Seasonality of acute kidney injury in a tertiary hospital academic center: an observational cohort study

• Main Authors: Gianmarco Lombardi, Giovanni Gambaro, Nicoletta Pertica, Alessandro Naticchia, Matteo Bargagli, Pietro Manuel Ferraro
• Format: Article
• Language: English
• Published: BMC 2021-01-01
• Series: Environmental Health
• Subjects: Acute kidney injury; Epidemiological study; Seasonality; Weather conditions
• Online Access: https://doi.org/10.1186/s12940-021-00691-5

Abstract Background The aim of our study was to describe seasonal trends of acute kidney injury (AKI) and its relationship with weather conditions in a hospitalized population. Methods We retrospectively collected demographic (age, sex), clinical (ICD-9-CM codes of diagnosis discharge) and laboratory data (creatinine values) from the inpatient population admitted to Fondazione Policlinico Universitario A. Gemelli IRCCS between January 2010 and December 2014 with inclusion of all patients ≥18 years with at least two values available for creatinine. The outcome of interest was AKI development, defined according to creatinine kinetics criteria. The exposures of interest were the months and seasons of the year; air temperature and humidity level were also evaluated. Log-binomial regression models adjusted for age, sex, eGFR, comorbidities, Charlson/Deyo index score, year of hospitalization were used to estimate risk ratios (RR) and 95% confidential intervals (CI). Results A total of 64,610 patients met the inclusion criteria. AKI occurred in 2864 (4.4%) hospital admissions. After full adjustment, winter period was associated with increased risk of AKI (RR 1.16, 95% CI 1.05, 1.29, p=0.003). Lower air temperature and higher humidity level were associated with risk of AKI, however in multivariable-adjusted models only higher humidity level showed a significant and independent association. Conclusions AKI is one of the most common complications of hospitalized populations with a defined seasonal pattern and a significant increase in incidence during wintertime; weather conditions, particularly higher humidity level, are independent predictors of AKI and could partially justify the observed seasonal variations.