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1.
Aging Clin Exp Res ; 30(1): 45-51, 2018 Jan.
Article in English | MEDLINE | ID: mdl-28251568

ABSTRACT

BACKGROUND: Renal function (RF) and activities of daily living (ADL) are risk factors for heart failure (HF) patients. AIMS: We evaluated differences in motor and cognitive ADL in relation to RF in elderly hospitalized HF patients. METHODS: Participants were selected from 414 consecutive hospitalized HF patients based on certain criteria. We investigated patient characteristics including Functional Independence Measure (FIM) and estimated glomerular filtration rate (eGFR). Subjects were divided into three groups by RF level and analyzed with one-way ANOVA and Chi-square tests and two-way ANCOVA and multiple comparison tests. RESULTS: Of the 414 patients, 165 met the inclusion criteria (high RF: 41, moderate RF: 84, low RF: 40). There were significant differences between the three groups in age, eGFR, hemoglobin level, mobility, cognitive function, and length of hospital stay (p < 0.05). Motor FIM showed an interaction between term and group, and cognitive FIM showed a main effect on the group (p < 0.05). In the multiple comparisons, motor FIM of all groups indicated significant recovery, but it was significantly lower after 1 week in the low RF versus moderate/high RF groups (p < 0.05). Cognitive FIM showed no significant recovery in the low RF group; the FIM score after 2 weeks was significantly lower than that in the moderate/high RF groups (p < 0.05). CONCLUSIONS: In elderly hospitalized HF patients, the motor ADL recovery process in the low RF group was delayed compared to the high RF group. Cognitive ADL in hospitalized HF patients is difficult to recover, especially in those with low RF.


Subject(s)
Activities of Daily Living , Cognitive Dysfunction/rehabilitation , Heart Failure/rehabilitation , Renal Insufficiency/rehabilitation , Aged , Aged, 80 and over , Analysis of Variance , Cognitive Dysfunction/classification , Cognitive Dysfunction/complications , Female , Geriatric Assessment , Glomerular Filtration Rate/physiology , Heart Failure/classification , Heart Failure/complications , Humans , Length of Stay/statistics & numerical data , Male , Middle Aged , Renal Insufficiency/classification , Renal Insufficiency/complications , Retrospective Studies
2.
Biomed Res Int ; 2017: 7420738, 2017.
Article in English | MEDLINE | ID: mdl-29201912

ABSTRACT

AIMS: To examine the relationship between activities of daily living (ADL) and readmission within 90 days and assess the cutoff value of ADL to predict readmission in hospitalized elderly patients with heart failure (HF). METHODS: This cohort study comprised 589 consecutive patients with HF aged ≥65 years, who underwent cardiac rehabilitation from May 2012 to May 2016 and were discharged home. We investigated patients' characteristics, basic attributes, and ADL (motor and cognitive Functional Independence Measure [FIM]). We analyzed the data using the unpaired t-test, χ2 test, Cox proportional hazard model, receiver operating characteristic (ROC) curve, and Kaplan-Meier method. RESULTS: Of 589 patients, 113 met the criteria, and they were divided into the nonreadmission (n = 90) and readmission groups (n = 23). Age, body mass index, New York Heart Association class, hemoglobin level, and motor FIM score were significantly different between the two groups (p < 0.05). The body mass index (hazard ratio [HR]: 0.87; p < 0.05) and motor FIM score (HR: 0.94; p < 0.01) remained statistically significant. The cutoff value for the motor FIM score determined by ROC curve analysis was 74.5 points (area under the curve = 0.78; p < 0.001). CONCLUSION: The motor FIM score in elderly patients with HF was an independent predictor of rehospitalization within 90 days.


Subject(s)
Activities of Daily Living , Cardiac Rehabilitation/methods , Heart Failure/physiopathology , Heart Failure/therapy , Motor Activity/physiology , Aged , Aged, 80 and over , Female , Heart Failure/epidemiology , Humans , Kaplan-Meier Estimate , Male , Patient Discharge , Patient Readmission , Proportional Hazards Models
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