Characterizing the spectrum of body mass index associated with severe postoperative pulmonary complications in children
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While high body mass index (BMI) is a recognized risk factor for pulmonary complications in adults, its importance as a risk factor for complications following pediatric surgery is poorly described. We evaluated the association between BMI and severe pediatric perioperative pulmonary complications (PPCs).
In this retrospective cohort study, we evaluated pediatric patients (aged 2–17 years) undergoing elective procedures in the 2015 Pediatric National Surgical Quality Improvement Program (NSQIP-P). Severe PPCs were defined as either pneumonia/reintubation within 3 days of surgery, or pneumonia/reintubation as an index complication within 7 days. Univariate and multivariable logistic regression analyses adjusting for patient factors and surgical case-mix tested associations between BMI class—using the Centers for Disease Control age- and sex-dependent BMI percentiles—and severe PPCs.
Among 40,949 patients, BMI class was distributed as follows: 2740 (6.7%) were underweight, 23,630 (57.7%) normal weight, 6161 (15.0%) overweight, and 8418 (20.6%) obese. Overweight BMI class was not associated with PPCs in univariate analyses, but became statistically significant after adjustment [OR 1.84 (95% CI 1.07–3.15), p = 0.03], and persisted across multiple adjustment approaches. Neither underweight [OR 1.01 (95% CI 0.53–1.94), p = 0.97] nor obesity [OR 1.10 (95% CI 0.63–1.94), p = 0.73] were associated with PPCs after adjustment.
Overweight pediatric patients have an elevated, previously underappreciated risk of severe PPCs. Contrary to prior studies, the present study found no greater risk in obese children, perhaps due to bias, confounding, or practice migration from “availability bias”. Findings from the present study, taken with prior work describing pulmonary risks of obesity, suggest that both obese and overweight children may be evaluated for tailored perioperative care to improve outcomes.
KeywordsPediatric surgery BMI Respiratory complications
The work was performed without extramural funding, support was provided solely from institutional and/or departmental sources.
Compliance with ethical standards
Conflict of interest
The authors report no potential financial, commercial or ethical conflicts of interest regarding the contents of this manuscript.
- 1.World Health Organization. Facts and figures on childhood obesity. https://www.who.int/end-childhood-obesity/facts/en/. Accessed 8 Sept 2018.
- 2.Childhood Obesity Facts, Overweight and Obesity, Centers for Disease Control and Prevention. https://www.cdc.gov/obesity/data/childhood.html. Accessed 8 Sept 2018.
- 8.Gross JB, Bachenberg KL, Benumof JL, Caplan RA, Connis RT, Coté CJ, Nickinovich DG, Prachand V, Ward DS, Weaver EM, Ydens L, Yu S, American Society of Anesthesiologists Task Force on Perioperative Management. Practice guidelines for the perioperative management of patients with obstructive sleep apnea: a report by the American Society of Anesthesiologists Task Force on Perioperative Management of patients with obstructive sleep apnea. Anesthesiology. 2006;104(5):1081–93 (quiz 1117–8).CrossRefGoogle Scholar
- 13.Scherrer PD, Mallory MD, Cravero JP, Lowrie L, Hertzog JH, Berkenbosch JW, Pediatric Sedation Research Consortium. The impact of obesity on pediatric procedural sedation-related outcomes: results from the Pediatric Sedation Research Consortium. Paediatr Anaesth. 2015;25(7):689–97.CrossRefGoogle Scholar
- 20.User Guide for the 2015 ACS NSQIP Pediatric Participant Use Data File (PUF). American College of Surgeons National Surgical Quality Improvement Program-Pediatric. https://www.facs.org/~/media/files/qualityprograms/nsqippeds/peds_acs_nsqip_puf_userguide_2015.ashx. Accessed 8 Sept 2018.
- 21.Bruny JL, Hall BL, Barnhart DC, Billmire DF, Dias MS, Dillon PW, Fisher C, Heiss KF, Hennrikus WL, Ko CY, Moss L, Oldham KT, Richards KE, Shah R, Vinocur CD, Ziegler MM. American College of Surgeons National Surgical Quality Improvement Program Pediatric: a beta phase report. J Pediatr Surg. 2013;48(1):74–80.CrossRefGoogle Scholar
- 23.Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z, Wei R, Curtin LR, Roche AF, Johnson CL. 2000 CDC growth charts for the United States: methods and development. Vital Health Stat. 2002;11(246):1–190.Google Scholar
- 24.Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, Flegal KM, Guo SS, Wei R, Mei Z, Curtin LR, Roche AF, Johnson CL. CDC growth charts: United States. Adv Data. 2000;314:1–27.Google Scholar
- 27.Shiloach M, Frencher SK, Steeger JE, Rowell KS, Bartzokis K, Tomeh MG, Richards KE, Ko CY, Hall BL. Toward robust information: data quality and inter-rater reliability in the American College of Surgeons National Surgical Quality Improvement Program. J Am Coll Surg. 2010;210(1):6–16.CrossRefGoogle Scholar
- 28.Daley J, Forbes MG, Young GJ, Charns MP, Gibbs JO, Hur K, Henderson W, Khuri SF. Validating risk-adjusted surgical outcomes: site visit assessment of process and structure. National VA Surgical Risk Study. J Am Coll Surg. 1997;185(4):341–51.Google Scholar
- 32.Cohen ME, Ko CY, Bilimoria KY, Zhou L, Huffman K, Wang X, Liu Y, Kraemer K, Meng X, Merkow R, Chow W, Matel B, Richards K, Hart AJ, Dimick JB, Hall BL. Optimizing ACS NSQIP modeling for evaluation of surgical quality and risk: patient risk adjustment, procedure mix adjustment, shrinkage adjustment, and surgical focus. J Am Coll Surg. 2013;217(2):336–346.e1.CrossRefGoogle Scholar