Evidence map›Paper›PMID 41634836›Full record

ArticleEuropean journal of medical research2026

Risk factors and nomogram prediction model for hypocalcemia in patients undergoing hemodialysis.

Sha Chen, Shu-Han Yu, Juan-Juan Wang, Qing-Xia Zhang, Ping Yang

Abstract read
In one paragraph

Article in European journal of medical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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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

5 authors.

Sha ChenDepartment of Nephrology, Dongyang Traditional Chinese Medicine Hospital, No. 999 Professor Road, Dongyang City, Jinhua, 322100, Zhejiang, China.
Shu-Han YuDepartment of Nephrology, Dongyang Traditional Chinese Medicine Hospital, No. 999 Professor Road, Dongyang City, Jinhua, 322100, Zhejiang, China.
Juan-Juan WangDepartment of Nephrology, Dongyang Traditional Chinese Medicine Hospital, No. 999 Professor Road, Dongyang City, Jinhua, 322100, Zhejiang, China.
Qing-Xia ZhangDepartment of Nephrology, Dongyang Traditional Chinese Medicine Hospital, No. 999 Professor Road, Dongyang City, Jinhua, 322100, Zhejiang, China.
Ping YangDepartment of Nephrology, Dongyang Traditional Chinese Medicine Hospital, No. 999 Professor Road, Dongyang City, Jinhua, 322100, Zhejiang, China. PingYang899@outlook.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHypocalcemia is a frequent complication in patients undergoing maintenance hemodialysis and is closely linked to disturbances in mineral metabolism, increased cardiovascular risk, and bone disorders. Early identification of high-risk individuals is essential for effective prevention and management. This study aimed to evaluate risk factors associated with hypocalcemia and to develop a nomogram prediction model for individualized risk assessment.

methodsThis retrospective study included 386 adult patients receiving maintenance hemodialysis between January 2020 and December 2024. Hypocalcemia was defined as total serum calcium < 2.1 mmol/L. Patients were categorized into a hypocalcemia group (n = 135) and a normocalcemia group (n = 251). Demographic, dialysis-related, biochemical, and clinical variables were collected. Univariate and multivariate logistic regression analyses were performed to identify independent predictors. A nomogram prediction model was constructed and its discrimination, calibration, and clinical utility were assessed using the receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA). Internal validation was performed using bootstrap resampling with 1000 iterations to assess model stability.

resultsMultivariate logistic regression revealed that thyroid disease, elevated serum creatinine, and hyperphosphatemia were independent risk factors for hypocalcemia, while higher parathyroid hormone (PTH) levels and compound α-ketoacid use were protective factors. The nomogram incorporating these variables demonstrated good discrimination (AUC = 0.846, 95% CI 0.802-0.891), with a sensitivity of 81.5% and specificity of 77.3%. The calibration curve showed strong agreement between predicted and observed outcomes, and DCA indicated favorable net clinical benefit. Internal validation showed robust performance with a bootstrap-corrected area under the ROC curve (AUC) of 0.832.

conclusionsThe developed nomogram provides a reliable and clinically applicable tool for individualized prediction of hypocalcemia in hemodialysis patients, facilitating improved risk stratification and management.

Indexed as

HemodialysisHypocalcemiaNomogram prediction modelParathyroid hormoneRisk factorsSerum phosphate

Identifiers

PMID41634836
PMCPMC12958510

What Socratic holds

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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 Socratic graph.