Evidence map›Paper›PMID 32765046›Full record

ArticleInternational journal of general medicine2020

Predictors of Mortality in Patients with Chronic Heart Failure: Is Hyponatremia a Useful Clinical Biomarker?

Manal M Alem

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Article in International journal of general medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Manal M AlemDepartment of Pharmacology, College of Clinical Pharmacy, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.ORCID 0000-0001-8447-792X
Imam Abdulrahman Bin Faisal University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic heart failure (CHF) is a global health burden. Despite advances in treatment, there remain well-recognised morbidity and mortality. Risk stratification requires the identification and validation of biomarkers, old and new. Hyponatremia has re-emerged as a prognostic marker in CHF patients.

methodsThis is a retrospective cohort study on 241 CHF patients recruited from King Fahd Hospital of the University, Al-Khobar, Saudi Arabia (January 2005-December 2016). Their serum sodium and biochemical parameters were measured at baseline, along with 2-D echocardiographic assessments of left ventricular mass and ejection fraction. The primary endpoint was the association between hyponatremia and all-cause mortality (ACM) after a follow-up period of 24 months.

resultsMean age of patients was 60.61 ± 12.63 (SD) years; 65.1% were males, and type 2 diabetes mellitus (DM) was present in 71%. Baseline serum sodium was 138.00 (136, 140) (median and interquartile range). Hyponatremia (<135 meq/L) was present in 14.1%. After follow-up, 46 deaths had occurred. Multivariate Cox-proportional hazard model showed that type 2 DM, New York Heart Association (NYHA) class (III-IV vs I-II), age, and left ventricular mass index (LVMI) were significant and independent predictors of ACM, with HR 3.03 (95% CI; 1.13, 8.16) (P=0.028), HR 2.31 (95% CI; 1.11, 4.82) (P=0.026), HR 1.06 (95% CI; 1.03, 1.09) (P<0.001), and HR 1.01 (95% CI; 1.00, 1.02) (P=0.039), respectively. Estimated glomerular filtration rate (eGFR) was not a significant predictor. Kaplan-Meier survival analysis was used for the analysis of NYHA class and hyponatremia interactions and showed that hyponatremia had an association with poorer survival in patients with NYHA class III-IV rather than I-II (Log-rank test, P= 0.0009).

conclusionHyponatremia was a feature in CHF patients, and ACM was predicted by type 2 DM, NYHA class, age, and LVMI. Hyponatremia impact on survival was in patients with more advanced disease.

Indexed as

all-cause mortalityejection fractionelectrolyte disturbanceheart failurehyponatremialeft ventricular mass indexSaudi Arabia

Identifiers

PMID32765046
PMCPMC7381090
OpenAlexW3043366464

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.