Evidence map›Paper›PMID 38447535›Full record

ArticleNephron2024

Hospital Readmissions for Fluid Overload among Individuals with Diabetes and Diabetic Kidney Disease: Risk Factors and Multivariable Prediction Models.

Jiashen Cai, Dorothy Huang, Hanis Binte Abdul Kadir, Zhihua Huang, Li Choo Ng, Andrew Ang, Ngiap Chuan Tan, Yong Mong Bee, Wei Yi Tay, Chieh Suai Tan and 1 more

Open access · greenAbstract read
In one paragraph

Article in Nephron, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors at 4 institutions in 1 country.

Jiashen CaiDepartment of Renal Medicine, Singapore General Hospital, Singapore, Singapore.
Dorothy HuangDepartment of Renal Medicine, Singapore General Hospital, Singapore, Singapore.
Hanis Binte Abdul KadirHealth Service Research Unit, Singapore General Hospital, Singapore, Singapore.
Zhihua HuangDepartment of Renal Medicine, Singapore General Hospital, Singapore, Singapore.
Li Choo NgDepartment of Renal Medicine, Singapore General Hospital, Singapore, Singapore.
Andrew AngSingHealth Polyclinics, Singapore, Singapore.
Ngiap Chuan TanSingHealth Polyclinics, Singapore, Singapore.
Yong Mong BeeDepartment of Endocrinology, Singapore General Hospital, Singapore, Singapore.
Wei Yi TayDepartment of Family Medicine and Continuing Care, Singapore General Hospital, Singapore, Singapore.
Chieh Suai TanDepartment of Renal Medicine, Singapore General Hospital, Singapore, Singapore.
Cynthia C LimDepartment of Renal Medicine, Singapore General Hospital, Singapore, Singapore.
Singapore General Hospital · SGSingHealth Polyclinics · SGNational University of Singapore · SGSingHealth Duke-NUS Academic Medical Centre · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsHospital readmissions due to recurrent fluid overload in diabetes and diabetic kidney disease can be avoided with evidence-based interventions. We aimed to identify at-risk patients who can benefit from these interventions by developing risk prediction models for readmissions for fluid overload in people living with diabetes and diabetic kidney disease.

methodsThis was a single-center retrospective cohort study of 1,531 adults with diabetes and diabetic kidney disease hospitalized for fluid overload, congestive heart failure, pulmonary edema, and generalized edema between 2015 and 2017. The multivariable regression models for 30-day and 90-day readmission for fluid overload were compared with the LACE score for discrimination, calibration, sensitivity, specificity, and net reclassification index (NRI).

resultsReadmissions for fluid overload within 30 days and 90 days occurred in 8.6% and 17.2% of patients with diabetes, and 8.2% and 18.3% of patients with diabetic kidney disease, respectively. After adjusting for demographics, comorbidities, clinical parameters, and medications, a history of alcoholism (HR 3.85, 95% CI: 1.41-10.55) and prior hospitalization for fluid overload (HR 2.50, 95% CI: 1.26-4.96) were independently associated with 30-day readmission in patients with diabetic kidney disease, as well as in individuals with diabetes. Additionally, current smoking, absence of hypertension, and high-dose intravenous furosemide were also associated with 30-day readmission in individuals with diabetes. Prior hospitalization for fluid overload (HR 2.43, 95% CI: 1.50-3.94), cardiovascular disease (HR 1.44, 95% CI: 1.03-2.02), eGFR ≤45 mL/min/1.73 m2 (HR 1.39, 95% CI: 1.003-1.93) was independently associated with 90-day readmissions in individuals with diabetic kidney disease. Additionally, thiazide prescription at discharge reduced 90-day readmission in diabetic kidney disease, while the need for high-dose intravenous furosemide predicted 90-day readmission in diabetes. The clinical and clinico-psychological models for 90-day readmission in individuals with diabetes and diabetic kidney disease had better discrimination and calibration than the LACE score. The NRI for the clinico-psychosocial models to predict 30- and 90-day readmissions in diabetes was 22.4% and 28.9%, respectively. The NRI for the clinico-psychosocial models to predict 30- and 90-day readmissions in diabetic kidney disease was 5.6% and 38.9%, respectively.

conclusionThe risk models can potentially be used to identify patients at risk of readmission for fluid overload for evidence-based interventions, such as patient education or transitional care programs to reduce preventable hospitalizations.

Indexed as

Diabetic NephropathiesPatient ReadmissionAgedDiabetes MellitusFemaleHeart FailureHumansMaleMiddle AgedRetrospective StudiesRisk FactorsWater-Electrolyte ImbalanceDiabetesFluid overloadHeart failureHospitalizationReadmission

Identifiers

PMID38447535
PMCPMC11332313
OpenAlexW4392578540

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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.