The incidence of acute kidney injury in hospitalized patients receiving aminoglycoside antibiotics: a retrospective study.

OBJECTIVE: Our aim is to investigate the incidence and risk factors of acute kidney injury (AKI) in hospitalized patients who received aminoglycoside antibiotics. MATERIALS AND METHODS: A retrospective analysis was performed on the electronic medical record information of inpatients who received aminoglycoside (AG) antibiotics in our center from January 2018 to December 2020. The diagnosis of AKI was based on serum creatinine changes. Several statistical methods, including chi square test and two sample Wilcoxon rank sum test, were used to evaluate the epidemiological characteristics of aminoglycosides associated AKI. The multivariate logistic regression analysis was used to screen the risk factors. RESULTS: Finally, 8,040 patients who received AGs were included in the study. Among them, 494 patients (6.14%) were judged as incidence with AKI, while only 29 patients were diagnosed with AKI in the medical record. The multiple logistic regression analysis suggested that admission to ICU, complicated with diabetes mellitus, heart failure, anemia, shock, combined use of diuretics, ß-lactam antibiotics, proton pump inhibitors were independent risk factors for AKI related to aminoglycosides. CONCLUSIONS: It is urgent to improve the understanding and attention of AKI for medical workers, and the assessment of risk factors before the use of aminoglycosides should be contributed to the early prevention, diagnosis, and treatment of AKI.

[Lag effect and influencing factors of temperature on other infectious diarrhea in Zhejiang province].

Objective: To study the lag effect of temperature and the source of heterogeneity on other infectious diarrhea (OID) in Zhejiang province, so as to identify related vulnerable populations at risk. Methods: Data on OID and meteorology in Zhejiang province from 2014 to 2016 were collected. A two-stage model was conducted, including: 1) using the distributed lag non-linear model to estimate the city-specific lag effect of temperature on OID, 2) applying the multivariate Meta- analysis to pool the estimated city-specific effect, 3) using the multivariate Meta-regression to explore the sources of heterogeneity. Results: There were 301 593 cases of OID in Zhejiang province during the study period. At the provincial level, temperature that corresponding to the lowest risk of OID was 16.7 ℃, and the temperature corresponding to the highest risk was 6.2℃ (RR=2.298, 95%CI: 1.527- 3.459). 16.7 ℃ was recognized as the reference temperature. P(5) and P(95) of the average daily temperature represented low and high temperature respectively. When the temperature was cold, the risk was delayed by 2 days, with the highest risk found on the 5(th) day (RR=1.057, 95%CI: 1.030-1.084) before decreasing to the 23(rd) day. When the temperature got hot, the risk of OID occurred on the first day (RR=1.081, 95%CI: 1.045-1.118) and gradually decreasing to the 8(th) day. Differences on heterogeneous sources related to the risks of OID in different regions, presented on urban latitude and the rate of ageing in the population. Conclusions: Both high or low temperature could increase the risk of OID, with a lag effect noticed. Prevention program on OID should be focusing on populations living in the high latitude and the elderly population at the low temperature areas.

[Influence of diurnal temperature range on influenza incidence in the elderly].

Objective: To understand the influence of diurnal temperature range (DTR) on influenza incidence in the elderly in Beijing and to conduct a subgroup analysis. Methods: The incidence data of daily influenza cases in the elderly and daily meteorological data from 2014 to 2016 in Beijing were collected for this study. A generalized additive model (GAM) was used to explore whether the relationship between daily influenza cases and DTR is a linear one. A distributed lag non-linear model (DLNM) was established to quantify the lagged effect of DTR on daily influenza incidence in the elderly. The model was also used to estimate the effects of DTR on daily influenza incidence among various subgroups. Results: A total of 4 097 influenza cases in the elderly were notified during study period. The mean DTR was 10.153 ℃. A linear relationship between daily influenza incidence and DTR was detected by using GAM. DTR was significantly associated with daily influenza incidence between lag0 and lag5 with a maximal effect at lag0. An 1 ℃ increase of DTR was associated with a 2.0% increase in daily influenza incidence in the elderly (95%CI: 0.9%-3.0%). The RR values of males, females, people aged 60-69 years, people aged ≥70 years were 1.018 (95%CI: 1.005-1.032), 1.021(95%CI: 1.007-1.035), 1.012 (95%CI: 1.002-1.022), 1.025 (95%CI: 1.012-1.039), respectively. The influencing time of DTR on females (lag6) was longer than males (lag2). Conclusions: DTR was associated with increased risk of influenza in the elderly in Beijing. It is necessary to take targeted measures in the elderly to control the incidence of influenza when DTR becomes greater.