ArticleBMC cardiovascular disorders2021
Impact of hospital volume on clinical outcomes of hospitalized heart failure patients: analysis of a nationwide database including 447,818 patients with heart failure.
Article in BMC cardiovascular disorders, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- The value of speckle tracking echocardiography in early identification of subclinical cardiac involvement in patients with multiple myeloma: a pilot retrospective study.Frontiers in medicine · 2026Article
- Association between patient volume to cardiologist, process of care, and clinical outcomes in heart failure.ESC heart failure · 2023Article
- Etiologies and Predictors of 30-Day Readmission in Heart Failure: An Updated Analysis.International journal of heart failure · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundHospital volume is known to be associated with outcomes of patients requiring complicated medical care. However, the relationship between hospital volume and prognosis of hospitalized patients with heart failure (HF) remains not fully understood. We aimed to clarify the impact of hospital volume on clinical outcomes of hospitalized HF patients using a nationwide inpatient database. METHODS AND
resultsWe studied 447,818 hospitalized HF patients who were admitted from January 2010 and discharged until March 2018 included in the Japanese Diagnosis Procedure Combination database. According to the number of patients, patients were categorized into three groups; those treated in low-, medium-, and high-volume centers. The median age was 81 years and 238,192 patients (53%) were men. Patients who had New York Heart Association class IV symptom and requiring inotropic agent within two days were more common in high volume centers than in low volume centers. Respiratory support, hemodialysis, and intra-aortic balloon pumping were more frequently performed in high volume centers. As a result, length of hospital stay was shorter, and in-hospital mortality was lower in high volume centers. Lower in-hospital mortality was associated with higher hospital volume. Multivariable logistic regression analysis fitted with generalized estimating equation indicated that medium-volume group (Odds ratio 0.91, p = 0.035) and high-volume group (Odds ratio 0.86, p = 0.004) had lower in-hospital mortality compared to the low-volume group. Subgroup analysis showed that this association between hospital volume and in-hospital mortality among overall population was seen in all subgroups according to age, presence of chronic renal failure, and New York Heart Association class.
conclusionHospital volume was independently associated with ameliorated clinical outcomes of hospitalized patients with HF.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.