BACKGROUND
Physical frailty is a powerful tool for identifying nondisabled individuals at high risk of adverse outcomes. The extent to which cognitive impairment in those without dementia adds value ...to physical frailty in detecting high‐risk individuals remains unclear.
OBJECTIVES
To estimate the effects of combining physical frailty and cognitive impairment without dementia (CIND) on the risk of basic activities of daily living (ADL) dependence and death over 8 years.
DESIGN
Prospective cohort study.
SETTING
The Health and Retirement Study (HRS).
PARTICIPANTS
A total of 7338 community‐dwelling people, 65 years or older, without dementia and ADL dependence at baseline (2006‐2008). Follow‐up assessments occurred every 2 years until 2014.
MEASUREMENTS
The five components of the Cardiovascular Health Study defined physical frailty. A well‐validated HRS method, including verbal recall, series of subtractions, and backward count task, assessed cognition. Primary outcomes were time to ADL dependence and death. Hazard models, considering death as a competing risk, associated physical frailty and CIND with outcomes after adjusting for sociodemographics, comorbidities, depression, and smoking status.
RESULTS
The prevalence of physical frailty was 15%; CIND, 19%; and both deficits, 5%. In unadjusted and adjusted analyses, combining these factors identified older adults at an escalating risk for ADL dependence (no deficit = 14% reference group; only CIND = 26%, sub–hazard ratio sHR = 1.5, 95% confidence interval CI = 1.3–1.8; only frail = 33%, sHR = 1.7, 95% CI = 1.4–2.0; both deficits = 46%, sHR = 2.0, 95%CI = 1.6–2.6) and death (no deficit = 21%; only CIND = 41%, HR = 1.6, 95% CI = 1.4–1.9; only frail = 56%, HR = 2.2, 95% CI = 1.7–2.7; both deficits = 66%, HR = 2.6, 95% CI = 2.0–3.3) over 8‐year follow‐up. Adding the cognitive measure to models that already included physical frailty alone increased accuracy in identifying those at higher risk of ADL dependence (Harrell's concordance C, 0.74 vs 0.71; P < .001) and death (Harrell's C, 0.70 vs 0.67; P < .001).
CONCLUSION
Physical frailty and CIND are independent predictors of incident disability and death. Because together physical frailty and CIND identify vulnerable older adults better, optimal risk assessment should supplement measures of physical frailty with measures of cognitive function. J Am Geriatr Soc 67:477–483, 2019.
...we reported categorical variables as count and percentage and interval variables as median and interquartile range (IQR) or mean and standard deviation (SD). ...we compared characteristics and ...outcomes between cases and controls using the Fisher exact test for categorical variables and Mann−Whitney test or independent samples t-test for the interval variables. ...despite considering comprehensive patient information, we could not obtain detailed data on some variables (e.g., the level of function before SARS-CoV-2 infection, complications in acute hospitals and vaccination status), a common limitation in retrospective studies. ...our study highlights the effectiveness of postacute intensive rehabilitation for severe COVID-19 patients, as it shows improved outcomes compared to those with
Current recommendations to assess sarcopenia requiring specialized equipment hinder its use as a prognostic tool in busy acute settings.
To investigate the prognostic value of a rapid sarcopenia ...measure in acutely ill older outpatients for 1-year adverse outcomes.
Prospective study with 665 acutely ill older adults (mean age 78.7 ± 8.3 years; 63% women) in need of intensive management to avoid hospital admission. Sarcopenia was screened upon admission, defined as the presence of both low muscle strength and low muscle mass. Low muscle strength was determined by handgrip strength according to the cutoffs of the Foundation for the National Institutes of Health (<16 kg for women and <26 kg for men). Low muscle mass was assessed by calf circumference, a validated surrogate measure of skeletal muscle mass, using previously established thresholds (≤33 cm for women and ≤34 cm for men). Outcomes were time to hospitalization, new dependence in basic activities of daily living (ADL), worsening walking ability, and death. To investigate the association of sarcopenia and its components with outcomes we used hazard models, considering death as a competing risk, adjusted for sociodemographic factors, Charlson comorbidity index, cognitive impairment, depressive symptoms, and weight loss.
On admission, 203 (31%) patients had sarcopenia. Comparing 1-year adverse outcomes between older adults with and without sarcopenia, respectively, cumulative incidences for hospitalization were 46% vs 32% (adjusted sub-hazard ratio sHR = 1.53; 95% CI = 1.16–2.04), for new ADL dependence, 47% vs 24% (adjusted sHR = 1.78; 95% CI = 1.31–2.42), for worsening walking ability, 28% vs 13% (adjusted sHR = 1.93; 95% CI = 1.28–2.90), and for death, 22% vs 10% (adjusted HR = 1.69; 95% CI = 1.05–2.73). Low muscle strength alone was associated with all outcomes, and low muscle mass was associated with all outcomes except mortality.
Sarcopenia was a strong predictor of 1-year adverse outcomes among acutely ill older outpatients. Combining handgrip strength with calf circumference may be a practical and efficient approach to screen for sarcopenia, and thereby identify high-risk older adults in busy clinical settings.
•Sarcopenia can identify older people at risk of poor outcomes.•Time pressure and few resources hinder the assess of sarcopenia in busy settings.•Grip strength and calf circumference are measures quickly assessed in busy settings.•Handgrip strength and calf circumference captures the key elements of sarcopenia.•This practical sarcopenia screening predicts poor outcomes after acute care.
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.
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).
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.
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% (
= 0.012 for trend) at the end of 1 year. Clinical events occurred in all assessments.
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.
Objectives
To estimate whether a 10-minute Targeted Geriatric Assessment (10-TaGA) adds utility to sociodemographic characteristics and comorbidities in predicting one-year mortality in busy acute ...care settings. We have also compared the performance of 10-TaGA with the Identification of Seniors at Risk (ISAR) scale.
Design
Prospective cohort study.
Setting
Geriatric day hospital specializing in acute care in Brazil
Participants
751 older adults aged 79.4 ± 8.4 years (64% female), presenting non-surgical, medical illness requiring hospital-level care (e.g., intravenous therapy, laboratory test, radiology) for ≤ 12 hours.
Measurements
The 10-TaGA, an easy-to-administer screening tool based on the comprehensive geriatric assessment (CGA), provided a measure of cumulative deficits ranging from 0 (no deficits) to 1 (highest deficit) on admission. Standard risk factors, including sociodemographics (age, gender, ethnicity, income) and the Charlson comorbidity index, were evaluated. The ISAR, a well-validated screening tool, was used for comparison.
Results
During one year of follow-up, 130 (17%) participants died. Compared to the ISAR, 10-TaGA offered better accuracy in identifying older patients at risk of death (area under the receiver operating characteristic curve: AUC 0.70 vs 0.65; P = 0.03). In a Cox regression model adjusted for sociodemographics and comorbidities, each 0.1 increment in the 10-TaGA score (range 0–1) was associated with increased mortality (hazard ratio = 1.42, 95% confidence interval 1.27–1.59). The addition of 10-TaGA markedly improved the discrimination of the model, which already incorporated standard risk factors (AUC 0.76 vs 0.71; P = 0.005); adding ISAR (AUC 0.73 vs 0.71; P = 0.09) did not have this marked effect.
Conclusion
The 10-TaGA is an independent predictor of one-year mortality in acute care patients. This multidimensional screening tool offers better accuracy than ISAR when differentiating between older people at low and high risk of death in healthcare settings where providers have limited time and resources.
Objectives
We investigated functional trajectories after severe COVID-19 and estimated their associations with adverse outcomes (falls, rehospitalizations, institutionalization, or death), cognition ...and post COVID-19 condition within 1-year of hospital discharge.
Design
Prospective cohort study.
Setting
A large academic medical center in Sao Paulo, Brazil.
Participants
Survivors of COVID-19 admissions to an intensive care unit.
Interventions
None.
Measurements
We evaluated participants’ disability status before hospital admission and three, six, nine, and twelve months after discharge using 15 activities of daily living. During follow-up, cognition and post COVID-19 condition (defined as persistent symptoms with duration ≥2 months) were assessed. A latent class growth analysis was performed to investigate functional trajectories after discharge.
Results
We included 422 participants (median age 63 years, 13.5% were frail before COVID-19). Four distinct functional trajectories could be identified: “minimal disability trajectory” (37.4% of participants), “mild disability trajectory” (37.9%), “moderate disability trajectory” (16.8%), and “severe disability trajectory” (7.8%). Compared with minimal disability trajectory, the odds ratios (95% confidence interval) for 1-year adverse outcomes were 2.28 (1.38–3.76) for minor disability trajectory; 4.21 (2.10–8.42) for moderate disability trajectory; and 4.16 (1.51–11.46) for severe disability trajectory, even after adjustments. The occurrence of post COVID-19 condition was 67.5% and associated with functional trajectories (p=0.004). Cognition was also associated with functional trajectories.
Conclusion
Severe COVID-19 survivors can experience diverse functional trajectories, with those presenting higher levels of disability at increased risk for long-term adverse outcomes. Further investigations are essential to confirm our findings and assess the effectiveness of rehabilitation interventions, aiming to improve health outcomes in those who survived severe COVID-19 and other causes of sepsis.
Guidelines recommend using clinical prediction models to identify patients most likely to benefit from medical procedures and treatments.1 However, a common barrier to their use is when items ...required to complete a prediction model are unknown or do not match the available information.2 This might occur when a clinician runs the model from a medical record before seeing the patient, does not obtain specific information for the model while in the examination room, or does not have access to laboratory values.3 In such scenarios, the clinician would be forced to either “make up” a value for the predictor, return to the room to ask the patient—often impractical—or not use the prediction model.2 An alternative approach is to anticipate the possibility of unavailable predictors, examine all possible combinations of available predictors, and “pre-estimate” all subset models. This strategy could be integrated into web-based calculators designed to offer prognostic estimates for clinicians.1 To test this approach, we use the example of the previously validated Lee prognostic index for 10-year mortality and compare the performance of the full 12-item Lee index to all possible combinations of the model where up to three items are unavailable.4
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