COVID-19 outcomes in people living with HIV: peering through the waves

Objective To evaluate clinical characteristics and outcomes of COVID-19 patients infected with HIV, and to compare with a paired sample without HIV infection. Methods This is a substudy of a Brazilian multicentric cohort that comprised two periods (2020 and 2021). Data was obtained through the retrospective review of medical records. Primary outcomes were admission to the intensive care unit, invasive mechanical ventilation, and death. Patients with HIV and controls were matched for age, sex, number of comorbidities, and hospital of origin using the technique of propensity score matching (up to 4:1). They were compared using the Chi-Square or Fisher's Exact tests for categorical variables and the Wilcoxon for numerical variables. Results Throughout the study, 17,101 COVID-19 patients were hospitalized, and 130 (0.76%) of those were infected with HIV. The median age was 54 (IQR: 43.0;64.0) years in 2020 and 53 (IQR: 46.0;63.5) years in 2021, with a predominance of females in both periods. People Living with HIV (PLHIV) and their controls showed similar prevalence for admission to the ICU and invasive mechanical ventilation requirement in the two periods, with no significant differences. In 2020, in-hospital mortality was higher in the PLHIV compared to the controls (27.9% vs. 17.7%;p = 0.049), but there was no difference in mortality between groups in 2021 (25.0% vs. 25.1%;p > 0.999). Conclusions Our results reiterate that PLHIV were at higher risk of COVID-19 mortality in the early stages of the pandemic, however, this finding did not sustain in 2021, when the mortality rate is similar to the control group.

COVID-19 outcomes in people living with HIV: Peering through the waves.

OBJECTIVE: To evaluate clinical characteristics and outcomes of COVID-19 patients infected with HIV, and to compare with a paired sample without HIV infection. METHODS: This is a substudy of a Brazilian multicentric cohort that comprised two periods (2020 and 2021). Data was obtained through the retrospective review of medical records. Primary outcomes were admission to the intensive care unit, invasive mechanical ventilation, and death. Patients with HIV and controls were matched for age, sex, number of comorbidities, and hospital of origin using the technique of propensity score matching (up to 4:1). They were compared using the Chi-Square or Fisher's Exact tests for categorical variables and the Wilcoxon for numerical variables. RESULTS: Throughout the study, 17,101 COVID-19 patients were hospitalized, and 130 (0.76%) of those were infected with HIV. The median age was 54 (IQR: 43.0;64.0) years in 2020 and 53 (IQR: 46.0;63.5) years in 2021, with a predominance of females in both periods. People Living with HIV (PLHIV) and their controls showed similar prevalence for admission to the ICU and invasive mechanical ventilation requirement in the two periods, with no significant differences. In 2020, in-hospital mortality was higher in the PLHIV compared to the controls (27.9% vs. 17.7%; p = 0.049), but there was no difference in mortality between groups in 2021 (25.0% vs. 25.1%; p > 0.999). CONCLUSIONS: Our results reiterate that PLHIV were at higher risk of COVID-19 mortality in the early stages of the pandemic, however, this finding did not sustain in 2021, when the mortality rate is similar to the control group.

Dissipating the fog: Cognitive trajectories and risk factors 1 year after COVID-19 hospitalization.

INTRODUCTION: Cognitive impairment is common after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, associations between post-hospital discharge risk factors and cognitive trajectories have not been explored. METHODS: A total of 1105 adults (mean age ± SD 64.9 ± 9.9 years, 44% women, 63% White) with severe coronavirus disease 2019 (COVID-19) were evaluated for cognitive function 1 year after hospital discharge. Scores from cognitive tests were harmonized, and clusters of cognitive impairment were defined using sequential analysis. RESULTS: Three groups of cognitive trajectories were observed during the follow-up: no cognitive impairment, initial short-term cognitive impairment, and long-term cognitive impairment. Predictors of cognitive decline after COVID-19 were older age (ß = -0.013, 95% CI = -0.023;-0.003), female sex (ß = -0.230, 95% CI = -0.413;-0.047), previous dementia diagnosis or substantial memory complaints (ß = -0.606, 95% CI = -0.877;-0.335), frailty before hospitalization (ß = -0.191, 95% CI = -0.264;-0.119), higher platelet count (ß = -0.101, 95% CI = -0.185;-0.018), and delirium (ß = -0.483, 95% CI = -0.724;-0.244). Post-discharge predictors included hospital readmissions and frailty. DISCUSSION: Cognitive impairment was common and the patterns of cognitive trajectories depended on sociodemographic, in-hospital, and post-hospitalization predictors. HIGHLIGHTS: Cognitive impairment after coronavirus disease 2019 (COVID-19) hospital discharge was associated with higher age, less education, delirium during hospitalization, a higher number of hospitalizations post discharge, and frailty before and after hospitalization. Frequent cognitive evaluations for 12-month post-COVID-19 hospitalization showed three possible cognitive trajectories: no cognitive impairment, initial short-term impairment, and long-term impairment. This study highlights the importance of frequent cognitive testing to determine patterns of COVID-19 cognitive impairment, given the high frequency of incident cognitive impairment 1 year after hospitalization.

Development and validation of the MMCD score to predict kidney replacement therapy in COVID-19 patients.

BACKGROUND: Acute kidney injury (AKI) is frequently associated with COVID-19, and the need for kidney replacement therapy (KRT) is considered an indicator of disease severity. This study aimed to develop a prognostic score for predicting the need for KRT in hospitalised COVID-19 patients, and to assess the incidence of AKI and KRT requirement. METHODS: This study is part of a multicentre cohort, the Brazilian COVID-19 Registry. A total of 5212 adult COVID-19 patients were included between March/2020 and September/2020. Variable selection was performed using generalised additive models (GAM), and least absolute shrinkage and selection operator (LASSO) regression was used for score derivation. Accuracy was assessed using the area under the receiver operating characteristic curve (AUC-ROC). RESULTS: The median age of the model-derivation cohort was 59 (IQR 47-70) years, 54.5% were men, 34.3% required ICU admission, 20.9% evolved with AKI, 9.3% required KRT, and 15.1% died during hospitalisation. The temporal validation cohort had similar age, sex, ICU admission, AKI, required KRT distribution and in-hospital mortality. The geographic validation cohort had similar age and sex; however, this cohort had higher rates of ICU admission, AKI, need for KRT and in-hospital mortality. Four predictors of the need for KRT were identified using GAM: need for mechanical ventilation, male sex, higher creatinine at hospital presentation and diabetes. The MMCD score had excellent discrimination in derivation (AUROC 0.929, 95% CI 0.918-0.939) and validation (temporal AUROC 0.927, 95% CI 0.911-0.941; geographic AUROC 0.819, 95% CI 0.792-0.845) cohorts and good overall performance (Brier score: 0.057, 0.056 and 0.122, respectively). The score is implemented in a freely available online risk calculator ( https://www.mmcdscore.com/ ). CONCLUSIONS: The use of the MMCD score to predict the need for KRT may assist healthcare workers in identifying hospitalised COVID-19 patients who may require more intensive monitoring, and can be useful for resource allocation.

Association of Frailty, Organ Support, and Long-Term Survival in Critically Ill Patients With COVID-19

OBJECTIVES: Few studies have explored the effect of frailty on the long-term survival of COVID-19 patients after ICU admission. Furthermore, the Clinical Frailty Scale (CFS) validity in critical care patients remains debated. We investigated the association between frailty and 6-month survival in critically ill COVID-19 patients. We also explored whether ICU resource utilization varied according to frailty status and examined the concurrent validity of the CFS in this setting. DESIGN: Ancillary study of a longitudinal prospective cohort. SETTING: University hospital in São Paulo. PATIENTS: Patients with severe COVID-19 admitted to ICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We assessed baseline frailty using the CFS (1–9;frail ≥ 5) and used validated procedures to compute a Frailty Index (0–1;frail > 0.25). We used Cox models to estimate associations of frailty status with 6-month survival after ICU admission and area under the receiver operating characteristic curves (AUCs) to estimate CFS’s accuracy in identifying frailty according to Frailty Index. We included 1,028 patients (mean age, 66 yr;male, 61%). Overall, 224 (22%) patients were frail (CFS ≥ 5), and 608 (59%) died over the 6-month follow-up. Frailty was independently associated with lower 6-month survival and further stratified mortality in patients with similar age and Sequential Organ Failure Assessment scores. We additionally verified that the CFS was highly accurate in identifying frailty as defined by the Frailty Index (AUC, 0.91;95% CI, 0.89–0.93). Although treatment modalities did not diverge according to frailty status, higher CFS scores were associated with withholding organ support due to refractory organ failure. CONCLUSIONS: One in five COVID-19 patients admitted to the ICU was frail. CFS scores greater than or equal to 5 were associated with lower long-term survival and decisions on withholding further escalation of invasive support for multiple organ failure in the ICU. Clinicians should consider frailty alongside sociodemographic and clinical measures to have a fuller picture of COVID-19 prognosis in critical care.

Patient-Centered Outcomes Following COVID-19: Frailty and Disability Transitions in Critical Care Survivors.

OBJECTIVES: As the pandemic advances, the interest in the long-lasting consequences of COVID-19 increases. However, a few studies have explored patient-centered outcomes in critical care survivors. We aimed to investigate frailty and disability transitions in COVID-19 patients admitted to ICUs. DESIGN: Prospective cohort study. SETTING: University hospital in Sao Paulo. PATIENTS: Survivors of COVID-19 ICU admissions. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We assessed frailty using the Clinical Frailty Scale (CFS). We also evaluated 15 basic, instrumental, and mobility activities. Baseline frailty and disability were defined by clinical conditions 2-4 weeks before COVID-19, and post-COVID-19 was characterized 90 days (day 90) after hospital discharge. We used alluvial flow diagrams to visualize transitions in frailty status, Venn diagrams to describe the overlap between frailty and disabilities in activities of daily living, and linear mixed models to explore the occurrence of new disabilities following critical care in COVID-19. We included 428 participants with a mean age of 64 years, 57% males, and a median Simplified Acute Physiology Score-3 score of 59. Overall, 14% were frail at baseline. We found that 124/394 participants (31%) were frail at day 90, 70% of whom were previously non-frail. The number of disabilities also increased (mean difference, 2.46; 95% CI, 2.06-2.86), mainly in participants who were non-frail before COVID-19. Higher pre-COVID-19 CFS scores were independently associated with new-onset disabilities. At day 90, 135 patients (34%) were either frail or disabled. CONCLUSIONS: Frailty and disability were more frequent 90 days after hospital discharge compared with baseline in COVID-19 patients admitted to the ICU. Our results show that most COVID-19 critical care survivors transition to poorer health status, highlighting the importance of long-term medical follow-up for this population.

Characteristics and Outcomes of Patients With Frailty Admitted to ICU With Coronavirus Disease 2019: An Individual Patient Data Meta-Analysis.

Frailty is often used in clinical decision-making for patients with coronavirus disease 2019, yet studies have found a variable influence of frailty on outcomes in those admitted to the ICU. In this individual patient data meta-analysis, we evaluated the characteristics and outcomes across the range of frailty in patients admitted to ICU with coronavirus disease 2019. DATA SOURCES: We contacted the corresponding authors of 16 eligible studies published between December 1, 2019, and February 28, 2021, reporting on patients with confirmed coronavirus disease 2019 admitted to ICU with a documented Clinical Frailty Scale. STUDY SELECTION: Individual patient data were obtained from seven studies with documented Clinical Frailty Scale were included. We classified patients as nonfrail (Clinical Frailty Scale = 1-4) or frail (Clinical Frailty Scale = 5-8). DATA EXTRACTION: We collected patient demographics, Clinical Frailty Scale score, ICU organ supports, and clinically relevant outcomes (ICU and hospital mortality, ICU and hospital length of stays, and discharge destination). The primary outcome was hospital mortality. DATA SYNTHESIS: Of the 2,001 patients admitted to ICU, 388 (19.4%) were frail. Increasing age and Sequential Organ Failure Assessment score, Clinical Frailty Scale score greater than or equal to 4, use of mechanical ventilation, vasopressors, renal replacement therapy, and hyperlactatemia were risk factors for death in a multivariable analysis. Hospital mortality was higher in patients with frailty (65.2% vs 41.8%; p < 0.001), with adjusted mortality increasing with a rising Clinical Frailty Scale score beyond 3. Younger and nonfrail patients were more likely to receive mechanical ventilation. Patients with frailty spent less time on mechanical ventilation (median days [interquartile range], 9 [5-16] vs 11 d [6-18 d]; p = 0.012) and accounted for only 12.3% of total ICU bed days. CONCLUSIONS: Patients with frailty with coronavirus disease 2019 were commonly admitted to ICU and had greater hospital mortality but spent relatively fewer days in ICU when compared with nonfrail patients. Patients with frailty receiving mechanical ventilation were at greater risk of death than patients without frailty.

COVID-19 is not over and age is not enough: Using frailty for prognostication in hospitalized patients.

BACKGROUND: Frailty screening using the Clinical Frailty Scale (CFS) has been proposed to guide resource allocation in acute care settings during the pandemic. However, the association between frailty and coronavirus disease 2019 (COVID-19) prognosis remains unclear. OBJECTIVES: To investigate the association between frailty and mortality over 6 months in middle-aged and older patients hospitalized with COVID-19 and the association between acute morbidity severity and mortality across frailty strata. DESIGN: Observational cohort study. SETTING: Large academic medical center in Brazil. PARTICIPANTS: A total of 1830 patients aged ≥50 years hospitalized with COVID-19 (March-July 2020). MEASUREMENTS: We screened baseline frailty using the CFS (1-9) and classified patients as fit to managing well (1-3), vulnerable (4), mildly (5), moderately (6), or severely frail to terminally ill (7-9). We also computed a frailty index (0-1; frail >0.25), a well-known frailty measure. We used Cox proportional hazards models to estimate the association between frailty and time to death within 30 days and 6 months of admission. We also examined whether frailty identified different mortality risk levels within strata of similar age and acute morbidity as measured by the Sequential Organ Failure Assessment (SOFA) score. RESULTS: Median age was 66 years, 58% were male, and 27% were frail to some degree. Compared with fit-to-managing-well patients, the adjusted hazard ratios (95% confidence interval [CI]) for 30-day and 6-month mortality were, respectively, 1.4 (1.1-1.7) and 1.4 (1.1-1.7) for vulnerable patients; 1.5 (1.1-1.9) and 1.5 (1.1-1.8) for mild frailty; 1.8 (1.4-2.3) and 1.9 (1.5-2.4) for moderate frailty; and 2.1 (1.6-2.7) and 2.3 (1.8-2.9) for severe frailty to terminally ill. The CFS achieved outstanding accuracy to identify frailty compared with the Frailty Index (area under the curve = 0.94; 95% CI = 0.93-0.95) and predicted different mortality risks within age and acute morbidity groups. CONCLUSIONS: Our results encourage the use of frailty, alongside measures of acute morbidity, to guide clinicians in prognostication and resource allocation in hospitalized patients with COVID-19.

Divergent: Age, Frailty, and Atypical Presentations of COVID-19 in Hospitalized Patients.

BACKGROUND: Although frailty has been associated with atypical manifestations of infections, little is known about COVID-19 presentations in hospitalized frail patients. We aimed to investigate the association between age, frailty, and clinical characteristics of COVID-19 in hospitalized middle-aged and older adults. METHOD: Longitudinal observational study comprising 711 patients aged ≥50 years consecutively admitted to a university hospital dedicated to COVID-19 severe cases, between March and May 2020. We reviewed electronic medical records to collect data on demographics, comorbidities, COVID-19 signs/symptoms, and laboratory findings on admission. We defined frailty using the Clinical Frailty Scale (CFS = 1-9; frail ≥5). We also documented in-hospital mortality. We used logistic regressions to explore associations between age, frailty, and COVID-19 signs/symptoms; and between typical symptoms (fever, cough, dyspnea) and mortality. RESULTS: Participants had a mean age of 66 ± 11 years, and 43% were female. Overall, 25% were frail, and 37% died. The most common COVID-19 presentations were dyspnea (79%), cough (74%), and fever (62%), but patients aged ≥65 years were less likely to have a co-occurrence of typical symptoms, both in the absence (OR = 0.56; 95% CI = 0.39-0.79) and in the presence of frailty (OR = 0.52; 95% CI = 0.34-0.81). In contrast, older age and frailty were associated with unspecific presentations, including functional decline, acute mental change, and hypotension. After adjusting for age, sex, and frailty, reporting fever was associated with lower odds of mortality (OR = 0.70; 95% CI = 0.50-0.97). CONCLUSIONS: Atypical COVID-19 presentations are common in frail and older hospitalized patients. Providers should be aware of unspecific disease manifestations during the management and follow-up of this population.

A fuller picture of COVID-19 prognosis: the added value of vulnerability measures to predict mortality in hospitalised older adults.

BACKGROUND: Although coronavirus disease 2019 (COVID-19) disproportionally affects older adults, the use of conventional triage tools in acute care settings ignores the key aspects of vulnerability. OBJECTIVE: This study aimed to determine the usefulness of adding a rapid vulnerability screening to an illness acuity tool to predict mortality in hospitalised COVID-19 patients. DESIGN: Cohort study. SETTING: Large university hospital dedicated to providing COVID-19 care. PARTICIPANTS: Participants included are 1,428 consecutive inpatients aged ≥50 years. METHODS: Vulnerability was assessed using the modified version of PRO-AGE score (0-7; higher = worse), a validated and easy-to-administer tool that rates physical impairment, recent hospitalisation, acute mental change, weight loss and fatigue. The baseline covariates included age, sex, Charlson comorbidity score and the National Early Warning Score (NEWS), a well-known illness acuity tool. Our outcome was time-to-death within 60 days of admission. RESULTS: The patients had a median age of 66 years, and 58% were male. The incidence of 60-day mortality ranged from 22% to 69% across the quartiles of modified PRO-AGE. In adjusted analysis, compared with modified PRO-AGE scores 0-1 ('lowest quartile'), the hazard ratios (95% confidence interval) for 60-day mortality for modified PRO-AGE scores 2-3, 4 and 5-7 were 1.4 (1.1-1.9), 2.0 (1.5-2.7) and 2.8 (2.1-3.8), respectively. The modified PRO-AGE predicted different mortality risk levels within each stratum of NEWS and improved the discrimination of mortality prediction models. CONCLUSIONS: Adding vulnerability to illness acuity improved accuracy of predicting mortality in hospitalised COVID-19 patients. Combining tools such as PRO-AGE and NEWS may help stratify the risk of mortality from COVID-19.