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Int J Surg. 2017 Apr;40:169-175. doi: 10.1016/j.ijsu.2017.03.016. Epub 2017 Mar 8.

Conversion-to-open in laparoscopic appendectomy: A cohort analysis of risk factors and outcomes.

Author information

1
Department of Surgery, New York Presbyterian Hospital - Weill Cornell Medicine, 525 E. 68th Street, New York, NY 10065, United States. Electronic address: bmf9002@nyp.org.
2
Department of Healthcare Policy and Research, Division of Biostatistics and Epidemiology, Weill Cornell Medicine, 402 East 67th Street, New York, NY 10065, United States. Electronic address: xiw2011@med.cornell.edu.
3
Department of Anesthesia, New York Presbyterian Hospital - Weill Cornell Medicine, 525 E. 68th Street, New York, NY 10065, United States. Electronic address: grg2010@med.cornell.edu.
4
Department of Anesthesia, New York Presbyterian Hospital - Weill Cornell Medicine, 525 E. 68th Street, New York, NY 10065, United States. Electronic address: lig3001@med.cornell.edu.
5
Department of Computer Science, Cornell University, 402 Gates Hall, Ithaca, NY 14853, United States. Electronic address: rdz@cs.cornell.edu.
6
Department of Computer Science, Cornell University, 402 Gates Hall, Ithaca, NY 14853, United States. Electronic address: akshayubhat@gmail.com.
7
Department of Surgery, New York Presbyterian Hospital - Weill Cornell Medicine, 525 E. 68th Street, New York, NY 10065, United States. Electronic address: raz2002@med.cornell.edu.
8
Department of Surgery, New York Presbyterian Hospital - Weill Cornell Medicine, 525 E. 68th Street, New York, NY 10065, United States. Electronic address: alp2014@med.cornell.edu.
9
Department of Anesthesia, New York Presbyterian Hospital - Weill Cornell Medicine, 525 E. 68th Street, New York, NY 10065, United States. Electronic address: pmf9003@med.cornell.edu.
10
Department of Surgery, New York Presbyterian Hospital - Weill Cornell Medicine, 525 E. 68th Street, New York, NY 10065, United States. Electronic address: cha9043@med.cornell.edu.

Abstract

BACKGROUND:

Identifying risk factors for conversion from laparoscopic to open appendectomy could select patients who may benefit from primary open appendectomy. We aimed to develop a predictive scoring model for conversion from laparoscopic to open based on pre-operative patient characteristics.

METHODS:

A retrospective review of the State Inpatient Database (2007-2011) was performed using derivation (N = 71,617) and validation (N = 143,235) cohorts of adults ≥ 18 years with acute appendicitis treated by laparoscopic-only (LA), conversion from laparoscopic to open (CA), or primary open (OA) appendectomy. Pre-operative variables independently associated with CA were identified and reported as odds ratios (OR) with 95% confidence intervals (CI). A weighted integer-based scoring model to predict CA was designed based on pre-operative variable ORs, and complications between operative subgroups were compared.

RESULTS:

Independent predictors of CA in the derivation cohort were age ≥40 (OR 1.67; CI 1.55-1.80), male sex (OR 1.25; CI 1.17-1.34), black race (OR 1.46; CI 1.28-1.66), diabetes (OR 1.47; CI 1.31-1.65), obesity (OR 1.56; CI 1.40-1.74), and acute appendicitis with abscess or peritonitis (OR 7.00; CI 6.51-7.53). In the validation cohort, the CA predictive scoring model had an optimal cutoff score of 4 (range 0-9). The risk of conversion-to-open was ≤5% for a score <4, compared to 10-25% for a score ≥4. On composite outcomes analysis controlling for all pre-operative variables, CA had a higher likelihood of infectious/inflammatory (OR 1.44; CI 1.31-1.58), hematologic (OR 1.31; CI 1.17-1.46), and renal (OR 1.22; CI 1.06-1.39) complications compared to OA. Additionally, CA had a higher likelihood of infectious/inflammatory, respiratory, cardiovascular, hematologic, and renal complications compared to LA.

CONCLUSIONS:

CA patients have an unfavorable complication profile compared to OA. The predictors identified in this scoring model could help select for patients who may benefit from primary open appendectomy.

KEYWORDS:

Appendectomy; Conversion to open; Laparoscopic; State inpatient database

PMID:
28285058
DOI:
10.1016/j.ijsu.2017.03.016
[Indexed for MEDLINE]
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