Short- and Long-Term Mortality and Mortality Risk Factors among Nursing Home Patients after COVID-19 Infection.

OBJECTIVE: To assess short- and long-term mortality and risk factors in nursing home patients with COVID-19 infection. DESIGN: Retrospective 2-center cohort study. SETTING AND PARTICIPANTS: Dutch nursing home patients with clinically suspected COVID-19 infection confirmed by reverse transcription-polymerase chain reaction testing. METHODS: Data were gathered between March 2020 and November 2020 using electronic medical records, including demographic characteristics, comorbidities, medical management, and symptoms on the first day of suspected COVID-19 infection. Mortality at 30 days and 6 months was assessed using multivariate logistic regression models and Kaplan-Meier analysis. At 6 months, a subgroup analysis was performed to estimate the mortality risk between COVID-negative patients and patients who survived COVID-19. Risk factors for mortality were assessed through multivariate logistic regression models. RESULTS: A total of 321 patients with suspected COVID-19 infection were included, of whom 134 tested positive. Sixty-two patients in the positive group died at 30 days, with a short-term mortality rate of 2.9 (95% CI 1.7-5.3). Risk factors were fatigue (OR 2.6, 95% CI 1.3-6.2) and deoxygenation (OR 2.9, 95% CI 1.3-7.6). At 6 months, the mortality risk was 2.1 (95% CI 1.3-3.7). Risk factors for 6-month mortality were shortness of breath (OR 2.7, 95% CI 1.3-7.0), deoxygenation (OR 2.5, 95% CI 1.1-6.5) and medical management (OR 4.5, 95% CI 1.7-25.8). However, among patients who survived COVID-19 infection, the long-term mortality risk was not sustained (OR 1.0, 95% CI 0.4-2.7). CONCLUSIONS AND IMPLICATIONS: Overall, COVID-19 infection increases short- and long-term mortality risk among nursing home patients. However, this study shows that surviving COVID-19 infection does not lead to increased mortality in the long term within this population. Therefore, advanced care planning should focus on quality of life among nursing home patients after COVID-19 infection.

The costs of HIV treatment and care in Ghana.

OBJECTIVE: To determine cost functions that describe the dynamics of costs of HIV treatment and care in Ghana by CD4 cell count at treatment initiation and over time on antiretroviral therapy (ART). DESIGN: We used detailed longitudinal healthcare utilization data from clinical health records of HIV-infected patients at seven Ghanaian ART clinics to estimate cost functions of treatment and care by CD4 cell count at treatment initiation and time on ART. METHODS: We developed two linear regression models; one with individual random effects to determine the relationship between CD4 cell count at ART initiation and costs of treatment and care, and one with individual fixed effects to determine the causal effect of time in care on costs of treatment and care. RESULTS: Costs for treatment and care were lowest (-7.9 US$) for patients with CD4 cell counts of at least 350 cells/µl at ART initiation, compared with patients with 50 cells/µl or less at ART initiation, yet the difference was not significant. The per-patient costs peaked during the first 6 months on ART at 112.6 US$, and significantly decreased by 70% after 4 years on treatment. CONCLUSION: Our findings show that an accurate analysis of resource needs of HIV treatment and care should take into account that healthcare costs for HIV-infected people are dynamic rather than constant. The cost functions derived from our study are valuable input for cost-effectiveness analyses and research allocation exercises for HIV treatment in sub-Saharan Africa.