Risk of emergency hospital admission related to adverse events after antibiotic treatment in adults with a common infection: impact of COVID-19 and derivation and validation of risk prediction models

Abstract

Background: With the global challenge of antimicrobial resistance intensified during the COVID-19 pandemic, evaluating adverse events (AEs) post-antibiotic treatment for common infections is crucial. This study aims to examines the changes in incidence rates of AEs during the COVID-19 pandemic and predict AE risk following antibiotic prescriptions for common infections, considering their previous antibiotic exposure and other long-term clinical conditions.

Methods: With the approval of NHS England, we used OpenSAFELY platform and analysed electronic health records from patients aged 18-110, prescribed antibiotics for urinary tract infection (UTI), lower respiratory tract infections (LRTI), upper respiratory tract infections (URTI), sinusitis, otitis externa, and otitis media between January 2019 and June 2023. We evaluated the temporal trends in the incidence rate of AEs for each infection, analysing monthly changes over time. The survival probability of emergency AE hospitalisation was estimated in each COVID-19 period (period 1: 1 January 2019 to 25 March 2020, period 2: 26 March 2020 to 8 March 2021, period 3: 9 March 2021 to 30 June 2023) using the Kaplan-Meier approach. Prognostic models, using Cox proportional hazards regression, were developed and validated to predict AE risk within 30 days post-prescription using the records in Period 1.

Results: Out of 9.4 million patients who received antibiotics, 0.6% of UTI, 0.3% of URTI, and 0.5% of LRTI patients experienced AEs. UTI and LRTI patients demonstrated a higher risk of AEs, with a noted increase in AE incidence during the COVID-19 pandemic. Higher comorbidity and recent antibiotic use emerged as significant AE predictors. The developed models exhibited good calibration and discrimination, especially for UTIs and LRTIs, with a C-statistic above 0.70.

Conclusions: The study reveals a variable incidence of AEs post-antibiotic treatment for common infections, with UTI and LRTI patients facing higher risks. AE risks varied between infections and COVID-19 periods. These findings underscore the necessity for cautious antibiotic prescribing and call for further exploration into the intricate dynamics between antibiotic use, AEs, and the pandemic.

Keywords: Adverse event; Antibiotics; COVID-19 pandemic; Common infection.

Fig. 1

The flowchart of participant selection

Fig. 2

Incidence rates of AE over time calculated every month based on the number of new cases per 1000 patients at risk (antibiotic users with certain infection consultation). Numerator is the number of adverse event cases (times 1000), and the denominator is the number of patients at risk, grouped by infection type. Boxplots represent the historical average (median and IQR) percentage of incidence rates of new AE’s cases from January 2019 to June 2023. The shadow area indicating the periods of national lockdown

Fig. 3

Kaplan–Meier plots for AE in 30 days after antibiotics. Plots show cumulative survival probability of AE by period and infection. The study duration was segmented based on the implementation of national lockdowns: (1) period 1 from 1 January 2019 to 25 March 2020, (2) period 2 from 26 March 2020 to 8 March 2021, and (3) period 3 from 9 March 2021 to 30 June 2023

Fig. 4

Period 1 cohort (pre-COVID): adjusted hazard ratios for selected predictors (including health behavioural and clinical variables). The Index of Multiple Deprivation (IMD) quintile was derived from the patient’s residential address. Body mass index (BMI) refers to a calculation of body fat based on height and weight. obese I (30–34.9 kg/m²), obese II (35–39.9 kg/m²), and obese III (≥ 40 kg/m²). The Charlson Comorbidities Index (CCI) is a method of categorising comorbidities of patients based on the International Classification of Diseases (ICD) diagnosis codes found in administrative data. It includes 17 weighted conditions such as myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, connective tissue disease, ulcer disease, mild liver disease, diabetes, hemiplegia, moderate or severe renal disease, diabetes with complications, any malignancy (including leukaemia and lymphoma), moderate or severe liver disease, metastatic solid tumour, and AIDS. Used in the past 30 days: the binary variable indicating if there was any antibiotic treatments administered in the 30 days preceding the index date. Used in the past 3 years: the patient’s antibiotic prescription history spans from three years plus 90 days, up until 90 days prior to the outcome date. Reference groups: Sex: Female, Age: 18–39, Region: East of England, IMD quintile: the least deprived quintile (IMD 5), Ethnicity: white, BMI: Not obese (< 30 kg/m²) Smoking: None (smoking status identified from the most recent clinical records), CCI: Zero, Antibiotic use: used in the past 30 days: No, used in the past 3 years: zero

Fig. 5

Calibration plot for UTI/URTI/LRTI models. Calibration plot showing observed survival probabilities (Y-axis) versus predicted survival probabilities (X-axis). The plot was generated from the validation cohort