: Sachs, Guglielminotti, Li.

Administrative, technical, or material support: Sachs, Smiley, Li.

Study supervision: Miller, Smiley, Li.

Conflict of Interest Disclosures: None reported.

References
1.
Moore  HB, Juarez-Colunga  E, Bronsert  M,  et al.  Effect of pregnancy on adverse outcomes after general surgery.  JAMA Surg. 2015;150(7):637-643.PubMedGoogle ScholarCrossref
2.
Abbasi  N, Patenaude  V, Abenhaim  HA.  Management and outcomes of acute appendicitis in pregnancy-population-based study of over 7000 cases.  BJOG. 2014;121(12):1509-1514.PubMedGoogle ScholarCrossref
3.
Kuy  S, Roman  SA, Desai  R, Sosa  JA.  Outcomes following cholecystectomy in pregnant and nonpregnant women.  Surgery. 2009;146(2):358-366.PubMedGoogle ScholarCrossref
4.
Martin  JA, Hamilton  BE, Osterman  MJ, Curtin  SC, Matthews  TJ.  Births: final data for 2013.  Natl Vital Stat Rep. 2015;64(1):1-65.PubMedGoogle Scholar
5.
Cohen-Kerem  R, Railton  C, Oren  D, Lishner  M, Koren  G.  Pregnancy outcome following non-obstetric surgical intervention.  Am J Surg. 2005;190(3):467-473.PubMedGoogle ScholarCrossref
6.
Allaert  SE, Carlier  SP, Weyne  LP, Vertommen  DJ, Dutré  PE, Desmet  MB.  First trimester anesthesia exposure and fetal outcome: a review.  Acta Anaesthesiol Belg. 2007;58(2):119-123.PubMedGoogle Scholar
7.
Mazze  RI, Källén  B.  Appendectomy during pregnancy: a Swedish registry study of 778 cases.  Obstet Gynecol. 1991;77(6):835-840.PubMedGoogle Scholar
8.
Källén  B, Mazze  RI.  Neural tube defects and first trimester operations.  Teratology. 1990;41(6):717-720.PubMedGoogle ScholarCrossref
9.
Mazze  RI, Källén  B.  Reproductive outcome after anesthesia and operation during pregnancy: a registry study of 5405 cases.  Am J Obstet Gynecol. 1989;161(5):1178-1185.PubMedGoogle ScholarCrossref
10.
Erekson  EA, Brousseau  EC, Dick-Biascoechea  MA, Ciarleglio  MM, Lockwood  CJ, Pettker  CM.  Maternal postoperative complications after nonobstetric antenatal surgery.  J Matern Fetal Neonatal Med. 2012;25(12):2639-2644.PubMedGoogle ScholarCrossref
11.
Conron  RW  Jr, Abbruzzi  K, Cochrane  SO, Sarno  AJ, Cochrane  PJ.  Laparoscopic procedures in pregnancy.  Am Surg. 1999;65(3):259-263.PubMedGoogle Scholar
12.
Akira  S, Yamanaka  A, Ishihara  T, Takeshita  T, Araki  T.  Gasless laparoscopic ovarian cystectomy during pregnancy: comparison with laparotomy.  Am J Obstet Gynecol. 1999;180(3, pt 1):554-557.PubMedGoogle ScholarCrossref
13.
Andreoli  M, Sayegh  SK, Hoefer  R, Matthews  G, Mann  WJ.  Laparoscopic cholecystectomy for recurrent gallstone pancreatitis during pregnancy.  South Med J. 1996;89(11):1114-1115.PubMedGoogle ScholarCrossref
14.
Affleck  DG, Handrahan  DL, Egger  MJ, Price  RR.  The laparoscopic management of appendicitis and cholelithiasis during pregnancy.  Am J Surg. 1999;178(6):523-529.PubMedGoogle ScholarCrossref
15.
Lyass  S, Pikarsky  A, Eisenberg  VH, Elchalal  U, Schenker  JG, Reissman  P.  Is laparoscopic appendectomy safe in pregnant women?  Surg Endosc. 2001;15(4):377-379.PubMedGoogle ScholarCrossref
16.
Rojansky  N, Shushan  A, Fatum  M.  Laparoscopy versus laparotomy in pregnancy: a comparative study.  J Am Assoc Gynecol Laparosc. 2002;9(1):108-110.PubMedGoogle Scholar
17.
Black  M, Bhattacharya  S, Fairley  T, Campbell  DM, Shetty  A.  Outcomes of pregnancy in women using illegal drugs and in women who smoke cigarettes.  Acta Obstet Gynecol Scand. 2013;92(1):47-52.PubMedGoogle ScholarCrossref
18.
Saurel-Cubizolles  MJ, Prunet  C, Blondel  B.  Cannabis use during pregnancy in France in 2010.  BJOG. 2014;121(8):971-977.PubMedGoogle ScholarCrossref
19.
Aldous  MB, Edmonson  MB.  Maternal age at first childbirth and risk of low birth weight and preterm delivery in Washington state.  JAMA. 1993;270(21):2574-2577.PubMedGoogle ScholarCrossref
20.
Goldenberg  RL, Culhane  JF, Iams  JD, Romero  R.  Epidemiology and causes of preterm birth.  Lancet. 2008;371(9606):75-84.PubMedGoogle ScholarCrossref
21.
Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality. Nationwide Inpatient Sample redesign report. https://www.hcup-us.ahrq.gov/db/nation/nis/reports/NISRedesignFinalReport040914.pdf. Published June 4, 2014. Accessed December 11, 2016.
22.
Peabody  JW, Luck  J, Jain  S, Bertenthal  D, Glassman  P.  Assessing the accuracy of administrative data in health information systems.  Med Care. 2004;42(11):1066-1072.PubMedGoogle ScholarCrossref
23.
Roos  LL, Mustard  CA, Nicol  JP,  et al.  Registries and administrative data: organization and accuracy.  Med Care. 1993;31(3):201-212.PubMedGoogle ScholarCrossref
24.
Quan  H, Parsons  GA, Ghali  WA.  Validity of procedure codes in International Classification of Diseases, 9th revision, Clinical Modification administrative data.  Med Care. 2004;42(8):801-809.PubMedGoogle ScholarCrossref
25.
Bateman  BT, Mhyre  JM, Hernandez-Diaz  S,  et al.  Development of a comorbidity index for use in obstetric patients.  Obstet Gynecol. 2013;122(5):957-965.PubMedGoogle ScholarCrossref
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