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Survival analysis of heart failure patients: A case study.

ABSTRACT: This study was focused on survival analysis of heart failure patients who were admitted to Institute of Cardiology and Allied hospital Faisalabad-Pakistan during April-December (2015). All the patients were aged 40 years or above, having left ventricular systolic dysfunction, belonging to NYHA class III and IV. Cox regression was used to model mortality considering age, ejection fraction, serum creatinine, serum sodium, anemia, platelets, creatinine phosphokinase, blood pressure, gender, diabetes and smoking status as potentially contributing for mortality. Kaplan Meier plot was used to study the general pattern of survival which showed high intensity of mortality in the initial days and then a gradual increase up to the end of study. Martingale residuals were used to assess functional form of variables. Results were validated computing calibration slope and discrimination ability of model via bootstrapping. For graphical prediction of survival probability, a nomogram was constructed. Age, renal dysfunction, blood pressure, ejection fraction and anemia were found as significant risk factors for mortality among heart failure patients.

SUBMITTER: Ahmad T

PROVIDER: S-EPMC5519051 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Survival analysis of heart failure patients: A case study.

Ahmad Tanvir T Munir Assia A Bhatti Sajjad Haider SH Aftab Muhammad M Raza Muhammad Ali MA

PloS one 20170720 7

This study was focused on survival analysis of heart failure patients who were admitted to Institute of Cardiology and Allied hospital Faisalabad-Pakistan during April-December (2015). All the patients were aged 40 years or above, having left ventricular systolic dysfunction, belonging to NYHA class III and IV. Cox regression was used to model mortality considering age, ejection fraction, serum creatinine, serum sodium, anemia, platelets, creatinine phosphokinase, blood pressure, gender, diabete ...[more]

PMID: 28727739

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Project description:ObjectivesThe objective of this study was to build and assess the performance of survival prediction models using the gender-specific informative risk factors for patients with left ventricular systolic dysfunction.MethodsA lasso approach was used to decide the informative predictors for building semi-parametric proportional hazards Cox model. Separate models were built for all patients [N = 299], male patients [Nmale = 194 (64.88%)], and female patients [Nfemale = 105 (35.12%)], to observe the risk factors associated with the individual's risk of death. The likelihood- ratio test was used to test the goodness of fit of the selected model, and the C-index was used to assess the predictive performance of the selected model(s) with respect to the overall model with all observed risk factors.ResultsThe survival prediction model for females is notably different from that for males. For males, smoking, diabetes, and anaemia, whereas for females, ejection fraction, sodium, and platelets count are non-informative with zero regression coefficients. The goodness of fit of the selected models with respect to the general model with all observed risk factors is tested using the likelihood-ratio test. The results are in favor of the selected models with p-values 0.51,0.61, and 0.70 for all patients, male patients, and female patients, respectively. The same values of C-index for the full model and the selected models for overall data, for males, and for females (0.72, 0.73, and 0.77 for overall data, male data, and female data, respectively) indicate that the selected models are as good as the corresponding overall models regarding their predictive performance.ConclusionThere is a substantial difference in the survival prediction models for heart failure (HF) of male and female patients in this study. More studies are needed in Pakistan for confirming this striking male-female difference regarding the potential risk factors to predict survival with heart failure.

Project description:BACKGROUND:Heart failure (HF) is a common condition affecting more than 10% of those over 70 years of age. Reliable estimates of survival following a diagnosis of HF are important to guide management and facilitate advanced care planning. Most existing research has focused on survival rates for patients admitted to hospital with acute HF. However, the majority of patients with HF are diagnosed in the outpatient setting and can have periods of sustained symptom stability in the chronic phase of their illness. There has not been a systematic review of the literature to determine the prognosis of patients with chronic HF in the community. METHODS:We will undertake a comprehensive search of the following databases: CINAHL, Database of Abstracts of Reviews of Effects, Embase, MEDLINE and the Clinical Trials Register ( clinicaltrials.gov ). Two reviewers will independently complete screening, data extraction and quality appraisal with the option of input from a third reviewer to arbitrate. We will include data from observational or database studies conducted in either community or outpatient settings. Studies of acute HF or specific subgroups of patients will be excluded. There is no restriction by geographical setting, publication language or study date. We will complete QUIPS and GRADE assessments to systematically appraise the quality of evidence within and between studies. Where possible, we will seek to pool results to conduct a meta-analysis and undertake relevant subgroup analysis including by study setting, participant age and study decade. The primary outcome will be survival time from diagnosis. The secondary outcomes will be HF-related hospital admissions, symptom burden and measures of morbidity. DISCUSSION:This systematic review will provide up to date evidence on the current survival rates and prognostic indicators for patients with chronic HF. We will put this into historical perspective, comparing outcomes across time to help understand the impact of advances in evidence-based treatment on average survival. This information is important in facilitating informed decision-making for patients and health professionals as well as highlighting areas to focus resources and improve public health planning. SYSTEMATIC REVIEW REGISTRATION:PROSPERO 2017 CRD42017075680.

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Survival analysis of heart failure patients: A case study.

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Survival analysis of heart failure patients: A case study.

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