INTRODUCTIONFalls are common among older people. Previous studies have shown that falls were multifactorial. However, data regarding community-dwelling Chinese population are minimal. We aimed to study factors associated with falls among community-dwelling older Chinese people.

MATERIALS AND METHODSWe conducted a cross-sectional study in a community hospital in Taiwan in 2010. Our sample included 671 elders from the 3680 examinees of the free annual Senior Citizens Health Examination. Participants were interviewed with a detailed questionnaire, and 317 elders were further invited for serum vitamin D tests. The main outcome was falls in the previous 12 months. Predictor variables included sociodemographic characteristics, lifestyle risk factors, body stature, frailty, serum 25 (OH) D levels, and medications.

RESULTSThe mean age of the 671 participants was 75.7 ± 6.4 years old, and 48.7% of which were female. Fallers comprised 21.0% of the study population. In multivariate models, female gender (adjusted odds ratio (aOR): 2.32), loss of height in adulthood (aOR: 1.52), low body weight (aOR: 2.69), central obesity (aOR: 1.67), frailty (aOR: 1.56), polypharmacy (aOR: 2.18) and hyperglycaemia (aOR: 1.56) were factors associated with falls. Vitamin D insufficiency (serum 25 (OH) D levels <30 ng/mL) was not associated with falls (OR: 0.78; 95% CI, 0.38 to 1.60) (n = 317) in this study.

CONCLUSIONAmong community-dwelling older people in Taiwan, falls were mainly associated with female gender, polypharmacy, frailty, reduced body height, low body weight or central obesity, and hyperglycaemia. In addition to other risk factors, body stature should be considered as a novel risk factor when screening elders at risk for falls.

Accidental Falls ; prevention & control ; statistics & numerical data ; Aged ; Aged, 80 and over ; Body Constitution ; Cross-Sectional Studies ; Demography ; Female ; Geriatric Assessment ; methods ; Humans ; Hyperglycemia ; epidemiology ; Independent Living ; statistics & numerical data ; Male ; Middle Aged ; Odds Ratio ; Polypharmacy ; Risk Assessment ; methods ; statistics & numerical data ; Risk Factors ; Sex Factors ; Socioeconomic Factors ; Taiwan ; epidemiology

Objective: The Schizophrenia Cognition Rating Scale (SCoRS) is an interview-based assessment tool for evaluating the cognitive deficit and daily functioning of patients with schizophrenia. Methods: Sixty-eight patients with schizophrenia and 68 age- and sex-matched healthy individuals were recruited to validate the Chinese version of SCoRS in this study. All participants underwent cognitive assessment using the SCoRS, which was verified by the Brief Assessment of Cognition in Schizophrenia (BACS), and the UCSD Performance-based Skills Assessment, Brief Version (UPSA-B). Patients with schizophrenia were additionally assessed using the Positive and Negative Syndrome Scale (PANSS). Results: SCoRS ratings reported by patients (SCoRS-S), those reported by the interviewer (SCoRS-I), and SCoRS global scores (SCoRS-G) showed significant correlation with all subscales of the BACS and the UPSA-B. On receiver operating characteristic curve analysis, SCoRS-S, SCoRS-I, and SCoRS-G significantly differentiated patients with schizophrenia from healthy controls. Moreover, SCoRS-S and SCoRS-I ratings showed positive correlation with the negative symptoms and general symptoms of PANSS. Conclusion The Chinese version of SCoRS showed good discriminant, concurrent, and external validity, suggesting that it is a useful and convenient tool for assessment of cognitive function among Mandarin-speaking patients with schizophrenia in clinical practice.

The impact the metabolic syndrome (MetS) components on the severity of insulin resistance (IR) has not been reported. We enrolled 564 subjects with MetS and they were divided into quartiles according to the level of each component; and an insulin suppression test was performed to measure IR. In males, steady state plasma glucose (SSPG) levels in the highest quartiles, corresponding to body mass index (BMI) and fasting plasma glucose (FPG), were higher than the other three quartiles and the highest quartiles, corresponding to the diastolic blood pressure and triglycerides, were higher than in the lowest two quartiles. In females, SSPG levels in the highest quartiles, corresponding to the BMI and triglycerides, were higher than in all other quartiles. No significant differences existed between genders, other than the mean SSPG levels in males were greater in the highest quartile corresponding to BMI than that in the highest quartile corresponding to HDL-cholesterol levels. The factor analysis identified two underlying factors (IR and blood pressure factors) among the MetS variables. The clustering of the SSPG, BMI, triglyceride and HDLcholesterol was noted. Our data suggest that adiposity, higher FPG and triglyceride levels have stronger correlation with IR and subjects with the highest BMI have the highest IR.
Waist-Hip Ratio ; Triglycerides/blood ; Middle Aged ; Metabolic Syndrome X/*metabolism ; Male ; *Insulin Resistance ; Humans ; Female ; Fasting/blood ; Cholesterol, HDL/blood ; Body Mass Index ; Blood Glucose/analysis ; Aged ; Adult

Background: To compare risk of diabetic retinopathy (DR) between patients taking sodium-glucose cotransporter-2 inhibitors (SGLT2is) and those taking glucagon-like peptide-1 receptor agonists (GLP1-RAs) in routine care. Methods: This retrospective cohort study emulating a target trial included patient data from the multi-institutional Chang Gung Research Database in Taiwan. Totally, 33,021 patients with type 2 diabetes mellitus using SGLT2is and GLP1-RAs between 2016 and 2019 were identified. 3,249 patients were excluded due to missing demographics, age <40 years, prior use of any study drug, a diagnosis of retinal disorders, a history of receiving vitreoretinal procedure, no baseline glycosylated hemoglobin, or no follow-up data. Baseline characteristics were balanced using inverse probability of treatment weighting with propensity scores. DR diagnoses and vitreoretinal interventions served as the primary outcomes. Occurrence of proliferative DR and DR receiving vitreoretinal interventions were regarded as vision-threatening DR. Results: There were 21,491 SGLT2i and 1,887 GLP1-RA users included for the analysis. Patients receiving SGLT2is and GLP-1 RAs exhibited comparable rate of any DR (subdistribution hazard ratio [SHR], 0.90; 95% confidence interval [CI], 0.79 to 1.03), whereas the rate of proliferative DR (SHR, 0.53; 95% CI, 0.42 to 0.68) was significantly lower in the SGLT2i group. Also, SGLT2i users showed significantly reduced risk of composite surgical outcome (SHR, 0.58; 95% CI, 0.48 to 0.70). Conclusion Compared to those taking GLP1-RAs, patients receiving SGLT2is had a lower risk of proliferative DR and vitreoretinal interventions, although the rate of any DR was comparable between the SGLT2i and GLP1-RA groups. Thus, SGLT2is may be associated with a lower risk of vision-threatening DR but not DR development.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.