ResearchPad - activities-of-daily-living Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Psychometric testing of the Fall Risks for Older People in the Community screening tool (FROP-Com screen) for community-dwelling people with stroke]]> The Falls Risk for Older People in the Community assessment (FROP-Com) was originally developed using 13 risk factors to identify the fall risks of community-dwelling older people. To suit the practical use in busy clinical settings, a brief version adopting 3 most fall predictive risk factors from the original FROP-Com, including the number of falls in the past 12 months, assistance required to perform domestic activities of daily living and observation of balance, was developed for screening purpose (FROP-Com screen). The objectives of this study were to investigate the inter-rater and test-retest reliability, concurrent and convergent validity, and minimum detectable change of the FROP-Com screen in community-dwelling people with stroke.ParticipantsCommunity-dwelling people with stroke (n = 48) were recruited from a local self-help group, and community-dwelling older people (n = 40) were recruited as control subjects.ResultsThe FROP-Com screen exhibited moderate inter-rater (Intraclass correlation coefficient [ICC]2,1 = 0.79, 95% confidence interval [CI]: 0.65–0.87) and test-retest reliability (ICC3,1 = 0.70, 95% CI: 0.46–0.83) and weak associations with two balance measures, the Berg Balance Scale (BBS) (rho = -0.38, p = 0.008) and the Timed “Up & Go” (TUG) test (rho = 0.35, p = 0.016). The screen also exhibited a moderate association with the Chinese version of the Activities-specific Balance Confidence Scale (ABC-C) (ABC-C; rho = -0.65, p<0.001), a measure of subjective balance confidence.ConclusionsThe FROP-Com screen is a reliable clinical tool with convergent validity paralleled with subjective balance confidence measure that can be used in fall risk screening of community-dwelling people with stroke. However, one individual item, the observation of balance, will require additional refinement to improve the potential measurement error. ]]> <![CDATA[Trajectories of fatigue among stroke patients from the acute phase to 18 months post-injury: A latent class analysis]]>


Post-stroke fatigue (PSF) is a common symptom affecting 23–75% of stroke survivors. It is associated with increased risk of institutionalization and death, and it is of many patients considered among the worst symptoms to cope with after stroke. Longitudinal studies focusing on trajectories of fatigue may contribute to understanding patients’ experience of fatigue over time and its associated factors, yet only a few have been conducted to date.


To explore whether subgroups of stroke survivors with distinct trajectories of fatigue in the first 18 months post stroke could be identified and whether these subgroups differ regarding sociodemographic, medical and/or symptom-related characteristics.

Materials and methods

115 patients with first-ever stroke admitted to Oslo University Hospital or Buskerud Hospital were recruited and data was collected prospectively during the acute phase and at 6, 12 and 18 months post stroke. Data on fatigue (both pre- and post-stroke), sociodemographic, medical and symptom-related characteristics were collected through structured interviews, standardized questionnaires and from the patients’ medical records.

Growth mixture modeling (GMM) was used to identify latent classes, i.e., subgroups of patients, based on their Fatigue Severity Scales (FSS) scores at the four time points. Differences in sociodemographic, medical, and symptom-related characteristics between the latent classes were evaluated using univariate and multivariable ordinal regression analyses.

Results and their significance

Using GMM, three latent classes of fatigue trajectories over 18 months were identified, characterized by differing levels of fatigue: low, moderate and high. The mean FSS score for each class remained relatively stable across all four time points. In the univariate analyses, age <75, pre-stroke fatigue, multiple comorbidities, current depression, disturbed sleep and some ADL impairment were associated with higher fatigue trajectories. In the multivariable analyses, pre-stroke fatigue (OR 4.92, 95% CI 1.84–13.2), multiple comorbidities (OR 4,52,95% CI 1.85–11.1) and not working (OR 4.61, 95% CI 1.36–15,7) were the strongest predictor of higher fatigue trajectories The findings of this study may be helpful for clinicians in identifying patients at risk of developing chronic fatigue after stroke.

<![CDATA[Predictors of long-term prognosis in acute kidney injury survivors who require continuous renal replacement therapy after cardiovascular surgery]]>

The long-term prognosis of patients with postoperative acute kidney injury (AKI) requiring continuous renal replacement therapy (CRRT) after cardiovascular surgery is unclear. We aimed to investigate long-term renal outcomes and survival in these patients to determine the risk factors for negative outcomes. Long-term prognosis was examined in 144 hospital survivors. All patients were independent and on renal replacement therapy at hospital discharge. The median age at operation was 72.0 years, and the median pre-operative estimated glomerular filtration rate (eGFR) was 39.5 mL/min/1.73 m2. The median follow-up duration was 1075 days. The endpoints were death, chronic maintenance dialysis dependence, and a composite of death and chronic dialysis. Predictors for death and dialysis were evaluated using Fine and Gray’s competing risk analysis. The cumulative incidence of death was 34.9%, and the chronic dialysis rate was 13.3% during the observation period. In the multivariate proportional hazards analysis, eGFR <30 mL/min/1.73 m2 at discharge was associated with the composite endpoint of death and dialysis [hazard ratio (HR), 2.1; 95% confidence interval (CI), 1.1–3.8; P = 0.02]. Hypertension (HR 8.7, 95% CI, 2.2–35.4; P = 0.002) and eGFR <30 mL/min/1.73 m2 at discharge (HR 26.4, 95% CI, 2.6–267.1; P = 0.006) were associated with dialysis. Advanced age (≥75 years) was predictive of death. Patients with severe CRRT-requiring AKI after cardiovascular surgery have increased risks of chronic dialysis and death. Patients with eGFR <30 mL/min/1.73 m2 at discharge should be monitored especially carefully by nephrologists due to the risk of chronic dialysis and death.

<![CDATA[Short-term mortality in older medical emergency patients can be predicted using clinical intuition: A prospective study]]>


Older emergency department (ED) patients are at risk for adverse outcomes, however, it is hard to predict these. We aimed to assess the discriminatory value of clinical intuition, operationalized as disease perception, self-rated health and first clinical impression, including the 30-day surprise question (SQ: “Would I be surprised if this patient died in the next 30 days” of patients, nurses and physicians. Endpoints used to evaluate the discriminatory value of clinical intuition were short-term (30-day) mortality and other adverse outcomes (intensive/medium care admission, prolonged length of hospital stay, loss of independent living or 30-day readmission).


In this prospective, multicentre cohort study, older medical patients (≥65 years), nurses and physicians filled in scores regarding severity of illness and their concerns (i.e. disease perception and clinical impression scores) immediately after arrival of the patient in the ED. In addition, patients filled in a self-rated health score and nurses and physicians answered the SQ. Area under the curves (AUCs) of receiver operating characteristics (ROCs) were calculated.


The median age of the 602 included patients was 79 years and 86.7% were community dwelling. Within 30 days, 66 (11.0%) patients died and 263 (43.7%) patients met the composite endpoint. The severity of concern score of both nurses and physicians yielded the highest AUCs for 30-day mortality (for both 0.75; 95%CI 0.68–0.81). AUCs for the severity of illness score and SQ of nurses and physicians ranged from 0.71 to 0.74 while those for the disease perception and self-rated health of patients ranged from 0.64 to 0.69. The discriminatory value of the scores for the composite endpoint was lower (AUCs ranging from 0.60 to 0.67). We used scores that have not been previously validated which could influence their generalisability.


Clinical intuition,—disease perception, self-rated health and first clinical impression—documented at an early stage after arrival in the ED, is a useful clinical tool to predict mortality and other adverse outcomes in older ED patients. Highest discriminatory values were found for the nurses’ and physicians’ severity of concern score. Intuition may be helpful for the implementation of personalised medical care in the future.

<![CDATA[Psychometric and diagnostic properties of the Taiwan version of the Quick Mild Cognitive Impairment screen]]>

There is a need for a screening tool with capacities of accurate detection of early mild cognitive impairment (MCI) and dementia and is suitable for use in a range of languages and cultural contexts. This research aims to evaluate the psychometric and diagnostic properties of the Taiwan version of Qmci (Qmci-TW) screen and to explore the discriminating ability of the Qmci-TW in differentiating among normal controls (NCs), MCI and dementia. Thirty-one participants with dementia and 36 with MCI and 35 NCs were recruited from a neurology department of regional hospital in Taiwan. Their results on the Qmci-TW, Taiwanese version of the Montreal Cognitive Assessment (MoCA), and Traditional Chinese version of the Mini–Mental State Examination (MMSE) were compared. For analysis, we used Cronbach’s α, intraclass correlation coefficient, Spearman’s ρ, Kruskal–Wallis test, receiver operating characteristic curve analysis, and multivariate analysis, as appropriate. The Qmci-TW exhibited satisfactory test–retest reliability, internal consistency, and interrater reliability as well as a strong positive correlation with results from the MoCA and MMSE. The optimal cut-off score on the Qmci-TW for differentiating MCI from NC was ≤ 51.5/100 and dementia from MCI was ≤ 31/100. The MoCA exhibited the highest accuracy in differentiating MCI from NC, followed by the Qmci-TW and then MMSE; whereas, the Qmci-TW and MMSE exhibited the same accuracy in differentiating dementia from MCI, followed by the MoCA. The Qmci-TW may be a useful clinical screening tool for a spectrum of cognitive impairments.