Autor(es): Carolino, Elisabete ; Matos, José Pedro ; Ricardo, Diogo ; Ramos, M. Rosário
Data: 2025
Identificador Persistente: http://hdl.handle.net/10400.21/22093
Origem: Repositório Científico do Instituto Politécnico de Lisboa
Assunto(s): Amputation; Diabetes; Poisson regression; Negative binomial regression; Projections; FCT_UIDP/05608/2020; FCT_UIDB/05608/2020
Amputation, whether surgical or traumatic, entails the loss of a body segment due to irreparable injury caused by trauma, vascular conditions, or other pathologies. Among individuals with diabetes, amputation remains one of the most feared and recognized outcomes. However, early diagnosis and timely intervention could prevent approximately 50% of diabetes-related amputations and ulcerations. This retrospective observational cross-sectional study draws on data from the Hospital Morbidity Database (BDGDH), provided by the Central Administration of the Health System (ACSS) under the Ministry of Health. This study focuses on amputations in diabetic patients in Portugal, particularly from 2000 to 2023. It aims to update statistical results and projections using current data to inform health planning and optimize resource allocation. The research uses data from the Hospital Morbidity Database, analysing factors such as year, age group, gender, and diagnosis codes. Poisson regression and Negative Binomial models were applied to estimate annual amputation rates and forecast future trends. The findings will help compare national trends with international standards, guiding public health policies and supporting prevention and early diagnosis programs to reduce the socio-economic impact of amputations.
