性别对糖尿病相关下肢截肢的影响：意大利地区关于趋势和预测因素的分析。

The impact of gender on diabetes-related lower extremity amputations: An Italian regional analysis on trends and predictors.

作者信息

Di Giovanni Pamela, Scampoli Piera, Meo Francesca, Cedrone Fabrizio, D'Addezio Michela, Di Martino Giuseppe, Valente Alessandra, Romano Ferdinando, Staniscia Tommaso

机构信息

Department of Pharmacy, "G. d'Annunzio" University of Chieti-Pescara, Via dei Vestini 31, 66100 Chieti, Italy.

School of Hygiene and Preventive Medicine, "G. d'Annunzio" University of Chieti-Pescara, Via dei Vestini 31, 66100 Chieti, Italy.

出版信息

Foot Ankle Surg. 2021 Jan;27(1):25-29. doi: 10.1016/j.fas.2020.01.005. Epub 2020 Jan 17.

DOI:10.1016/j.fas.2020.01.005

PMID:31983557

Abstract

BACKGROUND

Diabetes-related lower extremity amputations (LEAs) are a major public health issue. The aim of the study was to evaluate trends by gender and predictors of LEAs in an Italian region.

METHODS

Data were collected from hospital discharge records between 2006 and 2015. Gender- and age-adjusted standardised hospitalisation rates for major and minor amputations were calculated. Poisson regression model was performed to estimate trends in LEAs.

RESULTS

Hospitalisation rates decreased for minor amputations both among males (-30.0%) and females (-5.3%), while the major amputation rates decreased only for males (-44.7%). Males were at higher risk of undergoing major (IRR 1.41, 95%CI 1.19-1.67) and minor (IRR 1.62, 95%CI 1.45-1.82) amputations. Peripheral vascular disease was the leading predictor of major and minor amputations.

CONCLUSION

A significant reduction of LEAs was observed only for males. Identifying their predictable factors may help caregivers to provide higher standards of diabetes care.

摘要

背景

糖尿病相关的下肢截肢（LEA）是一个重大的公共卫生问题。本研究的目的是评估意大利某地区按性别划分的LEA趋势及其预测因素。

方法

收集2006年至2015年期间医院出院记录的数据。计算了大截肢和小截肢的性别和年龄调整标准化住院率。采用泊松回归模型来估计LEA的趋势。

结果

小截肢的住院率在男性（-30.0%）和女性（-5.3%）中均有所下降，而大截肢率仅在男性中有所下降（-44.7%）。男性接受大截肢（发病率比1.41，95%置信区间1.19 - 1.67）和小截肢（发病率比1.62，95%置信区间1.45 - 1.82）的风险更高。外周血管疾病是大截肢和小截肢的主要预测因素。