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◆ Antibiotics (Basel, Switzerland)2026-09-11

Behaviour of K. pneumoniae|Carbapenems in Several European Countries According to Clustering Time-Series Health Data with Generalised Affinity Coefficient.

Ana Paula Nascimento, Mónica Vieira, Cristina Prudêncio, Helena Bacelar-Nicolau

原始摘要(英文原文)· Original abstract
Background/Objectives: Antimicrobial resistance (AMR) constitutes a major public health and economic burden in contemporary society. This work aims to identify the patterns and temporal trends of Klebsiella pneumoniae resistance to carbapenems across several European countries. Methods: Data on K. pneumoniae resistance to carbapenems in several countries from 2005 to 2021 (with data available up to 2023) were retrieved from the public ECDC website in 2023. Agglomerative Hierarchical Cluster Analysis (HCA), based on the new generalised affinity coefficient, was applied to the estimated ARIMA models. Results: The dendrogram at the cut-off presented four clusters: the first cluster with Slovenia, Luxembourg, Italy and Estonia; the second cluster with Romania, Malta, Greece, Portugal and Spain; the third cluster Denmark, France and Czechia; and finally the fourth cluster with Lithuania, Cyprus, Finland, Austria, Belgium and Slovakia. Although the resistance values showed an increasing trend over the years in clusters II and III, the increase was more pronounced in cluster II. Conclusions: The application of data analysis, for the first time, using HCA based on a new similarity coefficient, namely, the generalised affinity coefficient, enables the evaluation of time-series patterns in different regions and enables the identification of clusters of countries showing similar temporal patterns of antimicrobial resistance. Carbapenem resistance in K. pneumoniae among countries belonging to cluster II showed increasing trends throughout the study period.
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Behaviour of K. pneumoniae|Carbapenems in Several European Countries According to Clustering Time-Series Health Data with Generalised Affinity Coefficient. — 科研速览 Science Skim