ArticleFrontiers in medicine2026
Impact of diabetes mellitus and glycemic control on postoperative recurrence of perianal abscess: a retrospective, single-center study.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.
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Corrections and comments
- Erratum issued
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7 authors.
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Abstract
Objective: To evaluate the independent effects of diabetes mellitus and the level of glycaemic control on postoperative recurrence of perianal abscess, and to develop and internally validate a clinically applicable risk prediction model. Methods: We conducted a single-center retrospective cohort study of 232 consecutive adults who underwent primary incision and drainage for perianal abscess between June 2023 and March 2025. Detailed demographic, clinical and operative data were extracted from electronic records, including diabetes status and preoperative glycated hemoglobin (HbA1c). Candidate predictors (age, sex, BMI, lifestyle factors, abscess location, diabetes, HbA1c, inflammatory markers and intraoperative pus residue) were first entered into a LASSO regression for variable selection, followed by multivariable logistic regression. Model performance was assessed in terms of discrimination (area under the receiver operating characteristic curve, AUC), calibration (calibration plots and Hosmer-Lemeshow test) and clinical utility (decision curve analysis), with internal validation by bootstrap resampling (1,000 replicates). Results: Of the 232 patients (median age 47 years; 53.0% male), 68 (29.3%) experienced recurrence within 6 months. Compared with the non-recurrence group, patients with recurrence had a higher prevalence of diabetes (45.6% vs. 15.2%, Conclusion: Diabetes mellitus and inadequate glycaemic control are important, independent risk factors for postoperative recurrence of perianal abscess, with a clear dose-response relationship between HbA1c and recurrence risk. The internally validated prediction model, which combines HbA1c with other readily available clinical variables, shows promise as a tool for early identification of high-risk patients and may support more personalized perioperative optimization and follow-up. External validation and impact studies are required before routine implementation in diverse clinical settings.
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