Objective? To explore the application effect of online learning platform on the training of family caregivers of disabled elderly people. Methods? From September 2017 to March 2018, the family caregivers of 90 disabled elderly people in a district of Changsha were selected by convenience sampling method, and divided into control group and observation group by random number table method, with 45 cases in each group. During the study period, the caregivers of the control group received general health education. The caregivers in the intervention group received online training on the self-developed online learning platform under the guidance of the researchers for months. Before and after the training, the family caregivers were investigated using the Family Caregivers Care Ability Scale and the Care Knowledge Assessment Questionnaire. Results? Before the training, there was no statistically significant difference in average score of care knowledge, and the total score and the five dimensions' scores of the Family Caregivers Care Ability Scale between the two groups (P ＞ 0.05). After training, the score of the care knowledge in the intervention group was (82.2±15.2), which was higher than that in the control group (64.2±17.2), and the difference was statistically significant (t=5.260,P＜ 0.01). After training, the score of Family Caregivers Care Ability Scale in the intervention group was (13.90±4.52), which was lower than that in the control group (16.57±3.25), and the difference was statistically significant (t=3.217,P＜ 0.01). The scores of the four dimension of the scale, including adjusting the role of caregiver, meeting need and providing assistance, dealing with personal mood, adjusting life in order to meet the needs to take care of elderly in the intervention gorup were lower than those in the control group, and the differences were statistically significant (P＜ 0.05). Conclusions? The training based on the online care knowledge and skill system for disability elderly can improve the family caregivers of nursing knowledge level and ability to take care of the elderly.

Objective:To investigate the efficacy of the intelligent version of the Montreal Cognitive Assessment Scale(MoCA)in identifying mild cognitive impairment(MCI)in elderly inpatients.Methods:Seventy-five patients diagnosed with mild cognitive impairment(MCI group)from the Neurology and Geriatrics Departments of a tertiary hospital in Changsha City, along with 195 patients with normal cognitive function(normal control group), were selected between July 2020 and December 2022.Both groups underwent evaluations using the intelligent version of the Montreal Cognitive Assessment(MoCA)and the Mini Mental State Examination(MMSE), and the results were analyzed.Results:The MCI group showed significantly lower total MoCA scores and MMSE scores[(19.73±2.42) vs.(24.8±2.33)]compared to the normal control group[(24.47±2.02) vs.(26.50±1.65)], with a statistically significant difference( P<0.01).The optimal cut-off score for the MoCA was found to be 23.5 points in diagnosing MCI, showing higher sensitivity, specificity, and kappa value(96.0%, 82.1%, and 0.690)compared to the MMSE scale(90.0%, 62.6%, and 0.428). Conclusions:The intelligent MoCA has a high screening accuracy for identifying MCI in this population, demonstrating superior sensitivity and specificity compared to the MMSE.

Objective:To understand the current situation of early mobilization in elder patients with acute ischemic stroke, and to analyze the influencing factors of early mobilization in patients with different degrees of neurological deficits, aiming to provide evidence for promoting early mobilization in patients with stroke and for formulating intervention strategies.Methods:Patients with acute ischemic stroke admitted to the stroke centers of two class A tertiary hospitals in Hunan Province between January and December 2021 were enrolled.The degree of neurological impairment, activities of daily living and muscle strength were evaluated within 24 hours after admission, and patients' performance of early mobilization was recorded.Based on whether patients performed out-of-bed activities such as sitting at the bedside, standing or walking, transferring from bed to chair within 48 hours after admission, they were divided into an early ambulation group and a non-early ambulation group.Univariate analysis and Logistic regression analysis were then used to examine the influencing factors of early ambulation in patients with mild to moderate neurological deficits.Results:Among 257 patients with acute ischemic stroke, 60.7%(156 cases)conducted early mobilization.The rate of early mobilization for patients with moderate neurological deficits was only 12.9%(12/193), significantly lower than that for patients with mild neurological deficits(87.8%, 144/164)( χ2=139.571, P<0.001).Univariate analysis showed that there were significantly differences in the level of activities of daily living, stroke history, strength of the upper and lower limbs of the affected side between the early and non-early ambulation groups with moderate neurological impairment(all P<0.05), and there were significant differences in the level of activities of daily living between the early ambulation group and the non-early ambulation group in patients with mild neurological impairment( χ2=11.907, P<0.001).Logistic regression analysis showed that requiring assistance in daily life( OR=4.189, 95% CI: 1.724-10.668, P=0.002), muscle strength of the affected lower extremity ≤ grade 3( OR=9.605, 95% CI: 2.627-35.113, P=0.001)and moderate neurological deficits( OR=8.585, 95% CI: 3.216-22.913, P<0.001)were the risk factors of early mobilization in stroke patients. Conclusions:The rate of stroke patients with moderate neurological impairment performing early mobilization is low within 48 hours after admission.Activities of daily living ability, limb muscle strength and degrees of neurological deficits are influencing factors of early mobilization in stroke patients.

OBJECTIVE: To develop a mortality prediction model for critically ill patients based on multidimensional and dynamic clinical data collected by the hospital information system (HIS) using random forest algorithm, and to compare the prediction efficiency of the model with acute physiology and chronic health evaluation II (APACHE II) model. METHODS: The clinical data of 10 925 critically ill patients aged over 14 years old admitted to the Third Xiangya Hospital of Central South University from January 2014 to June 2020 were extracted from the HIS system, and APACHE II scores of the critically ill patients were extracted. Expected mortality of patients was calculated according to the death risk calculation formula of APACHE II scoring system. A total of 689 samples with APACHE II score records were used as the test set, and the other 10 236 samples were used to establish the random forest model, of which 10% (n = 1 024) were randomly selected as the validation set and 90% (n = 9 212) were selected as the training set. According to the time series of 3 days before the end of critical illness, the clinical characteristics of patients such as general information, vital signs data, biochemical test results and intravenous drug doses were selected to develope a random forest model for predicting the mortality of critically ill patients. Using the APACHE II model as a reference, receiver operator characteristic curve (ROC curve) was drawn, and the discrimination performance of the model was evaluated through the area under the ROC curve (AUROC). According to the precision and recall, Precision-Recall curve (PR curve) was drawn, and the calibration performance of the model was evaluated through the area under the PR curve (AUPRC). Calibration curve was drawn, and the consistency between the predicted event occurrence probability of the model and the actual occurrence probability was evaluated through the calibration index Brier score. RESULTS: Among the 10 925 patients, there were 7 797 males (71.4%) and 3 128 females (28.6%). The average age was (58.9±16.3) years old. The median length of hospital stay was 12 (7, 20) days. Most patients (n = 8 538, 78.2%) were admitted to intensive care unit (ICU), and the median length of ICU stay was 66 (13, 151) hours. The hospitalized mortality was 19.0% (2 077/10 925). Compared with the survival group (n = 8 848), the patients in the death group (n = 2 077) were older (years old: 60.1±16.5 vs. 58.5±16.4, P < 0.01), the ratio of ICU admission was higher [82.8% (1 719/2 077) vs. 77.1% (6 819/8 848), P < 0.01], and the proportion of patients with hypertension, diabetes and stroke history was also higher [44.7% (928/2 077) vs. 36.3% (3 212/8 848), 20.0% (415/2 077) vs. 16.9% (1 495/8 848), 15.5% (322/2 077) vs. 10.0% (885/8 848), all P < 0.01]. In the test set data, the prediction value of random forest model for the risk of death during hospitalization of critically ill patients was greater than that of APACHE II model, which showed by that the AUROC and AUPRC of random forest model were higher than those of APACHE II model [AUROC: 0.856 (95% confidence interval was 0.812-0.896) vs. 0.783 (95% confidence interval was 0.737-0.826), AUPRC: 0.650 (95% confidence interval was 0.604-0.762) vs. 0.524 (95% confidence interval was 0.439-0.609)], and Brier score was lower than that of APACHE II model [0.104 (95% confidence interval was 0.085-0.113) vs. 0.124 (95% confidence interval was 0.107-0.141)]. CONCLUSIONS The random forest model based on multidimensional dynamic characteristics has great application value in predicting hospital mortality risk for critically ill patients, and it is superior to the traditional APACHE II scoring system.
Female ; Male ; Humans ; Aged ; Adult ; Middle Aged ; Adolescent ; Critical Illness ; Hospitalization ; Length of Stay ; APACHE ; Hospital Information Systems

OBJECTIVES: Acute ischemic stroke (AIS) is one of the main causes of disability in middle-aged and elderly people, and early activity plays an important role in functional recovery. This study aims to understand the factors that affect the implementation of early activity in patients with AIS and to provide reference for promoting early activity implementation and developing intervention strategies for AIS patients. METHODS: Using purposive sampling, 19 AIS patients and their caregivers who visited at Stroke Center in the Third Xiangya Hospital of Central South University and the Third Hospital of Changsha from June to December 2021, as well as 19 medical staff, hospital administrators, or community workers providing medical health services to stroke patients, were selected as interviewes. A semi-structured interview was conducted based on the social ecological theory model, and the Colaizzi seven-step method was used to analyze the interview data. RESULTS: According to qualitative interview results, the factors affecting early activity in AIS patients were summarized into 4 themes and 12 sub-themes: medical staff factors (insufficient knowledge and skills, insufficient knowledge of early activity, unclear division of responsibilities), patient factors (severity of the disease, lack of knowledge, psychological pressure, fear of falling), social environmental factors (lack of social support, shortage of human resources and rehabilitation equipment, insufficient medical insurance support), and evidence and norms (the evidence for early activity needs improvement, lack of standardized early activity procedures). CONCLUSIONS Early activity in AIS patients is impacted by factors at multiple levels, including medical staff, patients, social environment, and evidence and norms. Developing comprehensive intervention strategies to address these factors can promote early activity implementation in AIS patients.
Aged ; Middle Aged ; Humans ; Ischemic Stroke ; Accidental Falls ; Fear ; Social Environment ; Stroke

To understand the current situation regarding the knowledge and demand for patients with prediabetes at different self-management levels, and to provide guide for improving their knowledge.
 Methods: A total of 312 prediabetes patients from 3 hospitals in Changsha were enrolled in this survey. The questionnaires covered diabetes self-management behavior scale and prediabetes knowledge status and demand questionnaire. Diabetes knowledge acquisition and demand were analyzed among patients with different levels of self-management.
 Results: The score of self-management behavior for patients with prediabetes was 39.1±13.9. The rate of knowledge acquisition was low and the rate of demand was high. The knowledge acquisition rate was high and the knowledge demand rate was low in patients with high levels of self-management. As for the contents of health education, the dietary collocation and method for glucose detection were highly needed by all self-management levels of patients.
 Conclusion: Prediabetes patients' self-management level are low. Health education to patients with prediabetes should be based on individualized demands.
Diabetes Mellitus ; Health Knowledge, Attitudes, Practice ; Humans ; Prediabetic State ; Self-Management ; Surveys and Questionnaires