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. 2022 Mar 28;8(3):e09188.
doi: 10.1016/j.heliyon.2022.e09188. eCollection 2022 Mar.

The impact of body mass index on the prognostic performance of the Simplified Acute Physiology Score 3: A prospective cohort study

Isabella B B Ferreira  1   2   3   4 , Rodrigo C Menezes  2   5   6   4 , Matheus L Otero  7 , Thomas A Carmo  2   7   3 , Gabriel A Agareno  7 , Gabriel P Telles  3 , Bruno V B Fahel  3 , María B Arriaga  2   5   6 , Kiyoshi F Fukutani  2   5 , Licurgo Pamplona Neto  8 , Sydney Agareno  8 , Kevan M Akrami  5   6   9 , Nivaldo M Filgueiras Filho  1   3   4 , Bruno B Andrade  2   7   3   5   6
Affiliations

The impact of body mass index on the prognostic performance of the Simplified Acute Physiology Score 3: A prospective cohort study

Isabella B B Ferreira et al. Heliyon. .

Abstract

Objective: To assess the Simplified Acute Physiology Score 3 (SAPS3) prognostic score performance across different body mass index categories.

Methods: A retrospective cohort study in a general ICU in Brazil. A secondary analysis of medical records was performed with clinical and epidemiological data. Patients were stratified according to their body mass index (BMI) category, and a binary logistic regression was then performed to identify factors independently associated with mortality. SAPS3 accuracy was determined using the area under the receiver operating characteristics curve and the Hosmer-Lemeshow test. A modified Kaplan-Meyer plot was employed to evaluate death probability according to BMI. ICU mortality was evaluated as the primary outcome.

Results: A total of 2,179 patients (mean age of 67.9 years and female predominance (53.1%)) were enrolled. SAPS3 was found accurate in all groups except in the underweight (AUC: 0.694 95% CI 0.616-0.773; HL = 0.042). The patients in the underweight group tended to be older, have longer hospital stay, have worse functional status, and have a higher value on prognostic scores. After the adjustments, no statistically significant difference between the BMI groups was noted in relation to mortality, except for the low weight that presented a likelihood of death of 3.50 (95% CI, 1.43-8.58, p = 0.006).

Conclusion: This research showed that SAPS3 had poor accuracy in predicting ICU mortality in underweight patients. This group was shown to be an independent risk factor for worse clinical outcomes.

Keywords: Body mass index; Intensive care unit; Mortality; Prognosis; Simplified Acute Physiology Score 3.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Study flowchart.
Figure 2
Figure 2
Performance of SAPS3 Mortality Prediction According to BMI Category. The area under the receiver operating characteristics curve was calculated for each BMI stratum. SAPS3 performance was adequate in all BMI groups except for the underweight group, in which a significantly poor discriminant function was observed. P-value for all curves <0.001.
Figure 3
Figure 3
Risk assessment model for intra-unit mortality. The white prism represents the OR in the univariate analysis, while the black prism represents the OR after adjustment in the binary logistic regression. The variables that presented statistical significance at the end of the binary logistic regression were represented. CRP (C-reactive protein); K (potassium level); MV (mechanical ventilation); VAD (vasopressor drug).
Figure 4
Figure 4
Death Probability According to BMI. A modified Kaplan-Meier curve to estimate the probability of death by BMI level. For every 1 additional kg/m2, there is a 0.04% reduction in the probability of death.
See this image and copyright information in PMC

References

    1. Haniffa R., Isaam I., De Silva A.P., Dondorp A.M., De Keizer N.F. Performance of critical care prognostic scoring systems in low and middle-income countries: a systematic review. Crit. Care. 2018 Dec 26;22(1):18. https://ccforum.biomedcentral.com/articles/10.1186/s13054-017-1930-8 [Internet]; Available from: - DOI - PMC - PubMed
    1. World Health Organization . Fact Sheets; 2018. Obesity and Overweigh.https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight [Internet]; Available from:
    1. Saúde M da. G. Estatística e Informação em Saúde; 2019. Vigitel Brasil 2018: Vigilância de fatores de risco e proteção para doenças crônicas por inquerito telefônico; p. 131.http://bvsms.saude.gov.br/bvs/publicacoes/vigitel_brasil_2011_fatores_ri... [Internet]; Available from:
    1. Marques M.B., Langouche L. Endocrine, metabolic, and morphologic alterations of adipose tissue during critical illness. Crit. Care Med. 2013 Jan;41(1):317–325. http://journals.lww.com/00003246-201301000-00031 [Internet]; Available from: - PubMed
    1. Popkin B.M., Corvalan C., Grummer-Strawn L.M. Dynamics of the double burden of malnutrition and the changing nutrition reality. Lancet. 2020 Jan;395(10217):65–74. https://linkinghub.elsevier.com/retrieve/pii/S0140673619324973 [Internet]; Available from: - PMC - PubMed

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