tetano
Editor, Senior Moderator
JAMA Netw Open
. 2022 Dec 1;5(12):e2246152.
doi: 10.1001/jamanetworkopen.2022.46152.
Clinical Characteristics and Outcomes of Patients Hospitalized With COVID-19 During the First 4 Waves in Zambia
Peter A Minchella[SUP] 1 [/SUP], Duncan Chanda[SUP] 2 [/SUP], Jonas Z Hines[SUP] 1 [/SUP], Sombo Fwoloshi[SUP] 2 [/SUP], Megumi Itoh[SUP] 1 [/SUP], Davies Kampamba[SUP] 2 [/SUP], Robert Chirwa[SUP] 2 [/SUP], Suilanji Sivile[SUP] 2 [/SUP], Khozya D Zyambo[SUP] 2 [/SUP], Simon Agolory[SUP] 1 [/SUP], Lloyd B Mulenga[SUP] 2 [/SUP]
Affiliations
Abstract
Importance: Few epidemiologic studies related to COVID-19 have emerged from countries in Africa, where demographic characteristics, epidemiology, and health system capacity differ from other parts of the world.
Objectives: To describe the characteristics and outcomes of patients admitted to COVID-19 treatment centers, assess risk factors for in-hospital death, and explore how treatment center admissions were affected by COVID-19 waves in Zambia.
Design, setting, and participants: This retrospective cohort study assessed patients admitted to COVID-19 treatment centers in 5 Zambian cities between March 1, 2020, and February 28, 2022.
Exposures: Risk factors for in-hospital mortality, including patient age and severity of COVID-19, at treatment center admission.
Main outcomes and measures: Patient information was collected, including inpatient disposition (discharged or died). Differences across and within COVID-19 waves were assessed. Mixed-effects logistic regression models were used to assess associations between risk factors and in-hospital mortality as well as between characteristics of admitted patients and timing of admission.
Results: A total of 3876 patients were admitted during 4 COVID-19 waves (mean [SD] age, 50.6 [19.5] years; 2103 male [54.3%]). Compared with the first 3 waves (pooled), the proportion of patients who were 60 years or older admitted during wave 4, when the Omicron variant was circulating, was significantly lower (250 of 1009 [24.8%] vs 1116 of 2837 [39.3%]; P < .001). Factors associated with in-hospital mortality included older age (≥60 vs <30 years; adjusted odds ratio [aOR], 3.55; 95% CI, 2.34-5.52) and HIV infection (aOR, 1.39; 95% CI, 1.07-1.79). Within waves, patients who were admitted during weeks 5 to 9 had significantly higher odds of being 60 years or older (aOR, 2.09; 95% CI, 1.79-2.45) or having severe COVID-19 at admission (aOR, 2.49; 95% CI, 2.14-2.90) than those admitted during the first 4 weeks.
Conclusions and relevance: The characteristics of admitted patients during the Omicron wave and risk factors for in-hospital mortality in Zambia reflect data reported elsewhere. Within-wave analyses revealed a pattern in which it appeared that admission of higher-risk patients was prioritized during periods when there were surges in demand for health services during COVID-19 waves. These findings support the need to expand health system capacity and improve health system resiliency in Zambia and other countries with resource-limited health systems.
. 2022 Dec 1;5(12):e2246152.
doi: 10.1001/jamanetworkopen.2022.46152.
Clinical Characteristics and Outcomes of Patients Hospitalized With COVID-19 During the First 4 Waves in Zambia
Peter A Minchella[SUP] 1 [/SUP], Duncan Chanda[SUP] 2 [/SUP], Jonas Z Hines[SUP] 1 [/SUP], Sombo Fwoloshi[SUP] 2 [/SUP], Megumi Itoh[SUP] 1 [/SUP], Davies Kampamba[SUP] 2 [/SUP], Robert Chirwa[SUP] 2 [/SUP], Suilanji Sivile[SUP] 2 [/SUP], Khozya D Zyambo[SUP] 2 [/SUP], Simon Agolory[SUP] 1 [/SUP], Lloyd B Mulenga[SUP] 2 [/SUP]
Affiliations
- PMID: 36512359
- DOI: 10.1001/jamanetworkopen.2022.46152
Abstract
Importance: Few epidemiologic studies related to COVID-19 have emerged from countries in Africa, where demographic characteristics, epidemiology, and health system capacity differ from other parts of the world.
Objectives: To describe the characteristics and outcomes of patients admitted to COVID-19 treatment centers, assess risk factors for in-hospital death, and explore how treatment center admissions were affected by COVID-19 waves in Zambia.
Design, setting, and participants: This retrospective cohort study assessed patients admitted to COVID-19 treatment centers in 5 Zambian cities between March 1, 2020, and February 28, 2022.
Exposures: Risk factors for in-hospital mortality, including patient age and severity of COVID-19, at treatment center admission.
Main outcomes and measures: Patient information was collected, including inpatient disposition (discharged or died). Differences across and within COVID-19 waves were assessed. Mixed-effects logistic regression models were used to assess associations between risk factors and in-hospital mortality as well as between characteristics of admitted patients and timing of admission.
Results: A total of 3876 patients were admitted during 4 COVID-19 waves (mean [SD] age, 50.6 [19.5] years; 2103 male [54.3%]). Compared with the first 3 waves (pooled), the proportion of patients who were 60 years or older admitted during wave 4, when the Omicron variant was circulating, was significantly lower (250 of 1009 [24.8%] vs 1116 of 2837 [39.3%]; P < .001). Factors associated with in-hospital mortality included older age (≥60 vs <30 years; adjusted odds ratio [aOR], 3.55; 95% CI, 2.34-5.52) and HIV infection (aOR, 1.39; 95% CI, 1.07-1.79). Within waves, patients who were admitted during weeks 5 to 9 had significantly higher odds of being 60 years or older (aOR, 2.09; 95% CI, 1.79-2.45) or having severe COVID-19 at admission (aOR, 2.49; 95% CI, 2.14-2.90) than those admitted during the first 4 weeks.
Conclusions and relevance: The characteristics of admitted patients during the Omicron wave and risk factors for in-hospital mortality in Zambia reflect data reported elsewhere. Within-wave analyses revealed a pattern in which it appeared that admission of higher-risk patients was prioritized during periods when there were surges in demand for health services during COVID-19 waves. These findings support the need to expand health system capacity and improve health system resiliency in Zambia and other countries with resource-limited health systems.