Low level of hemoglobin A1c and the increased incidence of herpes zoster: longitudinal study

Kobayashi, Daiki; Shimbo, Takuro; Noto, Hiroshi; Eto, Hikaru; Takahashi, Osamu; Higuchi, Takakazu

doi:10.1007/s10096-019-03584-1

Cited by 7 publications

(3 citation statements)

References 31 publications

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“…Several clinical trials have examined the relationship with hemoglobin A1c levels. 8,12 A longitudinal analysis showed that individuals with the…”

Section: Discussionmentioning

confidence: 99%

“…We assessed the onset of HZ based on coding by dermatologist, and not on laboratory-based diagnostic codes, such as antigen titers. 8 If participants experienced more than one HZ episode during the study period, only the first episode was considered for this study. Patient characteristics gathered from medical records included age, sex, weight, and length of hospital stay.…”

Section: Methodsmentioning

confidence: 99%

“…This decrease in specific immunity may be responsible for the reactivation of HZ, rendering diabetes a risk factor for shingles. [7][8][9] Predictive factors for the incidence of HZ in T2DM patients are required, considering the current risk of HZ arising in patients with malignant melanoma and several associated risk factors. 10 However, to date, no research has been conducted on the topic.…”

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confidence: 99%

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Development and Evaluation of a New Predictive Nomogram for Predicting Risk of Herpes Zoster Infection in a Chinese Population with Type 2 Diabetes Mellitus

Zeng¹,

Li²,

Wang³

et al. 2021

RMHP

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Purpose: To identify potential risk factors for herpes zoster infection in type 2 diabetes mellitus in southeast Chinese population. Patients and Methods: We 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. Results: In 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. Conclusion:The 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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“…Several clinical trials have examined the relationship with hemoglobin A1c levels. 8,12 A longitudinal analysis showed that individuals with the…”

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Development and Evaluation of a New Predictive Nomogram for Predicting Risk of Herpes Zoster Infection in a Chinese Population with Type 2 Diabetes Mellitus

Zeng¹,

Li²,

Wang³

et al. 2021

RMHP

View full text Add to dashboard Cite

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Potential explanation for the association between hemoglobin A1c level and subsequent malignancy development

Kobayashi

2019

Acta Diabetol

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Risk factors for herpes zoster infections: a systematic review and meta-analysis unveiling common trends and heterogeneity patterns

Steinmann,

Lampe,

Grosser

et al. 2024

Infection

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Purpose The burden of herpes zoster (HZ) is substantial and numerous chronic underlying conditions are known as predisposing risk factors for HZ onset. Thus, a comprehensive study is needed to synthesize existing evidence. This study aims to comprehensively identify these risk factors. Methods A systematic literature search was done using MEDLINE via PubMed, EMBASE and Web of Science for studies published from January 1, 2003 to January 1, 2023. A random-effects model was used to estimate pooled Odds Ratios (OR). Heterogeneity was assessed using the I2 statistic. For sensitivity analyses basic outlier removal, leave-one-out validation and Graphic Display of Heterogeneity (GOSH) plots with different algorithms were employed to further analyze heterogeneity patterns. Finally, a multiple meta-regression was conducted. Results Of 6392 considered records, 80 were included in the meta-analysis. 21 different conditions were identified as potential risk factors for HZ: asthma, autoimmune disorders, cancer, cardiovascular disorders, chronic heart failure (CHF), chronic obstructive pulmonary disorder (COPD), depression, diabetes, digestive disorders, endocrine and metabolic disorders, hematological disorders, HIV, inflammatory bowel disease (IBD), mental health conditions, musculoskeletal disorders, neurological disorders, psoriasis, renal disorders, rheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and transplantation. Transplantation was associated with the highest risk of HZ (OR = 4.51 (95% CI [1.9–10.7])). Other risk factors ranged from OR = 1.17–2.87, indicating an increased risk for all underlying conditions. Heterogeneity was substantial in all provided analyses. Sensitivity analyses showed comparable results regarding the pooled effects and heterogeneity. Conclusions This study showed an increased risk of HZ infections for all identified factors.

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Low level of hemoglobin A1c and the increased incidence of herpes zoster: longitudinal study

Cited by 7 publications

References 31 publications

Development and Evaluation of a New Predictive Nomogram for Predicting Risk of Herpes Zoster Infection in a Chinese Population with Type 2 Diabetes Mellitus

Development and Evaluation of a New Predictive Nomogram for Predicting Risk of Herpes Zoster Infection in a Chinese Population with Type 2 Diabetes Mellitus

Potential explanation for the association between hemoglobin A1c level and subsequent malignancy development

Risk factors for herpes zoster infections: a systematic review and meta-analysis unveiling common trends and heterogeneity patterns

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