Development and validation of a dynamic nomogram for high care dependency during the hospital-family transition periods in older stroke patients DOI Creative Commons

Fangyan Li,

Lei Zhang, Ruilei Zhang

et al.

BMC Geriatrics, Journal Year: 2024, Volume and Issue: 24(1)

Published: Oct. 12, 2024

This research aimed to develop and validate a dynamic nomogram for predicting the risk of high care dependency during hospital-family transition periods in older stroke patients. 309 patients who were treated Department Neurology outpatient clinics three general hospitals Jinzhou, Liaoning Province from June December 2023 selected as training set. The investigated with General Patient Information Questionnaire, Care Dependency Scale (CDS), Tilburg Frailty Inventory (TFI), Hamilton Anxiety Rating (HAMA), Depression Scale-17 (HAMD-17), Mini Nutrition Assessment Short Form (MNA-SF). Lasso-logistic regression analysis was used screen factors period, model constructed. uploaded form web page based on Shiny apps. Bootstrap method employed repeat process 1000 times internal validation. model's predictive efficacy assessed using calibration plot, decision curve (DCA), area under (AUC) receiver operator characteristic (ROC) curve. A total 133 visited department Jinzhou January March 2024 validation set external model. Based history stroke, chronic disease, falls past 6 months, depression, malnutrition, frailty, build nomogram. AUC ROC curves 0.830 (95% CI: 0.784–0.875), that 0.833 0.766-0.900). close ideal curve, DCA results confirmed performed well terms clinical applicability. online constructed this study has good specificity, sensitivity, practicability, which can be applied senior prediction assessment tool dependency. It is great significance guide development early intervention strategies, optimize resource allocation, reduce burden families society.

Language: Английский

The relationship between healthy lifestyles and cognitive function in Chinese older adults: the mediating effect of depressive symptoms DOI Creative Commons

Guowei Xian,

Yulin Chai,

Yunna Gong

et al.

BMC Geriatrics, Journal Year: 2024, Volume and Issue: 24(1)

Published: March 28, 2024

Abstract Background Previous studies have proven the positive relationship between healthy lifestyles and cognitive function in older adults. However, specific impacts mechanisms require further investigation. Therefore, this study aimed to investigate whether were associated with Chinese adults depressive symptoms mediated their association. Methods 8272 valid samples included using latest data from Longitudinal Healthy Longevity Survey (CLHLS). Pearson’s test was applied key variables. Regression models employed examine mediating effects of lifestyles, Sobel’s bootstrap method confirm path effects. Results There a significant correlation symptoms, ( p < 0.01). directly impact (β = 0.162, had effect on (β=-0.301, 0.01), while (β=-0.108, Depressive partially 0.032, The Sobel tests confirmed robustness regression analysis results. Conclusion mediate function. Our findings suggest that prevention strategies for impairment should focus mental health.

Language: Английский

Citations

7
Innate immunity-mediated neuroinflammation promotes the onset and progression of post-stroke depression DOI
Mi Xiao, Yujie Chen, 俊哉 佐々木

et al.

Experimental Neurology, Journal Year: 2024, Volume and Issue: 381, P. 114937 - 114937

Published: Aug. 26, 2024

Language: Английский

Citations

3
Development and validation of a machine learning-based risk prediction model for post-stroke cognitive impairment DOI Creative Commons
Xia Zhong, Jing Li,

Shunxin Lv

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 30, 2024

Abstract Background Machine learning (ML) risk prediction models for post-stroke cognitive impairment (PSCI) are still far from optimal. This study aims to generate a reliable predictive model predicting PSCI in Chinese individuals using ML algorithms. Methods We collected data on 494 who were diagnosed with acute ischemic stroke (AIS) and hospitalized this condition January 2022 November 2023 at medical institution. All of the observed samples divided into training set (70%) validation (30%) random. Logistic regression combined least absolute shrinkage selection operator (LASSO) was utilized efficiently screen optimal features PSCI. seven different (LR, XGBoost, LightGBM, AdaBoost, GNB, MLP, SVM) compared their performance resulting variables. used five-fold cross-validation measure model's area under curve (AUC), sensitivity, specificity, accuracy, F1 score PR values. SHAP analysis provides comprehensive detailed explanation our optimized performance. Results identified 58.50% eligible AIS patients. The most HAMD-24, FBG, age, PSQI, paraventricular lesion. XGBoost model, among 7 developed based best features, demonstrates superior performance, as indicated by its AUC (0.961), sensitivity (0.931), specificity (0.889), accuracy (0.911), (0.926), AP value (0.967). Conclusion lesion is exceptional It provide clinicians tool early screening patients effective treatment decisions

Language: Английский

Citations

1
Anxiety and depression as potential risk factors for limited pain management in patients with elderly knee osteoarthritis: a cross-lagged study DOI Creative Commons
Wenhao Yang, Guangyuan Ma,

Jingchi Li

et al.

BMC Musculoskeletal Disorders, Journal Year: 2024, Volume and Issue: 25(1)

Published: Dec. 5, 2024

Pain management for knee osteoarthritis (KOA) patients is challenging. arises from both physiological and psychological interactions, with anxiety depression potentially contributing as risk factors that hinder effective pain in KOA patients. Before treatment(T1), A total of 206 elderly inpatients were enrolled based on initial screening criteria. After treatment (T2), selected inclusion exclusion criteria, completed follow-up through phone or online questionnaires. The interval between T1 T2 was three months. Outcome measures included the Visual Analogue Scale (VAS) intensity, Beck Anxiety Inventory (BAI) anxiety, Geriatric Depression (GDS) depression. Descriptive bivariate analyses used to evaluate pain, participants. cross-lagged model examine temporal causal associations among 91% experienced at least mild Furthermore, 31% reported higher levels anxiety. At same time, depression, significantly correlated mutually predictive(all p < 0.01). Across different time points, positively predicted T2,with correlation coefficients 0.19 (p 0.05) 0.07 0.05), respectively. may be potential limiting effectiveness Clinical should regularly integration interventions appropriate antianxiety antidepressant medications. Not applicable, investigative research nature study.

Language: Английский

Citations

1
Development and validation of a dynamic nomogram for high care dependency during the hospital-family transition periods in older stroke patients DOI Creative Commons

Fangyan Li,

Lei Zhang, Ruilei Zhang

et al.

BMC Geriatrics, Journal Year: 2024, Volume and Issue: 24(1)

Published: Oct. 12, 2024

This research aimed to develop and validate a dynamic nomogram for predicting the risk of high care dependency during hospital-family transition periods in older stroke patients. 309 patients who were treated Department Neurology outpatient clinics three general hospitals Jinzhou, Liaoning Province from June December 2023 selected as training set. The investigated with General Patient Information Questionnaire, Care Dependency Scale (CDS), Tilburg Frailty Inventory (TFI), Hamilton Anxiety Rating (HAMA), Depression Scale-17 (HAMD-17), Mini Nutrition Assessment Short Form (MNA-SF). Lasso-logistic regression analysis was used screen factors period, model constructed. uploaded form web page based on Shiny apps. Bootstrap method employed repeat process 1000 times internal validation. model's predictive efficacy assessed using calibration plot, decision curve (DCA), area under (AUC) receiver operator characteristic (ROC) curve. A total 133 visited department Jinzhou January March 2024 validation set external model. Based history stroke, chronic disease, falls past 6 months, depression, malnutrition, frailty, build nomogram. AUC ROC curves 0.830 (95% CI: 0.784–0.875), that 0.833 0.766-0.900). close ideal curve, DCA results confirmed performed well terms clinical applicability. online constructed this study has good specificity, sensitivity, practicability, which can be applied senior prediction assessment tool dependency. It is great significance guide development early intervention strategies, optimize resource allocation, reduce burden families society.

Language: Английский

Citations

0