Predicting posthospitalization falls in Brazilian older adults: External validation of the Carpenter instrument.

OBJECTIVES: This study sought to explore and externally validate the Carpenter instrument's efficacy in predicting postdischarge fall risk among older adults admitted to the emergency department (ED) for reasons other than falls or related injuries. METHODS: A prospective cohort study was conducted on 779 patients aged ≥ 65 years from a tertiary hospital in São Paulo, Brazil, who were monitored for up to 6 months post-ED hospitalization. The Carpenter instrument, which evaluates the four risk factors nonhealing foot sores, self-reported depression, inability to self-clip toenails, and prior falls, was utilized to assess fall risk. Follow-up by telephone occurred at 30, 90, and 180 days to identify falls and mortality. Fine-Gray models estimated the predictive power of Carpenter instrument for future falls, considering death as a competing event and sociodemographic factors, frail status, and clinical measures as confounders. RESULTS: Among 779 patients, 68 (9%) experienced a fall within 180 days post-ED admission, and 88 (11%) died. The majority were male (54%), with a mean age of 79 years. Upon utilizing the Carpenter score, those with a higher fall risk (≥2 points) displayed more comorbidities, greater frailty, and increased clinical severity at baseline. Regression analyses showed that every additional point on the Carpenter score increased the hazard of falls by 73%. Two primary contributors to its predictive potential were identified: a history of falls in the preceding year and an inability to self-clip toenails. However, the instrument's discriminative accuracy was suboptimal, with an area under the curve of 0.62. CONCLUSIONS: While the Carpenter instrument associated with a higher 6-month postadmission fall risk among older adults post-ED visit, its accuracy for individual patient decision making was limited. Given the significant impact of falls on health outcomes and health care costs, refining risk assessment tools remains essential. Future research should focus on enhancing these assessments and devising targeted proactive strategies.

Gut microbiota disturbances in hospitalized older adults with malnutrition and clinical outcomes.

OBJECTIVE: Malnutrition is one of the most threatening conditions in geriatric populations. The gut microbiota has an important role in the host's metabolic and muscular health: however, its interplay with disease-related malnutrition is not well understood. We aimed to identify the association of malnutrition with the gut microbiota and predict clinical outcomes in hospitalized acutely ill older adults. METHODS: We performed a secondary longitudinal analysis in 108 geriatric patients from a prospective cohort evaluated at admission and 72 h of hospitalization. We collected clinical, demographic, nutritional, and 16S rRNA gene-sequenced gut microbiota data. Microbiota diversity, overall composition, and differential abundance were calculated and compared between patients with and without malnutrition. Microbiota features associated with malnutrition were used to predict clinical outcomes. RESULTS: Patients with malnutrition (51%) had a different microbiota composition compared to those who were well-nourished during hospitalization (ANOSIM R = 0.079, P = 0.003). Patients with severe malnutrition showed poorer α-diversity at admission (Shannon P = 0.012, Simpson P = 0.018) and follow-up (Shannon P = 0.023, Chao1 P = 0.008). Differential abundance of Lachnospiraceae NK4A136 group, Subdoligranulum, and Faecalibacterium prausnitzii were significantly lower and inversely associated with malnutrition, while Corynebacterium, Ruminococcaceae Incertae Sedis, and Fusobacterium were significantly increased and positively associated with malnutrition. Corynebacterium, Ruminococcaceae Incertae Sedis, and the overall composition were important predictors of critical care in patients with malnutrition during hospitalization. CONCLUSION: Older adults with malnutrition, especially in a severe stage, may be subject to substantial gut microbial disturbances during hospitalization. The gut microbiota profile of patients with malnutrition might help us to predict worse clinical outcomes.

Delirium detection tools show varying completion rates and positive score rates when used at scale in routine practice in general hospital settings: A systematic review.

BACKGROUND: Multiple short delirium detection tools have been validated in research studies and implemented in routine care, but there has been little study of these tools in real-world conditions. This systematic review synthesized literature reporting completion rates and/or delirium positive score rates of detection tools in large clinical populations in general hospital settings. METHODS: PROSPERO (CRD42022385166). Medline, Embase, PsycINFO, CINAHL, and gray literature were searched from 1980 to December 31, 2022. Included studies or audit reports used a validated delirium detection tool performed directly with the patient as part of routine care in large clinical populations (n ≥ 1000) within a general acute hospital setting. Narrative synthesis was performed. RESULTS: Twenty-two research studies and four audit reports were included. Tools used alone or in combination were the Confusion Assessment Method (CAM), 4 'A's Test (4AT), Delirium Observation Screening Scale (DOSS), Brief CAM (bCAM), Nursing Delirium Screening Scale (NuDESC), and Intensive Care Delirium Screening Checklist (ICDSC). Populations and settings varied and tools were used at different stages and frequencies in the patient journey, including on admission only; inpatient, daily or more frequently; on admission and as inpatient; inpatient post-operatively. Tool completion rates ranged from 19% to 100%. Admission positive score rates ranged from: CAM 8%-51%; 4AT 13%-20%. Inpatient positive score rates ranged from: CAM 2%-20%, DOSS 6%-42%, and NuDESC 5-13%. Postoperative positive score rates were 21% and 28% (4AT). All but two studies had moderate-high risk of bias. CONCLUSIONS: This systematic review of delirium detection tool implementation in large acute patient populations found clinically important variability in tool completion rates, and in delirium positive score rates relative to expected delirium prevalence. This study highlights a need for greater reporting and analysis of relevant healthcare systems data. This is vital to advance understanding of effective delirium detection in routine care.

The pervasive association between political ideology and COVID-19 vaccine uptake in Brazil: an ecologic study.

BACKGROUND: Despite the unequivocal benefits of vaccination, vaccine coverage has been falling in several countries in the past few years. Studies suggest that vaccine hesitancy is an increasingly significant phenomenon affecting adherence to vaccines. More recently, during the COVID-19 pandemic, political views have emerged as an additional influencing factor for vaccine hesitancy. METHODS: In this ecologic study, we used information from publicly available databases to investigate the association between political ideology, depicted by the percentage of votes for the right-wing candidate Jair Bolsonaro in the presidential elections of 2018 and 2022, and COVID-19 vaccination in Brazilian municipalities. The primary endpoint was the COVID-19 vaccination index, calculated as the number of COVID-19 vaccine doses administered up to September 2022 divided by the number of inhabitants in each municipality. The analysis was conducted using Pearson correlation coefficients and linear regression models adjusted for HDI, the percentage of male voters, the percentage of voters who were older than 50 years old, and the percentage of voters with a middle school education or less. In addition, we explored whether the effect of the percentage of Bolsonaro voters on the COVID-19 vaccination index was modified in different quartiles of HDI using an interaction term. RESULTS: Five thousand five hundred sixty-three Brazilian municipalities were included in the analysis. For both the 2018 and 2022 elections, the percentage of votes for Jair Bolsonaro was significantly and inversely associated with COVID-19 vaccine uptake after adjustment for the sociodemographic characteristics of the voters (change in mean vaccination index in 2018 for each 1% increase in Bolsonaro voters -0.11, 95% confidence interval [CI] -0.13 to -0.08, p < 0.001; change in mean vaccination index in 2022 for each 1% increase in Bolsonaro voters -0.09, 95% CI -0.11 to -0.07, p < 0.001). We also found a statistically significant interaction between the primary predictor of interest and HDI scores, with a more significantly detrimental effect of the right-wing political stance in municipalities in the lower HDI quartiles (interaction p < 0.001 for the first HDI quartile; p = 0.001 for the second HDI quartile). CONCLUSION: Our findings suggest that political ideologies have influenced COVID-19 vaccine hesitancy in Brazilian municipalities, affecting communities inequitably. The politicization of vaccines is a new challenge for vaccine programs. Strategies to face these challenges should include joint efforts from governments and civil society for a common public health goal.

Prediction of intensive care admission and hospital mortality in COVID-19 patients using demographics and baseline laboratory data.

INTRODUCTION: Optimized allocation of medical resources to patients with COVID-19 has been a critical concern since the onset of the pandemic. METHODS: In this retrospective cohort study, the authors used data from a Brazilian tertiary university hospital to explore predictors of Intensive Care Unit (ICU) admission and hospital mortality in patients admitted for COVID-19. Our primary aim was to create and validate prediction scores for use in hospitals and emergency departments to aid clinical decisions and resource allocation. RESULTS: The study cohort included 3,022 participants, of whom 2,485 were admitted to the ICU; 1968 survived, and 1054 died in the hospital. From the complete cohort, 1,496 patients were randomly assigned to the derivation sample and 1,526 to the validation sample. The final scores included age, comorbidities, and baseline laboratory data. The areas under the receiver operating characteristic curves were very similar for the derivation and validation samples. Scores for ICU admission had a 75% accuracy in the validation sample, whereas scores for death had a 77% accuracy in the validation sample. The authors found that including baseline flu-like symptoms in the scores added no significant benefit to their accuracy. Furthermore, our scores were more accurate than the previously published NEWS-2 and 4C Mortality Scores. DISCUSSION AND CONCLUSIONS: The authors developed and validated prognostic scores that use readily available clinical and laboratory information to predict ICU admission and mortality in COVID-19. These scores can become valuable tools to support clinical decisions and improve the allocation of limited health resources.

Twelve Months and Counting: Following Clinical Outcomes in Critical COVID-19 Survivors.

Rationale: Recent reports suggest that patients with severe coronavirus disease (COVID-19) often experience long-term consequences of the infection. However, studies on intensive care unit (ICU) survivors are underrepresented. Objectives: We aimed to explore 12-month clinical outcomes after critical COVID-19, describing the longitudinal progress of disabilities, frailty status, frequency of cognitive impairment, and clinical events (rehospitalization, institutionalization, and falls). Methods: We performed a prospective cohort study of survivors of COVID-19 ICU admissions in Sao Paulo, Brazil. We assessed patients every 3 months for 1 year after hospital discharge and obtained information on 15 activities of daily living (basic, instrumental, and mobility activities), frailty, cognition, and clinical events. Results: We included 428 patients (mean age of 64 yr, 61% required invasive mechanical ventilation during ICU stay). The number of disabilities peaked at 3 months compared with the pre-COVID-19 period (mean difference, 2.46; 99% confidence interval, 1.94-2.99) and then decreased at 12 months (mean difference, 0.67; 99% confidence interval, 0.28-1.07). At 12-month follow-up, 12% of patients were frail, but half of them presented frailty only after COVID-19. The prevalence of cognitive symptoms was 17% at 3 months and progressively decreased to 12.1% (P = 0.012 for trend) at the end of 1 year. Clinical events occurred in all assessments. Conclusions: Although a higher burden of disabilities and cognitive symptoms occurred 3 months after hospital discharge of critical COVID-19 survivors, a significant improvement occurred during the 1-year follow-up. However, one-third of the patients remained in worse conditions than their pre-COVID-19 status.

Prediction of intensive care admission and hospital mortality in COVID-19 patients using demographics and baseline laboratory data

Abstract Introduction: Optimized allocation of medical resources to patients with COVID-19 has been a critical concern since the onset of the pandemic. Methods: In this retrospective cohort study, the authors used data from a Brazilian tertiary university hospital to explore predictors of Intensive Care Unit (ICU) admission and hospital mortality in patients admitted for COVID-19. Our primary aim was to create and validate prediction scores for use in hospitals and emergency departments to aid clinical decisions and resource allocation. Results: The study cohort included 3,022 participants, of whom 2,485 were admitted to the ICU; 1968 survived, and 1054 died in the hospital. From the complete cohort, 1,496 patients were randomly assigned to the derivation sample and 1,526 to the validation sample. The final scores included age, comorbidities, and baseline laboratory data. The areas under the receiver operating characteristic curves were very similar for the derivation and validation samples. Scores for ICU admission had a 75% accuracy in the validation sample, whereas scores for death had a 77% accuracy in the validation sample. The authors found that including baseline flu-like symptoms in the scores added no significant benefit to their accuracy. Furthermore, our scores were more accurate than the previously published NEWS-2 and 4C Mortality Scores. Discussion and conclusions: The authors developed and validated prognostic scores that use readily available clinical and laboratory information to predict ICU admission and mortality in COVID-19. These scores can become valuable tools to support clinical decisions and improve the allocation of limited health resources.

Palliative care in Hospitalized Middle-Aged and Older Adults With COVID-19.

CONTEXT: As COVID-19 overwhelms health systems worldwide, palliative care strategies may ensure rational use of resources while safeguarding patient comfort and dignity. OBJECTIVE: To describe palliative care practices in hospitalized middle-aged and older adults in two of the largest COVID-19 treatment centers in Sao Paulo, Brazil. METHODS: Retrospective cohort. Eligible patients were those aged 50 years or older hospitalized between March and May 2020 with a laboratory confirmation of SARS-CoV-2 infection. Palliative care implementation was defined as present if medical notes indicated a decision to limit escalation of life support measures, or when opioids or sedatives were prescribed for palliative management of symptoms. RESULTS: We included 1162 participants (57% male, median 65 years). Overall, 21% were frail and 54% were treated in intensive care units, but only 17% received palliative care. Stepwise logistic regression demonstrated that age ≥80 years, dementia, history of stroke or cancer, frailty, having a PaO2/FiO2<200 or a C-reactive protein ≥150mg/dL at admission predicted palliative care implementation. Patients placed under palliative care stayed longer (13 vs.11 days) and were more likely to die in hospital (86 vs.27%). They also spent more days in ICU and received vasoactive drugs, hemodialysis, and invasive ventilation more frequently. CONCLUSIONS: One in five middle-aged and older adults hospitalized with COVID-19 received palliative care in our cohort. Patients who were very old, multimorbid, frail, and had severe COVID-19 were more likely to receive palliative care. However, it was often delayed until advanced and invasive life support measures had already been implemented.

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.