RESUMO
Objective:To explore the predictive value of different critical values of slow gait speed on adverse outcomes in elderly maintenance hemodialysis (MHD) patients.Methods:The study was a prospective cohort study. The clinical data of elderly patients (≥ 60 years old) who received MHD treatment in the Third Affiliated Hospital of Guangzhou Medical University from March 1 to June 30, 2021 were collected, including demographic characteristics, diseases-related data and laboratory examination results. The follow-up period was one year. The six-meter walking test was used to measure the gait speed (m/s), and 0.6 m/s, 0.8 m/s and 1.0 m/s were used as the different critical values of the gait speed for grouping. The differences of clinical data between different groups were compared. Logistic regression analysis method was used to assess the association of slow gait speed with adverse outcomes (falls and hospitalization) in elderly MHD patients. The receiver operating characteristic (ROC) curve was performed to evaluate the best critical value of slow gait speed to predict the risk of falls and hospitalization.Results:A total of 108 elderly patients with MHD were included, with 57 males and 51 females. There were 43 patients (39.8%) of falls and 34 patients (31.5%) of hospitalization. There were statistically significant differences in age, Charlson's comorbidity index, and the proportions of hypertension, family support needed in daily life, walking aids needed, falls and hospitalization events among the four groups of the patients grouped according to gait speed (all P < 0.05). Multivariate logistic regression analysis results showed that the risk of falls predicted by gait speed of 0.6- < 0.8 m/s was higher than that by gait speed of > 1.0 m/s ( OR=3.973, 95% CI 1.116-14.136, P=0.033). The risk of hospitalization predicted by gait speed < 0.6 m/s was higher than that by gait speed > 1.0 m/s ( OR=9.147, 95% CI 1.658-50.453, P=0.011). The logistic regression analysis was performed with the critical values of 0.6 m/s, 0.8 m/s and 1.0 m/s as the classification variables, and the results showed that the gait speed of < 0.8 m/s was an influencing factor of the falls risk in elderly MHD patients (≥ 0.8 m/s as reference, OR=3.200, 95% CI 1.099-9.318, P=0.033). The gait speed < 0.8 m/s and < 0.6 m/s were influencing factors of hospitalization (≥ 0.8 m/s as reference, OR=3.899, 95% CI 1.355-11.216, P=0.012; ≥ 0.6 m/s as reference, OR=4.226, 95% CI 1.107-16.140, P=0.035). The area under the ROC curve for gait speed of < 0.6 m/s, < 0.8 m/s and < 1.0 m/s to predict the risk of falls were 0.605(95% CI 0.493-0.717, P=0.065), 0.668(95% CI 0.562-0.774, P=0.003), and 0.634 (95% CI 0.529-0.739, P=0.019), respectively. The best critical value of slow gait speed to predict the risk of fall was 0.73 m/s, and the area under the ROC curve was 0.720(95% CI 0.623-0.817, P < 0.001), with the sensitivity and specificity of 0.846 and 0.512, respectively. The area under the ROC curve for gait speed of < 0.6 m/s, < 0.8 m/s and < 1.0 m/s to predict the risk of hospitalization were 0.629(95% CI 0.509-0.749, P=0.032),0.683(95% CI 0.573-0.793, P=0.002), and 0.608(95% CI 0.497- 0.719, P=0.073). The best critical value of slow gait speed to predict the risk of hospitalization was 0.81 m/s, and the area under the ROC curve was 0.688(95% CI 0.576-0.800, P=0.002), with the sensitivity and specificity of 0.689 and 0.676, respectively. Conclusion:The critical value of gait speed 0.8 m/s can be used to predict the risk of falls and hospitalization in elderly MHD patients.
RESUMO
Objective:To investigate the psychological effect of physical function dependence on maintenance hemodialysis (MHD) patients and their primary family caregivers.Methods:The study was a cross-sectional survey. The MHD patients in the hemodialysis centre, the Third Affiliated Hospital of Guangzhou Medical University from March 2022 to June 2022 were enrolled. The patients' demographics and laboratory data were collected. Katz and Lawton-Brody questionnaires were used to assess patients' physical function, and Five Item Mental Health Inventory (MHI-5) was used to evaluate the psychological conditions of the patients and their primary family caregivers. Multiple linear regression analysis was used to analyze the influencing factors of MHI-5 scores of the patients and their primary family caregivers.Results:A total of 116 patients were included, with 61 males and 55 females. There were 47 patients (40.5%) with physical function dependence. In the physical function dependence group, serum albumin ( t=-2.512, P=0.013), MHI-5 scores of patients and their primary family caregivers ( t=-8.461, P < 0.001; t=-8.533, P < 0.001) and male ratio ( χ2=8.467, P=0.002) were significantly lower, and the age ( t=9.754, P < 0.001) and the proportions of hypertension ( χ2=20.421, P < 0.001), diabetes ( χ2=10.470, P=0.002), cardiovascular and cerebrovascular diseases ( χ2=9.898, P=0.003) were significantly higher than those in the normal physical function group. The incidence of mental disorders in MHD patients was 39.7%(46/116), and the incidence of mental disorders in the physical function dependence group was significantly higher than that in the normal physical function group [72.3%(34/47) vs. 17.4%(12/69), χ2=35.275, P < 0.001]. The incidence of mental disorders in the primary family caregivers was 32.8%(38/116), and the incidence of mental disorders in the primary family caregivers of physical function dependence group was significantly higher than that in the normal physical function group [66.0%(31/47) vs. 10.1%(7/69), χ2=39.536, P < 0.001]. The incidence of mental disorders in the primary family caregivers of MHD patients who were not spouses was significantly higher than that of spouses [46.0%(29/63) vs. 17.0%(9/53), χ2=11.028, P=0.001], and in physical function dependence group, the incidence of mental disorders in non-spouses was significantly higher than that in spouses [80.6%(25/31) vs. 37.5%(6/16), χ2=8.749, P=0.003]. Multiple linear analysis showed that bathing ( β=-5.182, P=0.015), doing laundry ( β=-7.053, P < 0.001), taking medication ( β=-8.680, P=0.003), and female patients ( β=-2.982, P=0.030) were the influencing factors of MHI-5 scores decline in MHD patients. Bathing ( β=-4.404, P=0.032), preparing meals ( β=-3.954, P=0.041), managing money ( β=-5.067, P=0.021), and female patients ( β=-2.466, P=0.042) were the influencing factors of MHI-5 scores decline in primary family caregivers. Conclusions:The incidence of physical function dependence in MHD patients is high, and its manifestations and influencing factors are diverse. The incidence of mental disorders in MHD patients and their primary family caregivers is also high, especially in patients with physical function dependence and non- spouse family caregivers. Clinicians should pay attention to and assess the physical function dependence of MHD patients as early as possible, and intervene in time. At the same time, they should also pay attention to the mental health of MHD patients and their primary family caregivers.