ICU Mortality Across Prepandemic and Pandemic Cohorts in a Resource-Limited Setting
2023; Elsevier BV; Volume: 1; Issue: 1 Linguagem: Inglês
10.1016/j.chstcc.2023.100005
ISSN2949-7884
AutoresGeorge L. Anesi, Stella Savarimuthu, Jonathan Invernizzi, Robyn Hyman, Arisha Ramkillawan, Creaghan Eddey, Robert Wise, Michelle Smith, George L. Anesi, Nikki Allorto, Leesa Bishop, Carel Cairns, Creaghan Eddey, Robyn Hyman, Jonathan Invernizzi, Sumayyah Khan, Rachel Kohn, Arisha Ramkillawan, Stella Savarimuthu, Michelle Smith, Gary E. Weissman, D. Wilson, Robert Wise,
Tópico(s)Healthcare cost, quality, practices
ResumoBackgroundHospital adaptation and resiliency, required during public health emergencies to optimize outcomes, are understudied especially in resource-limited settings.Research QuestionWhat are the prepandemic and pandemic critical illness outcomes in a resource-limited setting and in the context of capacity strain?Study Design and MethodsWe performed a retrospective cohort study among patients admitted to ICUs at two public hospitals in the KwaZulu-Natal Department of Health in South Africa preceding and during the COVID-19 pandemic (2017-2022). We used multivariate logistic regression to analyze the association between three patient cohorts (prepandemic non-COVID-19, pandemic non-COVID-19, and pandemic COVID-19) and ICU capacity strain and the primary outcome of ICU mortality.ResultsThree thousand two hundred twenty-one patients were admitted to the ICU during the prepandemic period and 2,539 patients were admitted to the ICU during the pandemic period (n = 375 [14.8%] with COVID-19 and n = 2,164 [85.2%] without COVID-19). The prepandemic and pandemic non-COVID-19 cohorts were similar. Compared with the non-COVID-19 cohorts, the pandemic COVID-19 cohort showed older age, higher rates of chronic cardiovascular disease and diabetes, less extrapulmonary organ dysfunction, and longer ICU length of stay. Compared with the prepandemic non-COVID-19 cohort, the pandemic non-COVID-19 cohort showed similar odds of ICU mortality (OR, 1.06; 95% CI, 0.90-1.25; P = .50) whereas the pandemic COVID-19 cohort showed significantly increased odds of ICU mortality (OR, 3.91; 95% CI, 3.03-5.05 P < .0005). ICU occupancy was not associated with ICU mortality in either the COVID-19 cohort (OR, 1.05 per 10% change in ICU occupancy; 95% CI, 0.96-1.14; P = .27) or the pooled non-COVID-19 cohort (OR, 1.01 per 10% change in ICU occupancy; 95% CI, 0.98-1.03; P = .52).InterpretationPatients admitted to the ICU before and during the pandemic without COVID-19 were broadly similar in clinical characteristics and outcomes, suggesting critical care resiliency, whereas patients admitted to the ICU with COVID-19 showed important clinical differences and significantly higher mortality. Hospital adaptation and resiliency, required during public health emergencies to optimize outcomes, are understudied especially in resource-limited settings. What are the prepandemic and pandemic critical illness outcomes in a resource-limited setting and in the context of capacity strain? We performed a retrospective cohort study among patients admitted to ICUs at two public hospitals in the KwaZulu-Natal Department of Health in South Africa preceding and during the COVID-19 pandemic (2017-2022). We used multivariate logistic regression to analyze the association between three patient cohorts (prepandemic non-COVID-19, pandemic non-COVID-19, and pandemic COVID-19) and ICU capacity strain and the primary outcome of ICU mortality. Three thousand two hundred twenty-one patients were admitted to the ICU during the prepandemic period and 2,539 patients were admitted to the ICU during the pandemic period (n = 375 [14.8%] with COVID-19 and n = 2,164 [85.2%] without COVID-19). The prepandemic and pandemic non-COVID-19 cohorts were similar. Compared with the non-COVID-19 cohorts, the pandemic COVID-19 cohort showed older age, higher rates of chronic cardiovascular disease and diabetes, less extrapulmonary organ dysfunction, and longer ICU length of stay. Compared with the prepandemic non-COVID-19 cohort, the pandemic non-COVID-19 cohort showed similar odds of ICU mortality (OR, 1.06; 95% CI, 0.90-1.25; P = .50) whereas the pandemic COVID-19 cohort showed significantly increased odds of ICU mortality (OR, 3.91; 95% CI, 3.03-5.05 P < .0005). ICU occupancy was not associated with ICU mortality in either the COVID-19 cohort (OR, 1.05 per 10% change in ICU occupancy; 95% CI, 0.96-1.14; P = .27) or the pooled non-COVID-19 cohort (OR, 1.01 per 10% change in ICU occupancy; 95% CI, 0.98-1.03; P = .52). Patients admitted to the ICU before and during the pandemic without COVID-19 were broadly similar in clinical characteristics and outcomes, suggesting critical care resiliency, whereas patients admitted to the ICU with COVID-19 showed important clinical differences and significantly higher mortality. Take-home PointsStudy Question: How did critical care outcomes compare across three peripandemic study cohorts (prepandemic non-COVID-19, pandemic non-COVID-19, and pandemic COVID-19) and across degrees of capacity strain in a resource-limited setting?Results: Patients without COVID-19 before and during the pandemic showed comparable outcomes, whereas patients with COVID-19 showed significantly increased odds of ICU mortality. ICU occupancy, although increased during the pandemic, was not associated with ICU mortality for patients either without or with COVID-19.Interpretation: These results suggest a degree of critical care resiliency in a resource-limited setting that may exceed that being reported in better-resourced settings, perhaps owing to more longitudinal experience with scarce resource allocation and critical care delivery under adverse circumstances. Study Question: How did critical care outcomes compare across three peripandemic study cohorts (prepandemic non-COVID-19, pandemic non-COVID-19, and pandemic COVID-19) and across degrees of capacity strain in a resource-limited setting? Results: Patients without COVID-19 before and during the pandemic showed comparable outcomes, whereas patients with COVID-19 showed significantly increased odds of ICU mortality. ICU occupancy, although increased during the pandemic, was not associated with ICU mortality for patients either without or with COVID-19. Interpretation: These results suggest a degree of critical care resiliency in a resource-limited setting that may exceed that being reported in better-resourced settings, perhaps owing to more longitudinal experience with scarce resource allocation and critical care delivery under adverse circumstances. In the face of public health emergencies and acute surge events such as the COVID-19 pandemic, hospitals are tested on their adaptation, the ability to improve care and outcomes for primarily affected (ie, infected) patients by implementing new care processes based on accumulated experience, and their resiliency, that is, the ability to continue to deliver high-quality care to patients not primarily affected (ie, bystander patients, those uninfected but who still require acute care during this time), despite the presence of a surge event.1Anderson J.E. Aase K. Bal R. et al.Multilevel influences on resilient healthcare in six countries: an international comparative study protocol.BMJ Open. 2020; 10e039158Crossref Scopus (11) Google Scholar, 2Anesi G.L. Jablonski J. Harhay M.O. et al.Characteristics, outcomes, and trends of patients with COVID-19-related critical illness at a learning health system in the United States.Ann Intern Med. 2021; 174: 613-621Crossref PubMed Scopus (72) Google Scholar, 3Anesi G.L. Lynch Y. Evans L. A Conceptual and adaptable approach to hospital preparedness for acute surge events due to emerging infectious diseases.Crit Care Explor. 2020; 2e0110Crossref PubMed Scopus (32) Google Scholar, 4Meyer D. Bishai D. Ravi S.J. et al.A checklist to improve health system resilience to infectious disease outbreaks and natural hazards.BMJ Glob Health. 2020; 5: e002429Crossref PubMed Scopus (24) Google Scholar, 5Prescott H.C. Levy M.M. Survival from severe coronavirus disease 2019: is it changing?.Crit Care Med. 2021; 49: 351-353Crossref PubMed Scopus (4) Google Scholar Although much attention during a respiratory viral acute surge event initially and naturally is focused on adaptation for primarily infected patients, the resiliency required for optimal care delivery and outcomes for uninfected bystander patients often is overlooked. However, it has the potential for large impacts on population health. Prepandemic research has demonstrated a relationship between acute capacity strain and poorer bystander patient outcomes within individual hospital wards.6Churpek M.M. Gupta S. Spicer A.B. et al.Hospital-level variation in death for critically ill patients with COVID-19.Am J Respir Crit Care Med. 2021; 204: 403-411Crossref PubMed Scopus (29) Google Scholar During the pandemic, COVID-19-related capacity strain has been associated with poorer outcomes for patients without COVID-19 or all-comer patients in ICUs, hospitals, and the general population.7French G. Hulse M. Nguyen D. et al.Impact of hospital strain on excess deaths during the COVID-19 pandemic—United States, July 2020-July 2021.MMWR Morb Mortal Wkly Rep. 2021; 70: 1613-1616Crossref PubMed Google Scholar, 8Wilcox M.E. Rowan K.M. Harrison D.A. Doidge J.C. Does unprecedented ICU capacity strain, as experienced during the COVID-19 pandemic, impact patient outcome?.Crit Care Med. 2022; 50: e548-e556Crossref PubMed Scopus (14) Google Scholar, 9Zampieri F.G. Bastos L.S.L. Soares M. Salluh J.I. Bozza F.A. The association of the COVID-19 pandemic and short-term outcomes of non-COVID-19 critically ill patients: an observational cohort study in Brazilian ICUs.Intensive Care Med. 2021; 47: 1440-1449Crossref PubMed Scopus (17) Google Scholar, 10Duclos A. Cordier Q. Polazzi S. et al.Excess mortality among non-COVID-19 surgical patients attributable to the exposure of French intensive and intermediate care units to the pandemic.Intensive Care Med. 2023; 49: 313-323Crossref PubMed Scopus (0) Google Scholar The COVID-19 pandemic has caused devastating illness globally. Despite a heavy burden of disease, resource-limited settings in general and on the African continent in particular remain underrepresented in pandemic research,11Naidoo A.V. Hodkinson P. Lai King L. Wallis L.A. African authorship on African papers during the COVID-19 pandemic.BMJ Glob Health. 2021; 6: e004612Crossref PubMed Scopus (13) Google Scholar and vaccination rates of < 30% portend a prolonged regional pandemic.12Covid-19 vaccine tracker: the global race to vaccinate. Financial Times Updated December 23, 2022. Accessed February 9, 2023. https://ig.ft.com/coronavirus-vaccine-tracker/?areas=gbr&areas=usa&areas=eue&areas=xaf&cumulative=1&doses=full&populationAdjusted=1Google Scholar,13Bakamutumaho B. Lutwama J.J. Owor N. et al.Epidemiology, clinical characteristics, and mortality of hospitalized patients with severe COVID-19 in Uganda, 2020-2021.Ann Am Thorac Soc. 2022; 19: 2100-2103Crossref PubMed Scopus (1) Google Scholar In those studies that have focused on African patients during the pandemic, the absence of high-fidelity prepandemic local cohorts has restricted analyses to within-pandemic comparisons.14African COVID-19 Critical Care Outcomes Study (ACCCOS) Investigators. Patient care and clinical outcomes for patients with COVID-19 infection admitted to African high-care or intensive care units (ACCCOS): a multicentre, prospective, observational cohort study.Lancet. 2021; 397: 1885-1894Abstract Full Text Full Text PDF PubMed Scopus (85) Google Scholar,15Maslo C. Friedland R. Toubkin M. Laubscher A. Akaloo T. Kama B. Characteristics and outcomes of hospitalized patients in South Africa during the COVID-19 Omicron wave compared with previous waves.JAMA. 2022; 327: 583-584Crossref PubMed Scopus (252) Google Scholar It remains unclear whether the same adaptation and resiliency relationships persist in resource-limited settings, where important differences in ICU referral and admission practices and ICU resources exist, and in the face of differences in hospital and ICU capacity strain. In particular, our prior research has shown that ICU occupancy, as a metric of ICU capacity strain, is highly associated with ICU admission decisions in well-resourced settings.16Anesi G.L. Chowdhury M. Small D.S. et al.Association of a novel index of hospital capacity strain with admission to intensive care units.Ann Am Thorac Soc. 2020; 17: 1440-1447Crossref PubMed Scopus (19) Google Scholar,17Anesi G.L. Liu V.X. Gabler N.B. et al.Associations of intensive care unit capacity strain with disposition and outcomes of patients with sepsis presenting to the emergency department.Ann Am Thorac Soc. 2018; 15: 1328-1335Crossref PubMed Scopus (40) Google Scholar However, this relationship may not persist in resource-limited settings where more rigorous ICU gatekeeping practices exist in the context of more chronic scarcity and to preserve ICU beds for those patients most likely to benefit.18Anesi G.L. Gabler N.B. Allorto N.L. et al.Intensive care unit capacity strain and outcomes of critical illness in a resource-limited setting: a 2-hospital study in South Africa.J Intensive Care Med. 2020; 35: 1104-1111Crossref PubMed Scopus (15) Google Scholar Chronically resource-limited hospitals may be overwhelmed more easily by pandemic-related capacity strain or alternatively may be more resilient owing to experience with scarce resource allocation and critical care delivery under adverse circumstances. As part of the South Africa ICU Capacity Strain Study Group, we performed a retrospective cohort study to analyze critical care outcomes across three study cohorts (prepandemic non-COVID-19, pandemic non-COVID-19, and pandemic COVID-19) and across degrees of capacity strain. The study data source was the Integrated Critical Care Electronic Database,19Allorto N.L. Wise R.D. Development and evaluation of an integrated electronic data management system in a South African metropolitan critical care service.South Afr J Anaesth Analg. 2015; 21: 31-35Crossref Scopus (7) Google Scholar which has been the source for multiple prior publications from the South Africa ICU Capacity Strain Study Group.18Anesi G.L. Gabler N.B. Allorto N.L. et al.Intensive care unit capacity strain and outcomes of critical illness in a resource-limited setting: a 2-hospital study in South Africa.J Intensive Care Med. 2020; 35: 1104-1111Crossref PubMed Scopus (15) Google Scholar,20Bishop L.A. Wilson D.P.K. Wise R.D. Savarimuthu S.M. Anesi G.L. Prognostic value of the Quick Sepsis-Related Organ Failure Assessment (qSOFA) score among critically ill medical and surgical patients with suspected infection in a resource-limited setting.Afr J Thorac Crit Care Med. 2021; 27: 145-150Crossref Scopus (2) Google Scholar, 21Kahn S. Wise R. Savarimuthu S.M. Anesi G.L. Association between pre-ICU hospital length of stay and ICU outcomes in a resource-limited setting.SAJCC. 2021; 37: 98-103Crossref Google Scholar, 22Savarimuthu S.M. Cairns C. Allorto N.L. et al.qSOFA as a predictor of ICU outcomes in a resource-limited setting in KwaZulu-Natal Province, South Africa.SAJCC. 2020; 36: 92-95Crossref Google Scholar The ICU database includes all referrals and admissions for ICU care at two public hospitals within the KwaZulu-Natal Department of Health (Pietermaritzburg, South Africa): Greys Hospital, a tertiary hospital with approximately 530 inpatient beds, and Harry Gwala Regional Hospital (formerly Edendale Hospital), a secondary or regional hospital with approximately 900 inpatient beds. These hospitals serve the large local urban and suburban population, as well as patients referred from surrounding district and community hospitals. Each hospital has one multidisciplinary (ie, mixed medical and surgical) ICU that admits adult and pediatric (either primary or as overflow) patients and has closed, high-intensity staffing models typically led by an anesthesia or surgical critical care consultant (equivalent to an attending physician or surgeon in the United States). The critical care consultant oversees daytime rounds with a team of medical officers (generalist doctors) and registrars (trainees equivalent to resident physicians in the United States) who staff the ICU overnight in remote contact with the consultant. The South African public health system, provided to citizens without out-of-pocket costs, treats approximately 84% of the population, but accounts for 43% of the country's ICU beds. ICU case mix is notable for: comprising predominantly Black race, skewing male sex, including approximately 20% with HIV infection, and having ICU needs most commonly resulting from surgical issues (trauma and other postoperative monitoring) and infection. ICU beds at the study hospitals are allocated based on the Society of Critical Care Medicine ICU triage priority system and is typically limited to patients needing ICU-specific therapy (priority I) or intensive monitoring (priority II), with rare admissions of patients less likely (priority III), too well (priority IVA), or too sick (priority IVB) to benefit from ICU admission.18Anesi G.L. Gabler N.B. Allorto N.L. et al.Intensive care unit capacity strain and outcomes of critical illness in a resource-limited setting: a 2-hospital study in South Africa.J Intensive Care Med. 2020; 35: 1104-1111Crossref PubMed Scopus (15) Google Scholar,23Task Force of the American College of Critical Care Medicine, Society of Critical Care MedicineGuidelines for intensive care unit admission, discharge, and triage.Crit Care Med. 1999; 27: 633-638Crossref PubMed Google Scholar The ICU database is integrated into the clinical ICU team real-time workflow and captures a discrete set of variables at the time of ICU referral and ICU admission and end-ICU disposition.18Anesi G.L. Gabler N.B. Allorto N.L. et al.Intensive care unit capacity strain and outcomes of critical illness in a resource-limited setting: a 2-hospital study in South Africa.J Intensive Care Med. 2020; 35: 1104-1111Crossref PubMed Scopus (15) Google Scholar Patient-level COVID-19 status was noted in the ICU database by the clinical teams in real time and was audited by the study team. National South Africa data on SARS-CoV-2 case and vaccination trends were extracted separately from the publicly available Our World in Data COVID-19 dataset,24COVID-19 datasetOur World in Data; 2023. Updated June 2, 2023.https://ourworldindata.org/covid-casesDate accessed: February 2, 2023Google Scholar with raw data from the Johns Hopkins University Center for Systems Science and Engineering COVID-19 data repository.25Dong E. Du H. Gardner L. An interactive web-based dashboard to track COVID-19 in real time.Lancet Infect Dis. 2020; 20: 533-534Abstract Full Text Full Text PDF PubMed Scopus (5853) Google Scholar The study included adult (aged ≥ 18 years) patients admitted to the ICU at the study hospitals from January 1, 2017, through June 30, 2022, and included three patient cohorts: the prepandemic non-COVID-19 patient cohort admitted from January 1, 2017, through March 4, 2020, and the pandemic non-COVID-19 and pandemic COVID-19 patient cohorts admitted from March 5, 2020 (when South Africa recorded its first SARS-CoV-2 case24COVID-19 datasetOur World in Data; 2023. Updated June 2, 2023.https://ourworldindata.org/covid-casesDate accessed: February 2, 2023Google Scholar,25Dong E. Du H. Gardner L. An interactive web-based dashboard to track COVID-19 in real time.Lancet Infect Dis. 2020; 20: 533-534Abstract Full Text Full Text PDF PubMed Scopus (5853) Google Scholar) through June 30, 2022. The prepandemic non-COVID-19 cohort included a subgroup of patients previously described and studied.20Bishop L.A. Wilson D.P.K. Wise R.D. Savarimuthu S.M. Anesi G.L. Prognostic value of the Quick Sepsis-Related Organ Failure Assessment (qSOFA) score among critically ill medical and surgical patients with suspected infection in a resource-limited setting.Afr J Thorac Crit Care Med. 2021; 27: 145-150Crossref Scopus (2) Google Scholar, 21Kahn S. Wise R. Savarimuthu S.M. Anesi G.L. Association between pre-ICU hospital length of stay and ICU outcomes in a resource-limited setting.SAJCC. 2021; 37: 98-103Crossref Google Scholar, 22Savarimuthu S.M. Cairns C. Allorto N.L. et al.qSOFA as a predictor of ICU outcomes in a resource-limited setting in KwaZulu-Natal Province, South Africa.SAJCC. 2020; 36: 92-95Crossref Google Scholar The pandemic cohorts included pandemic periods and surges dominated by five viral variants in South Africa: Ancestral Wuhan strain (peak July 2020), Beta variant (peak January 2021), Delta variant (peak July 2021), Omicron BA.1/BA.2 subvariants (peak December 2021), and Omicron BA.4/BA.5 subvariants (peak May 2022).26Hodcroft E.B. CoVariants.org. CoVariants.org website.https://covariants.orgDate accessed: February 9, 2023Google Scholar We performed two coprimary retrospective cohort analyses to measure the association of (1) the three study cohorts (prepandemic non-COVID-19, pandemic non-COVID-19, and pandemic COVID-19) and (2) degrees of capacity strain, with the primary outcome of ICU mortality. ICU mortality was defined as a death in the ICU or a palliative discharge from the ICU. Patient-level adjustment variables (recorded at ICU admission) for all models included: age, sex, HIV status, chronic cardiovascular disease, diabetes, medical vs surgical status, and study hospital.14African COVID-19 Critical Care Outcomes Study (ACCCOS) Investigators. Patient care and clinical outcomes for patients with COVID-19 infection admitted to African high-care or intensive care units (ACCCOS): a multicentre, prospective, observational cohort study.Lancet. 2021; 397: 1885-1894Abstract Full Text Full Text PDF PubMed Scopus (85) Google Scholar We additionally adjusted for the national cumulative count of fully vaccinated individuals, defined as completion of any primary vaccine series as of the calendar day of ICU admission (patient-level vaccination status was not available).24COVID-19 datasetOur World in Data; 2023. Updated June 2, 2023.https://ourworldindata.org/covid-casesDate accessed: February 2, 2023Google Scholar,25Dong E. Du H. Gardner L. An interactive web-based dashboard to track COVID-19 in real time.Lancet Infect Dis. 2020; 20: 533-534Abstract Full Text Full Text PDF PubMed Scopus (5853) Google Scholar We did not adjust for SARS-CoV-2 viral variant because we believed it would be colinear with COVID-19-based cohorts (an exposure variable), but we accounted for viral variants in secondary analyses described herein. Although we adjusted for chronic comorbidities, we elected not to adjust for acute physiologic features because this exists in the causal pathway between ICU admission indication (ie, COVID-19 vs non-COVID-19) and ICU outcomes. In the first cohort analysis, we performed multivariate logistic regression assessing the association between patient cohort (ie, prepandemic non-COVID-19, pandemic non-COVID-19, or pandemic COVID-19) and ICU mortality, adjusted for patient-level covariates and national cumulative count of fully vaccinated individuals (first coprimary analysis). To account for a relationship between capacity strain and COVID-19 outcomes6Churpek M.M. Gupta S. Spicer A.B. et al.Hospital-level variation in death for critically ill patients with COVID-19.Am J Respir Crit Care Med. 2021; 204: 403-411Crossref PubMed Scopus (29) Google Scholar,8Wilcox M.E. Rowan K.M. Harrison D.A. Doidge J.C. Does unprecedented ICU capacity strain, as experienced during the COVID-19 pandemic, impact patient outcome?.Crit Care Med. 2022; 50: e548-e556Crossref PubMed Scopus (14) Google Scholar,27Kadri S.S. Sun J. Lawandi A. et al.Association between caseload surge and COVID-19 survival in 558 U.S. hospitals, March to August 2020.Ann Intern Med. 2021; 174: 1240-1251Crossref PubMed Scopus (82) Google Scholar,28Bravata D.M. Perkins A.J. Myers L.J. et al.Association of intensive care unit patient load and demand with mortality rates in US Department of Veterans Affairs hospitals during the COVID-19 pandemic.JAMA Network Open. 2021; 4e2034266Crossref Scopus (153) Google Scholar and based on prior work in this and other data sets,16Anesi G.L. Chowdhury M. Small D.S. et al.Association of a novel index of hospital capacity strain with admission to intensive care units.Ann Am Thorac Soc. 2020; 17: 1440-1447Crossref PubMed Scopus (19) Google Scholar,18Anesi G.L. Gabler N.B. Allorto N.L. et al.Intensive care unit capacity strain and outcomes of critical illness in a resource-limited setting: a 2-hospital study in South Africa.J Intensive Care Med. 2020; 35: 1104-1111Crossref PubMed Scopus (15) Google Scholar,29Anesi G.L. Liu V.X. Chowdhury M. et al.Association of ICU admission and outcomes in sepsis and acute respiratory failure.Am J Respir Crit Care Med. 2022; 205: 520-528Crossref PubMed Scopus (8) Google Scholar we performed a sensitivity analysis further adjusted for five capacity strain metrics: ICU occupancy, ICU referral burden, ICU turnover, ICU acuity (see e-Appendix 1 for metric definitions), and national 7-day rolling mean of incident SARS-CoV-2 cases per 1 million residents.24COVID-19 datasetOur World in Data; 2023. Updated June 2, 2023.https://ourworldindata.org/covid-casesDate accessed: February 2, 2023Google Scholar,25Dong E. Du H. Gardner L. An interactive web-based dashboard to track COVID-19 in real time.Lancet Infect Dis. 2020; 20: 533-534Abstract Full Text Full Text PDF PubMed Scopus (5853) Google Scholar To account for the high trauma proportion in the non-COVID-19 cohorts (35.5% prepandemic non-COVID-19 and 37.0% pandemic non-COVID-19 cohorts vs 5.5% in the pandemic COVID-19 cohort) and the important differences between trauma and nontrauma ICU admissions and outcomes, in another sensitivity analysis, we restricted the outcome to patients without trauma as the primary indication for ICU admission. In the second cohort analysis, we performed multivariate logistic regression assessing the association between ICU occupancy, as a continuous variable, and ICU mortality, now stratified by COVID-19 status and with the same strategy of patient-level adjustment (second coprimary analysis). We also report predicted probabilities of ICU mortality for ICU occupancy deciles. In a secondary analysis to account for different risk between SARS-CoV-2 viral variants, we performed multivariate logistic regression assessing the association between pandemic surge periods and ICU mortality, again with the same patient-level adjustment strategy. Pandemic surge periods (e-Table 1) were defined based on the dominant national variant26Hodcroft E.B. CoVariants.org. CoVariants.org website.https://covariants.orgDate accessed: February 9, 2023Google Scholar and a national 7-day rolling mean of incident SARS-CoV-2 cases of ≥ 50 cases/1 million residents as of the calendar day of ICU admission.24COVID-19 datasetOur World in Data; 2023. Updated June 2, 2023.https://ourworldindata.org/covid-casesDate accessed: February 2, 2023Google Scholar,25Dong E. Du H. Gardner L. An interactive web-based dashboard to track COVID-19 in real time.Lancet Infect Dis. 2020; 20: 533-534Abstract Full Text Full Text PDF PubMed Scopus (5853) Google Scholar Periods between March 5, 2020, and June 30, 2022, with < 50 incident SARS-CoV-2 cases/1 million residents were considered between-surge periods. We calculated descriptive statistics of the prepandemic non-COVID-19, pandemic non-COVID-19, and pandemic COVID-19 cohorts and for the ICU capacity strain metrics and report ORs and predicted probabilities for logistic regression models. Sample size estimations were performed assuming a two-sided test with a type I error rate (α) of 5% and 80% power (type II error rate [β], 20%). For the association between peripandemic cohorts and ICU mortality, based on available sample size, we estimated a detectable OR of 1.21 for the pandemic non-COVID-19 cohort and a detectable OR of 1.37 for the pandemic COVID-19 cohort.30Faul F. Erdfelder E. Lang A.G. Buchner A. G∗Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences.Behav Res Methods. 2007; 39: 175-191Crossref PubMed Google Scholar For the association between ICU occupancy and ICU mortality, based on available sample size and allowing for a strong correlation between covariates (R2 = 0.6), we estimated a detectable mortality effect difference of 2.6% for the pooled non-COVID-19 cohort and a detectable mortality effect difference of 9.2% for the pandemic COVID-19 cohort.31Ender PB. Stata package: University of California, Los Angeles Advanced Research Computing Statistical Methods and Data Analytics website. Accessed May 25, 2023. https://stats.oarc.ucla.edu/stata/ado/analysis/powerlog-hlp-htmGoogle Scholar Missing values for model outcomes, exposures, and covariates were low (< 1%), allowing for a complete case analysis. P values of < .05 were considered statistically significant and 95% CIs are presented throughout. All analyses were conducted using Stata version 14.2 (StataCorp LP). The study protocol was approved by the Biomedical Research Ethics Committee of Harry Gwala Regional Hospital ("Characteristics and Outcomes of Patients Admitted With COVID-19 to a South African ICU," March 16, 2022, Pietermaritzburg, South Africa) and Greys Hospital ("Characteristics and Outcomes of Patients Admitted With COVID-19 to South African Regional and Tertiary ICUs," protocol no. 00002156, November 25, 2020, Pietermaritzburg, South Africa), and by the institutional review board of the University of Pennsylvania ("Association of ICU Capacity Strain and Mortality in a Resource-Limited Setting," protocol no. 824688, July 29, 2020, Philadelphia, PA). National South Africa COVID-19 data are licensed for public use through a Creative Commons Attribution 4.0 International license.24COVID-19 datasetOur World in Data; 2023. Updated June 2, 2023.https://ourworldindata.org/covid-casesDate accessed: February 2, 2023Google Scholar,25Dong E. Du H. Gardner L. An interactive web-based dashboard to track COVID-19 in real time.Lancet Infect Dis. 2020; 20: 533-534Abstract Full Text Full Text PDF PubMed Scopus (5853) Google Scholar Table 1 and e-Table 2 report study patient characteristics by cohort. Three thousand two hundred twenty-one patients were admitted to the ICU during the
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