Objectives: To survey the difference of frailty prevalence in elderly inpatients amongdifferent wards; to compare the diagnostic performance of five frailty measurements (Clinical Frailty Scale [CFS], FRAIL, Fried, Edmonton, Frailty Index [FI]) in identifying frailty; and to explore the risk factors of frailty in elderly inpatients. Participants and methods: This was a cross-sectional study including 1000 inpatients (mean age 75.2±6.7 years, 51.5% male; 542, 229, and 229 patients from cardiology, non-surgical, and surgical wards, respectively) in a tertiary hospital from September 2018 to February 2019. We applied the combined index to integrate the five frailty measurements mentioned above as the gold standard of frailty diagnosis. Multivariate logistic regression models were used to determine the independent risk factors of frailty. Results: Frailty prevalence was 32.3% (Fried), 36.2% (CFS), 19.2% (FRAIL), 25.2% (Edmonton), 35.1% (FI) in all patients. The frailty was more common in non-surgical wards, regardless of the frailty assessment tools used (non-surgical wards: 27.5% to 51.5%; cardiology ward: 14.9% to 29.3%; surgical wards: 18.8% to 41.9%). CFS≥5 showed a sensitivity of 94.1% and a specificity of 85.2% for all patients. FI≥0.25 showed a sensitivity of 94.8% and a specificity of 87.0% for all patients. Age [odds ratio (OR) = 1.089, P<0.001], education level (OR = 0.782, P=0.001), heart rate (OR = 1.025, P<0.001), albumin (OR = 0.911, P=0.002), log D-dimer (OR = 2.940, P<0.001), ≥5 comorbidities (OR = 2.164, P=0.002), and ≥5 medications (OR = 2.819, P<0.001) were independently associated with frailty in all participants. Conclusion: Frailty is common among elderly inpatients, especially in non-surgical wards. CFS is a preferred screening tool and FI may be an optimal assessment tool. Old age, low educational level, fast heart rate, low albumin, high D-dimer, ≥5 comorbidities, and polypharmacy are independent risk factors of frailty in elderly hospitalized patients.

We Sought to identify circulating miRNAs suitable for HF diagnosis. In this study, a genome-wide plasma miRNA microarray was performed in 13 HF patients and 3 controls. The expression levels of selected differentially expressed, upregulated miRNAs (miR-3135b, miR-3908 and miR-5571-5p) were validated with quantitative real-time PCR (qRT-PCR) assays in an independent cohort of 33 HF patients and 20 controls. Of all the miRNAs analyzed, miR-3135b (P<0.001), miR-3908 (P<0.001), and miR-5571-5p (P<0.001) were found to have significantly different expression levels in HF compared to controls. The Receiver operating characteristic (ROC) curves for miR-3135b, miR-3908, and miR-5571-5p revealed area under the curve (AUC) values of 1.00, 0.86, and 0.94, respectively. More importantly, miR-3135b and miR-3908 were able to discriminate heart failure with reduced ejection fraction (HFrEF) from heart failure with preserved ejection fraction (HFpEF) (P<0.05). The miR-5571-5p plasma level was significantly associated with NYHA class (P<0.001). This study demonstrated for the first time that some specific microRNAs (miR-3135b, miR-3908, and miR-5571-5p) are useful biomarkers for HF and for differentiating HFrEF from HFpEF.

Aims: At present, there is a lack of recent heart failure (HF) epidemiological data up to 2021. This study aims to assess the HF burden and its risk factors from 1990 to 2021 and project trends to 2050. Methods and results: We derived HF prevalence and years lived with disability (YLDs) from Global Burden of Disease Study 2021, performing subgroup analyses by sex, age, sociodemographic index (SDI), and regions. Health inequalities were measured using the Inequality Slope Index and Concentration Index. Additionally, we made a decomposition analysis of the HF burden and forecasted its impact by 2050. The global age-standardized prevalence rate (ASPR) and age-standardized YLD rate (ASYR) of HF were 676.68 (95% UI: 598.68–776.84) and 64.7 (95% UI: 44.2–89.47) per 100 000 people and increased by 5.5% and 5.9% from 1990 to 2021, respectively. The ASPR and ASYR were higher in regions in the relatively higher SDI quintile, while the HF burden in regions in the lower SDI quintile is increasing. Ischaemic heart disease accounted for the highest ASPR of HF globally [244.02 (95% UI: 179.09–322.13)], followed by hypertensive heart disease [148.32 (95% UI: 117.32–186.28)]. The ASPR and ASYR of HF are projected to rise from 2022 to 2050, with males dominating. Conclusion: The escalating HF burden represents a critical public health challenge, necessitating immediate intervention. Policymakers must devise precise strategies aimed at curbing and preventing the HF burden.

Background: Circulating microRNAs (miRNAs) potentially carry disease-specific information. In the current study, we aim to characterize the miRNA signature in plasma from dilated cardiomyopathy (DCM) patients and assess the possible correlation between expression levels of circulating miRNAs and symptom severity in DCM patients. Methods: Using microarray-based miRNA expression profiling, we compared the miRNA expression levels in plasma samples from 4 DCM patients and 3 healthy controls. The expression levels of selected differentially expressed, upregulated miRNAs (miR-3135b, miR-3908 and miR-5571-5p) were validated independently in plasma samples from 19 DCM patients and 20 controls. Results: We observed that plasma miR-3135b (p < 0.001), miR-3908 (p < 0.001) and miR-5571-5p (p < 0.001) were significantly upregulated in DCM patients. The area under receiver operating characteristic (ROC) curves for the 3 miRNAs ranged from 0.83 to 1.00. Moreover, miR-5571-5p levels in plasma were significantly upregulated with severe New York Heart Association (NYHA) classification (p < 0.05). Conclusions: The circulating miRNAs (miR-3135b, miR-3908 and miR-5571-5p) have potential as diagnostic biomarkers for DCM. Additionally, miR-5571-5p correlated with NYHA classification. Background: Circulating microRNAs (miRNAs) potentially carry disease-specific information. In the current study, we aim to characterize the miRNA signature in plasma from dilated cardiomyopathy (DCM) patients and assess the possible correlation between expression levels of circulating miRNAs and symptom severity in DCM patients. Methods: Using microarray-based miRNA expression profiling, we compared the miRNA expression levels in plasma samples from 4 DCM patients and 3 healthy controls. The expression levels of selected differentially expressed, upregulated miRNAs (miR-3135b, miR-3908 and miR-5571-5p) were validated independently in plasma samples from 19 DCM patients and 20 controls. Results: We observed that plasma miR-3135b (p < 0.001), miR-3908 (p < 0.001) and miR-5571-5p (p < 0.001) were significantly upregulated in DCM patients. The area under receiver operating characteristic (ROC) curves for the 3 miRNAs ranged from 0.83 to 1.00. Moreover, miR-5571-5p levels in plasma were significantly upregulated with severe New York Heart Association (NYHA) classification (p < 0.05). Conclusions: The circulating miRNAs (miR-3135b, miR-3908 and miR-5571-5p) have potential as diagnostic biomarkers for DCM. Additionally, miR-5571-5p correlated with NYHA classification.

Background: We aimed to assess the utility of the combination of the mini-mental state examination (MMSE) + clock drawing test (CDT) and the Fried phenotype for predicting non-elective hospital readmission or death within 6 months in elderly inpatients with cardiovascular disease (CVD). Methods: A single-center prospective cohort was conducted from September 2018 to February 2019. Inpatients ≥65 years old were recruited. Predictive validity was tested using a Cox proportional hazards regression model analysis, and the discriminative ability was evaluated by the receiver operating characteristic (ROC) curve. Results: A total of 542 patients were included. Overall, 12% (64/542) screened positive for cognitive impairment, 16% (86/542) were physically frail and 8% (44/542) had cognitive impairment combined with physical frailty, showing an older age (P < 0.001) and a lower education level (P < 0.001) than physically frail patients. A total of 113 patients (20.9%) died or were readmitted at 6 months. Frail participants with a normal (hazard ratio [HR]: 1.73, 95% confidence interval [CI]: 1.06–2.82, P = 0.028) or impaired cognition (HR: 2.50, 95% CI: 1.27–4.91, P = 0.008) had a higher risk of non-elective hospital readmission or death than robust patients after adjusting for the age, sex, education level, marital status, the presence of diabetes mellitus, heart failure, and history of stroke. The area under the ROC curve (AUC) showed that the discriminative ability in relation to 6 months readmission and death for the MMSE + CDT + Fried phenotype was 0.65 (95% CI: 0.60–0.71), and the AUC for men was 0.71 (95% CI: 0.63–0.78), while that for women was 0.60 (95% CI: 0.51–0.69). Conclusions: Accounting for cognitive impairment in the frailty phenotype may allow for the better prediction of non-elective hospital readmission or death in elderly inpatients with CVD in the short term. Trial registration: ChiCTR1800017204; date of registration: 07/18/2018.

Background: This study aimed to develop and validate an electronic frailty index (eFI) based on routine electronic health records (EHR) for older adult inpatients and to analyze the correlations between frailty and hospitalized events and costs.Methods: We created an eFI from routine EHR and validated the effectiveness by the consistency of the comprehensive geriatric assessment-frailty index (CGA-FI) with an independent prospective cohort. Then, we analyzed the correlations between frailty and hospitalized events and costs by regressions.Results: During the study period, 49,226 inpatients were included in the analysis, 42,821 (87.0%) of which had enough data to calculate an eFI. A strong correlation between the CGA-FI and eFI was shown in the validation cohort of 685 subjects (Pearson's r = 0.716, P < 0.001). The sensitivity and specificity for an eFI≥0.15, the upper tertile, to identify frailty, defined as a CGA-FI≥0.25, were 64.8 and 88.7%, respectively. After adjusting for age, sex, and operation, an eFI≥0.15 showed an independent association with long hospital stay (odds ratio [OR] = 2.889, P < 0.001) and death in hospital (OR = 19.97, P < 0.001). Moreover, eFI values (per 0.1) were positively associated with total costs (β = 0.453, P < 0.001), examination costs (β = 0.269, P < 0.001), treatment costs (β = 0.414, P < 0.001), nursing costs (β = 0.381, P < 0.001), pharmacy costs (β = 0.524, P < 0.001), and material costs (β = 0.578, P < 0.001) after adjusting aforementioned factors.Conclusions: We successfully developed an effective eFI from routine EHR from a general hospital in China. Frailty is an independent risk factor for long hospital stay and death in hospital. As the degree of frailty increases, the hospitalized costs increase accordingly.