Postoperative intensive care allocation and mortality in high-risk surgical patients: evidence from a low- and middle-income country cohort
Alocação de cuidados intensivos pós-operatórios e mortalidade em pacientes cirúrgicos de alto risco: evidências de uma coorte de países de baixa e média renda
Adriene Stahlschmidt, Sávio Cavalcante Passos, Guilherme Roloff Cardoso, Gabriela Jungblut Schuh, Paulo Corrêa da Silva Neto, Stela Maris de Jezus Castro, Luciana Cadore Stefan
Abstract
Background
The escalation of surgeries for high-risk patients in Low- and Middle-Income Countries (LMICs) lacks evidence on the positive impact of Intensive Care Unit (ICU) admission and lacks universal criteria for allocation. This study explores the link between postoperative ICU allocation and mortality in high-risk patients within a LMIC. Additionally, it assesses the Ex-Care risk model's utility in guiding postoperative allocation decisions.
Methods
A secondary analysis was conducted in a cohort of high-risk surgical patients from a 800-bed university-affiliated teaching hospital in Southern Brazil (July 2017 to January 2020). Inclusion criteria encompassed 1431 inpatients with Ex-Care Model-assessed all-cause postoperative 30-day mortality risk exceeding 5%. The study compared 30-day mortality outcomes between those allocated to the ICU and the Postanesthetic Care Unit (PACU). Outcomes were also assessed based on Ex-Care risk model classes.
Results
Among 1431 high-risk patients, 250 (17.47%) were directed to the ICU, resulting in 28% in-hospital 30-day mortality, compared to 8.9% in the PACU. However, ICU allocation showed no independent effect on mortality (RR = 0.91; 95% CI 0.68‒1.20). Patients in the highest Ex-Care risk class (Class IV) exhibited a substantial association with mortality (RR = 2.11; 95% CI 1.54–2.90) and were more frequently admitted to the ICU (23.3% vs. 13.1%).
Conclusion
Patients in the highest Ex-Care risk class and those with complications faced elevated mortality risk, irrespective of allocation. Addressing the unmet need for adaptable postoperative care for high-risk patients outside the ICU is crucial in LMICs. Further research is essential to refine criteria and elucidate the utility of risk assessment tools like the Ex-Care model in assisting allocation decisions.
Keywords
Resumo
Introdução
A escalada de cirurgias para pacientes de alto risco em países de baixa e média renda (PBMR) carece de evidências sobre o impacto positivo da admissão em unidades de terapia intensiva (UTI) e carece de critérios universais para alocação. Este estudo explora a ligação entre a alocação pós-operatória na UTI e a mortalidade em pacientes de alto risco em um PBMR. Além disso, avalia a utilidade do modelo de risco Ex-Care na orientação de decisões de alocação pós-operatória.
Métodos
Uma análise secundária foi realizada em uma coorte de pacientes cirúrgicos de alto risco de um hospital universitário com 800 leitos no Sul do Brasil (julho de 2017 a janeiro de 2020). Os critérios de inclusão abrangeram 1.431 pacientes internados com risco de mortalidade pós-operatória em 30 dias, por todas as causas, avaliado pelo modelo Ex-Care, superior a 5%. O estudo comparou os desfechos de mortalidade em 30 dias entre aqueles alocados na UTI e na Sala de Recuperação Pós-anestésica (SRPA). Os resultados também foram avaliados com base nas classes do modelo de risco Ex-Care.
Resultados
Entre 1.431 pacientes de alto risco, 250 (17,47%) foram direcionados para a UTI, resultando em 28% de mortalidade hospitalar em 30 dias, em comparação com 8,9% na SRPA. No entanto, a alocação na UTI não mostrou efeito independente na mortalidade (RR = 0,91; IC 95% 0,68-1,20). Pacientes na classe de risco Ex-Care mais alta (Classe IV) apresentaram associação substancial com mortalidade (RR = 2,11; IC 95% 1,54–2,90) e foram internados com mais frequência na UTI (23,3% vs. 13,1%).
Conclusão
Os pacientes na classe de risco Ex-Care mais alta e aqueles com complicações enfrentaram risco elevado de mortalidade, independentemente da alocação. Abordar a necessidade não atendida de cuidados pós-operatórios adaptáveis para pacientes de alto risco fora da UTI é crucial nos países de baixa e média renda. Mais pesquisas são essenciais para refinar os critérios e elucidar a utilidade de ferramentas de avaliação de risco, como o modelo Ex-Care, no auxílio às decisões de alocação.
Palavras-chave
Referências
1. Weiser TG, Haynes AB, Molina G, et al. Estimate of the global volume of surgery in 2012: an assessment supporting improved health outcomes. Lancet. 2015;385(Suppl 2:S1).
2. Kahan BC, Koulenti D, Arvaniti K, et al. Critical care admission following elective surgery was not associated with survival benefit: prospective analysis of data from 27 countries. Intensive Care Med. 2017;43:971−9.
3. Rose J, Weiser TG, Hider P, et al. Estimated need for surgery worldwide based on prevalence of diseases: a modelling strategy for the WHO Global Health Estimate. Lancet Glob Heal. 2015;3(Suppl 2):S13−20.
4. Pearse RM, Harrison DA, James P, et al. Identification and characterisation of the high-risk surgical population in the United Kingdom. Crit Care. 2006;10:R81.
5. Rozeboom PD, Henderson WG, Dyas AR, et al. Development and Validation of a Multivariable Prediction Model for Postoperative Intensive Care Unit Stay in a Broad Surgical Population. JAMA Surg. 2022;157:344−52.
6. Silva JMJ, Rocha HMC, Katayama HT, et al. SAPS 3 score as a predictive factor for postoperative referral to intensive care unit. Ann Intensive Care. 2016;6:42.
7. Massenburg BB, Saluja S, Jenny HE, et al. Assessing the Brazilian surgical system with six surgical indicators: a descriptive and modelling study. BMJ Glob Heal. 2017;18:e000226.
8. Gutierrez CS, Passos SC, Castro SMJ, et al. Few and feasible preoperative variables can identify high-risk surgical patients: derivation and validation of the Ex-Care risk model. Br J Anaesth. 2021;126:525−32.
9. Stefani LPC, Gutierrez CDS, Castro SMDJ, et al. Derivation and validation of a preoperative risk model for postoperative mortality (SAMPE model): An approach to care stratification. PLoS One. 2017;12:1−14.
10. Silva Junior J, Chaves R, Corr ea T, et al. Epidemiology and out- ^ come of high-surgical-risk patients admitted to an intensive care unit in Brazil. Rev Bras Ter Intensiva. 2020;32(1):17−27.
11. Stahlschmidt A, Passos SC, Cardoso GR, et al. Enhanced perioperative care to improve outcomes for high-risk surgical patients in Brazil: a single-centre before-and-after cohort study. Anaesthesia. 2022;77:416−27.
12. von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61:344−9.
13. Saklad M. Grading of patients for surgical procedures. Anesthesiology. 1941;2:281−4.
14. Glance LG, Lustik SJ, Hannan EL, et al. The surgical mortality probability model: Derivation and validation of a simple risk prediction rule for noncardiac surgery. Ann Surg. 2012;255:696−702.
15. Jammer I, Wickboldt N, Sander M, et al. Standards for definitions and use of outcome measures for clinical effectiveness research in perioperative medicine: European Perioperative Clinical Outcome (EPCO) definitions: A statement from the ESAESICM joint taskforce on perioperative outcome measur. Eur J Anaesthesiol. 2015;32:88−105.
16. Singer M, Deutschman C, Seymour C, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis3). JAMA. 2016;315:801−10.
17. Davies S, Francis J, Dilley J, et al. Measuring outcomes after major abdominal surgery during hospitalization: reliability and validity of the Postoperative Morbidity Survey. Perioper Med. 2013;2:1.
18. Victora C, Huttly S, Fuchs S, et al. The role of conceptual frameworks in epidemiological analysis: a hierarchical approach. Int J Epidemiol. 1997;26:224−7.
19. Wunsch H, Gershengorn HB, Cooke CR, et al. Use of Intensive Care Services for Medicare Beneficiaries Undergoing Major Surgical Procedures. Anesthesiology. 2016;124:899−907.
20. Gillies MA, Harrison EM, Pearse RM, et al. Intensive care utilization and outcomes after high-risk surgery in Scotland: a population-based cohort study. Br J Anaesth. 2017;118:123−31.
21. Pearse RM, Moreno RP, Bauer P, et al. Mortality after surgery in Europe: a 7 day cohort study. Lancet. 2012;380:1059−65.
22. Skinner DL, De Vasconcellos K, Wise R, et al. Critical care admission of South African (SA) surgical patients: Results of the SA Surgical Outcomes Study. S Afr Med J. 2017;107:411−9.
23. Ghaffar S, Pearse RM, Gillies MA. ICU admission after surgery: who benefits? Curr Opin Crit Care. 2017;23:424−9.
24. Ozdemir BA, Sinha S, Karthikesalingam A, et al. Mortality of emergency general surgical patients and associations with hospital structures and processes. Br J Anaesth. 2016;116:54−62.
25. Gillies MA, Pearse RM. Intensive Care after High-risk Surgery: What’s in a Name? Anesthesiology. 2016;124:761−2.
26. Nates JL, Nunnally M, Kleinpell R, et al. ICU Admission, Discharge, and Triage Guidelines: A Framework to Enhance Clinical Operations, Development of Institutional Policies, and Further Research. Crit Care Med. 2016;44:1552−602.
27. Griffiths P, Ball J, Drennan J, et al. The association between patient safety outcomes and nurse/healthcare assistant skill mix and staffing levels & factors that may influence staffing requirements. University of Southampton; 2014 https://www. nice.org.uk/guidance/sg1/documents/safe-staffing-for-nursing-in-adult-inpatient-wards-in-acute-hospitals-evidencereview-12 Published.
28. Silva Junior JM, Chaves RCF, Corr ea TD, et al. Epidemiology and ^ outcome of high-surgical-risk patients admitted to an intensive care unit in Brazil. Rev Bras Ter Intensiva. 2020;32:17−27.
29. The Royal College of Surgeons of England. The High-Risk General Surgical Patient: Raising the Standard. Royal College of Surgeons of England. 2018. https://www.rcseng.ac.uk/news-andevents/media-centre/press-releases/high-risk-general-surgical Published.
30. Chan DXH, Sim YE, Chan YH, et al. Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: A single-center retrospective study. BMJ Open. 2018;8:1−11.
Submetido em:
11/01/2024
Aceito em:
14/05/2024
Facebook
Google+
Twitter
LinkedIn
Mendeley
StumbleUpon
CiteULike
Reddit
Email