ArticleRisk management and healthcare policy2021
Development and Evaluation of a New Predictive Nomogram for Predicting Risk of Herpes Zoster Infection in a Chinese Population with Type 2 Diabetes Mellitus.
Article in Risk management and healthcare policy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Herpes zoster hospitalization as a sentinel signal for undiagnosed dysglycemia: a call for routine glycemic screening in clinical practice.Frontiers in clinical diabetes and healthcare · 2026Article
- Exploring the Link Between Diabetes, Herpes Zoster, and Post-Herpetic Neuralgia: Insights From Mendelian Randomization.Journal of pain research · 2025Article
- The efficacy and prognosis analysis of short-term spinal cord stimulation in the treatment of zoster-associated pain: a retrospective study.Frontiers in neurology · 2025Article
- Perceptions, Attitudes, Beliefs, and Practices Toward Traditional Chinese Medicine Therapies for Herpes Zoster: A Cross-Sectional Study of Healthcare Professionals.Risk management and healthcare policy · 2024Article
- Diabetic retinopathy risk prediction in patients with type 2 diabetes mellitus using a nomogram model.Frontiers in endocrinology · 2022Article
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo identify potential risk factors for herpes zoster infection in type 2 diabetes mellitus in southeast Chinese population. PATIENTS AND
methodsWe built a model involving 266 herpes zoster patients collecting data from January 2018 to December 2019. The least absolute shrinkage and selection operator (Lasso) predictive model was used to test herpes zoster virus risk using the patient data. Multivariate regression was conducted to decide which variable would be the strongest to decrease the Lasso penalty. The predictive model was tested using the C-index, a calibration plot, and decision curve study. External validity was verified by bootstrapping by counting probabilities.
resultsIn the prediction nomogram, the prediction variables included age, sex, weight, length of hospital stay, infection, and blood pressure. The C-index of 0.844 (0.798-0.896) indicated substantial variability and thus the model was adjusted appropriately. A score of 0.825 was achieved somewhere in the above interval. Examination of the decision curve estimated that herpes zoster nomogram was useful when the intervention was determined at the 16 percent of the herpes zoster infection potential threshold.
conclusionThe herpes zoster nomogram combines age, weight, position of the rash, 2-hour plasma glucose, glycosuria, serum creatinine, length of the hospital stay, and hypertension. This calculator can be used to assess the individual herpes zoster risks in patients diagnosed with type 2 diabetes mellitus.
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