scholarly journals Thirty-year trends in heart failure hospitalization and mortality rates and the prognostic impact of co-morbidity: a Danish nationwide cohort study

2016 ◽  
Vol 18 (5) ◽  
pp. 490-499 ◽  
Author(s):  
Morten Schmidt ◽  
Sinna Pilgaard Ulrichsen ◽  
Lars Pedersen ◽  
Hans Erik Bøtker ◽  
Henrik Toft Sørensen
Keyword(s):  
Heart Failure ◽  
Cohort Study ◽  
Mortality Rates ◽  
Prognostic Impact ◽  
Heart Failure Hospitalization ◽  
Co Morbidity

scholarly journals Assessing joint spatial autocorrelations between mortality rates due to cardiovascular conditions in South Africa

2019 ◽  
Vol 14 (2) ◽  
Author(s):  
Timotheus B. Darikwa ◽  
Samuel Manda ◽  
‘Maseka Lesaoana
Keyword(s):  
Heart Failure ◽  
South Africa ◽  
Heart Disease ◽  
Health Outcomes ◽  
Empirical Bayes ◽  
Spatial Clustering ◽  
Mortality Rates ◽  
Noncommunicable Diseases ◽  
Co Morbidity ◽  
Dependent Mortality

South Africa is experiencing an increasing burden of noncommunicable diseases (NCDs). There is evidence of co-morbidity of several NCDs at small geographical areas in the country. However, the extent to which this applies to joint spatial autocorrections of NCDs is not known. The objective of this study was to derive and quantify multivariate spatial autocorrections for NCDrelated mortality in South Africa. The study used mortality attributable to cerebrovascular, ischaemic heart failure and hypertension captured by the country’s Department of Home Affairs for the years 2001, 2007 and 2011. Both univariate and pairwise spatial clustering measures were derived using observed, empirical Bayes smoothed and age-adjusted standardised mortality rates. Cerebrovascular and ischaemic heart co-clustering was significant for the years 2001 and 2011. Cerebrovascular and hypertension co-clustering was significant for the years 2007 and 2011, while hypertension and ischaemic heart co-clustering was significant for the year 2011. Co-clusters of cerebrovascular-ischaemic heart disease are the most profound and located in the south-western part of the country. It was successfully demonstrated that bivariate spatial autocorrelations can be derived for spatially dependent mortality rates as exemplified by mortality rates attributed to three cardiovascular conditions. The identified co-clusters of spatially dependent health outcomes may be targeted for an integrated intervention and monitoring programme.

scholarly journals Prognostic impact of albumin-bilirubin score on the prediction of in-hospital mortality in patients with heart failure: a retrospective cohort study

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e049325
Author(s):  
Su Han ◽  
Chuanhe Wang ◽  
Fei Tong ◽  
Ying Li ◽  
Zhichao Li ◽  
...  
Keyword(s):  
Heart Failure ◽  
Cohort Study ◽  
Hospital Mortality ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Continuous Variable ◽  
Hospital Death ◽  
Prognostic Impact ◽  
C Statistic ◽  
Patients With Heart Failure

ObjectivesLiver dysfunction is prevalent in patients with heart failure (HF) and can lead to poor prognosis. The albumin-bilirubin (ALBI) score is considered as an effective and convenient scoring system for assessing liver function. We analysed the correlation between ALBI and in-hospital mortality in patients with HF.DesignA retrospective cohort study.Setting and participantsA total of 9749 patients with HF (from January 2013 to December 2018) was enrolled and retrospectively analysed.Main outcome measuresThe main outcome is in-hospital mortality.ResultsALBI score was calculated using the formula (log10 bilirubin [umol/L] * 0.66) + (albumin [g/L] * −0.085), and analysed as a continuous variable as well as according to three categories. Following adjustment for multivariate analysis, patients which occurred in-hospital death was remarkably elevated in tertile 3 group (ALBI ≥2.27) (OR 1.671, 95% CI 1.228 to 2.274, p=0.001), relative to the other two groups (tertile 1: ≤2.59; tertile 2: −2.59 to −2.27). Considering ALBI score as a continuous variable, the in-hospital mortality among patients with HF increased by 8.2% for every 0.1-point increase in ALBI score (OR 1.082; 95% CI 1.052 to 1.114; p<0.001). The ALBI score for predicting in-hospital mortality under C-statistic was 0.650 (95% CI 0.641 to 0.660, p<0.001) and the cut-off value of ALBI score was −2.32 with a specificity of 0.630 and a sensitivity of 0.632. Moreover, ALBI score can enhance the predictive potential of NT-pro-BNP (NT-pro-BNP +ALBI vs NT-pro-BNP: C-statistic: z=1.990, p=0.0467; net reclassification improvement=0.4012, p<0.001; integrated discrimination improvement=0.0082, p<0.001).ConclusionsIn patients with HF, the ALBI score was an independent prognosticator of in-hospital mortality. The predictive significance of NT-proBNP +ALBI score was superior to NT-proBNP, and ALBI score can enhance the predictive potential of NT-proBNP.

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