Evidence map›Paper›PMID 38827006›Full record

ArticleCureus2024

Understanding Hospital Readmissions: Insights, Patterns, and Interventions for Improvement in Chronic Kidney Disease.

Arun Surasura, Bobbadi Gajendra Siva Krishna Pavan Kumar, Sravani Chinamanagonda, Divya Durga, Sahithi Gubbala

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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

5 authors.

Arun SurasuraInternal Medicine, NRI Medical College and General Hospital, Guntur, IND.
Bobbadi Gajendra Siva Krishna Pavan KumarInternal Medicine, NRI Academy of Medical Sciences, Guntur, IND.
Sravani ChinamanagondaInternal Medicine, NRI Academy of Medical Sciences, Guntur, IND.
Divya DurgaMedicine, NRI Medical College and General Hospital, Guntur, IND.
Sahithi GubbalaMedicine, NRI Medical College and General Hospital, Guntur, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHospital readmissions among chronic kidney disease (CKD) patients pose substantial challenges in healthcare, impacting both patients and healthcare systems. Understanding the patterns and determinants of CKD-related readmissions is crucial for devising effective interventions.

objectiveThis research aimed to investigate the factors contributing to hospital readmissions among CKD patients, identify the primary reasons for readmissions, and explore potential interventions to mitigate readmission risks.

methodsA retrospective analysis was conducted among a cohort of 300 CKD patients over an 18-month period at a tertiary care unit specializing in nephrology services. Data on demographics, CKD stages, comorbidities, reasons for readmissions, and lengths of hospital stays were analyzed. Logistic regression models were employed to identify predictors of readmissions.

resultsAdvancing CKD stages were associated with increased readmission rates, with higher rates observed in older patients. Cardiovascular complications and acute kidney injury were prominent reasons for readmissions. Age, comorbid conditions, and previous hospitalizations emerged as significant predictors of readmissions. Lengths of hospital stays during readmissions were also correlated with CKD stages.

conclusionThe research underscores the complex interplay of demographic and clinical factors contributing to hospital readmissions among CKD patients. Tailored interventions addressing disease severity, comorbidities, and patient-specific characteristics are pivotal in reducing readmission risks and enhancing care outcomes for this population.

Indexed as

chronic kidney diseasecomorbiditiesdemographicshospital readmissionsinterventions

Identifiers

PMID38827006
PMCPMC11144055

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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.