OBJECTIVES: To determine the prevalence of chronic kidney disease in patients undergoing TAVR and analyse their overall procedural outcomes.
METHODS: This retrospective observational study was conducted at 43 publicly funded hospitals in Hong Kong. Severe aortic stenosis patients undergoing TAVR between the years 2010 and 2019 were enroled in the study. Two groups were identified according to the presence of baseline chronic kidney disease.
RESULTS: A total of 499 patients (228, 58.6% men) were enroled in the study. Baseline hypertension was more prevalent in patients with CKD (82.8%; P=0.003). As for primary end-points, mortality rates of CKD patients were significantly higher compared to non-CKD patients (10% vs. 4.1%; P=0.04%). Gout and hypertension were found to be significantly associated with CRF. Patients with gout were nearly six times more likely to have CRF than those without gout (odds ratio = 5.96, 95% CI = 3.12-11.29, P<0.001). Patients with hypertension had three times the likelihood of having CRF compared to those without hypertension (odds ratio=2.83, 95% CI=1.45-6.08, P=0.004).
CONCLUSION: In patients with severe aortic stenosis undergoing TAVR, baseline CKD significantly contributes to mortality outcomes at long-term follow up.
HYPOTHESIS: This study tested the hypothesis that attendance-related HCRUs and costs differed between patients with Brugada syndrome (BrS) and congenital long QT syndrome (LQTS).
METHODS: This was a retrospective cohort study of consecutive BrS and LQTS patients at public hospitals or clinics in Hong Kong, China. HCRUs and costs (in USD) for Accident and Emergency (A&E), inpatient, general outpatient and specialist outpatient attendances were analyzed between 2001 and 2019 at the cohort level. Comparisons were made using incidence rate ratios (IRRs [95% confidence intervals]).
RESULTS: Over the 19-year period, 516 BrS (median age of initial presentation: 51 [interquartile range: 38-61] years, 92% male) and 134 LQTS (median age of initial presentation: 21 [9-44] years, 32% male) patients were included. Compared to LQTS patients, BrS patients had lower total costs (2 008 126 [2 007 622-2 008 629] vs. 2 343 864 [2 342 828-2 344 900]; IRR: 0.857 [0.855-0.858]), higher costs for A&E attendances (83 113 [83 048-83 177] vs. 70 604 [70 487-70 721]; IRR: 1.177 [1.165-1.189]) and general outpatient services (2,176 [2,166-2,187] vs. 921 [908-935]; IRR: 2.363 [2.187-2.552]), but lower costs for inpatient stay (1 391 624 [1 391 359-1 391 889] vs. 1 713 742 [1 713 166-1 714 319]; IRR: 0.812 [0.810-0.814]) and lower costs for specialist outpatient services (531 213 [531 049-531 376] vs. 558 597 [558268-558926]; IRR: 0.951 [0.947-0.9550]).
CONCLUSIONS: Overall, BrS patients consume 14% less health care resources compared to LQTS patients in terms of attendance costs. BrS patients require more A&E and general outpatient services, but less inpatient and specialist outpatient services than LQTS patients.
PURPOSE: To examine the association between the modified R-hf risk score and all-cause mortality in patients with HFrEF.
METHODS: Retrospective cohort study included adults hospitalized with HFrEF, as defined by clinical symptoms of HF with biplane EF less than 40% on transthoracic echocardiography, at a tertiary centre in Dalian, China, between 1 November 2015, and 31 October 2019. All patients were followed up until 31 October 2020. A modified R-hf risk score was calculated by substituting brain natriuretic peptide (BNP) for N-terminal prohormone of BNP (NT-proBNP) using EF× estimated glomerular filtration rate (eGFR)× haemoglobin (Hb))/BNP. The patients were stratified into tertiles according to the R-hf risk score. The measured outcome was all-cause mortality. The score performance was assessed using C-statistics.
RESULTS: A total of 840 patients were analyzed (70.2% males; mean age, 64±14 years; median (interquartile range) follow-up 37.0 (27.8) months). A lower modified R-hf risk score predicted a higher risk of all-cause mortality, independent of sex and age [1st tertile vs. 3rd tertile: adjusted hazard ratio (aHR), 3.46; 95% CI: 2.11-5.67; P<0.001]. Multivariate Cox regression analysis indicated that a lower modified R-hf risk score was associated with increased cumulative all-cause mortality [univariate: (1st tertile vs. 3rd tertile: aHR, 3.45; 95% CI: 2.11-5.65; P<0.001) and multivariate: (1st tertile vs. 3rd tertile: aHR 2.21, 95% CI: 1.29-3.79; P=0.004)]. The performance of the model, as reported by C-statistic was 0.67 (95% CI: 0.62-0.72).
CONCLUSION: The modified R-hf risk score predicted all-cause mortality in patients hospitalized with HFrEF. Further validation of the modified R-hf risk score in other cohorts of patients with HFrEF is needed before clinical application.
METHODS: Medline and Embase were searched for articles reporting outcomes of ACS patients stratified by SES using a multidimensional index, comprising at least 2 of the following components: Income, Education and Employment. A comparative meta-analysis was conducted using random-effects models to estimate the risk ratio of all-cause mortality in low SES vs high SES populations, stratified according to geographical region, study year, follow-up duration and SES index.
RESULTS: A total of 29 studies comprising of 301,340 individuals were included, of whom 43.7% were classified as low SES. While patients of both SES groups had similar cardiovascular risk profiles, ACS patients of low SES had significantly higher risk of all-cause mortality (adjusted HR:1.19, 95%CI: 1.10-1.1.29, p