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1.
Clin Infect Dis ; 2023 Aug 19.
Article in English | MEDLINE | ID: mdl-37596856

ABSTRACT

BACKGROUND: Sepsis surveillance using electronic health record (EHR)-based data may provide more accurate epidemiologic estimates than administrative data, but experience with this approach to estimate population-level sepsis burden is lacking. METHODS: This was a retrospective cohort study including all adults admitted to publicly-funded hospitals in Hong Kong between 2009-2018. Sepsis was defined as clinical evidence of presumed infection (clinical cultures and treatment with antibiotics) and concurrent acute organ dysfunction (≥2 point increase in baseline SOFA score). Trends in incidence, mortality, and case fatality risk (CFR) were modelled by exponential regression. Performance of the EHR-based definition was compared with 4 administrative definitions using 500 medical record reviews. RESULTS: Among 13,550,168 hospital episodes during the study period, 485,057 (3.6%) had sepsis by EHR-based criteria with 21.5% CFR. In 2018, age- and sex-adjusted standardized sepsis incidence was 759 per 100,000 (relative +2.9%/year [95%CI 2.0, 3.8%] between 2009-2018) and standardized sepsis mortality was 156 per 100,000 (relative +1.9%/year [95%CI 0.9,2.9%]). Despite decreasing CFR (relative -0.5%/year [95%CI -1.0, -0.1%]), sepsis accounted for an increasing proportion of all deaths (relative +3.9%/year [95%CI 2.9, 4.9%]). Medical record reviews demonstrated that the EHR-based definition more accurately identified sepsis than administrative definitions (AUC 0.91 vs 0.52-0.55, p < 0.001). CONCLUSIONS: An objective EHR-based surveillance definition demonstrated an increase in population-level standardized sepsis incidence and mortality in Hong Kong between 2009-2018 and was much more accurate than administrative definitions. These findings demonstrate the feasibility and advantages of an EHR-based approach for widescale sepsis surveillance.

2.
BMJ Open ; 13(7): e067101, 2023 07 10.
Article in English | MEDLINE | ID: mdl-37429680

ABSTRACT

OBJECTIVES: Direct comparisons between COVID-19 and influenza A in the critical care setting are limited. The objective of this study was to compare their outcomes and identify risk factors for hospital mortality. DESIGN AND SETTING: This was a territory-wide, retrospective study on all adult (≥18 years old) patients admitted to public hospital intensive care units in Hong Kong. We compared COVID-19 patients admitted between 27 January 2020 and 26 January 2021 with a propensity-matched historical cohort of influenza A patients admitted between 27 January 2015 and 26 January 2020. We reported outcomes of hospital mortality and time to death or discharge. Multivariate analysis using Poisson regression and relative risk (RR) was used to identify risk factors for hospital mortality. RESULTS: After propensity matching, 373 COVID-19 and 373 influenza A patients were evenly matched for baseline characteristics. COVID-19 patients had higher unadjusted hospital mortality than influenza A patients (17.5% vs 7.5%, p<0.001). The Acute Physiology and Chronic Health Evaluation IV (APACHE IV) adjusted standardised mortality ratio was also higher for COVID-19 than influenza A patients ((0.79 (95% CI 0.61 to 1.00) vs 0.42 (95% CI 0.28 to 0.60)), p<0.001). Adjusting for age, PaO2/FiO2, Charlson Comorbidity Index and APACHE IV, COVID-19 (adjusted RR 2.26 (95% CI 1.52 to 3.36)) and early bacterial-viral coinfection (adjusted RR 1.66 (95% CI 1.17 to 2.37)) were directly associated with hospital mortality. CONCLUSIONS: Critically ill patients with COVID-19 had substantially higher hospital mortality when compared with propensity-matched patients with influenza A.


Subject(s)
COVID-19 , Influenza, Human , Adult , Humans , Adolescent , Retrospective Studies , Influenza, Human/epidemiology , Length of Stay , Intensive Care Units , Hospitals, Public
3.
J Intensive Care ; 9(1): 2, 2021 Jan 06.
Article in English | MEDLINE | ID: mdl-33407925

ABSTRACT

BACKGROUND: Globally, mortality rates of patients admitted to the intensive care unit (ICU) have decreased over the last two decades. However, evaluations of the temporal trends in the characteristics and outcomes of ICU patients in Asia are limited. The objective of this study was to describe the characteristics and risk adjusted outcomes of all patients admitted to publicly funded ICUs in Hong Kong over a 11-year period. The secondary objective was to validate the predictive performance of Acute Physiology And Chronic Health Evaluation (APACHE) IV for ICU patients in Hong Kong. METHODS: This was an 11-year population-based retrospective study of all patients admitted to adult general (mixed medical-surgical) intensive care units in Hong Kong public hospitals. ICU patients were identified from a population electronic health record database. Prospectively collected APACHE IV data and clinical outcomes were analysed. RESULTS: From 1 April 2008 to 31 March 2019, there were a total of 133,858 adult ICU admissions in Hong Kong public hospitals. During this time, annual ICU admissions increased from 11,267 to 14,068, whilst hospital mortality decreased from 19.7 to 14.3%. The APACHE IV standard mortality ratio (SMR) decreased from 0.81 to 0.65 during the same period. Linear regression demonstrated that APACHE IV SMR changed by - 0.15 (95% CI - 0.18 to - 0.11) per year (Pearson's R = - 0.951, p < 0.001). Observed median ICU length of stay was shorter than that predicted by APACHE IV (1.98 vs. 4.77, p < 0.001). C-statistic for APACHE IV to predict hospital mortality was 0.889 (95% CI 0.887 to 0.891) whilst calibration was limited (Hosmer-Lemeshow test p < 0.001). CONCLUSIONS: Despite relatively modest per capita health expenditure, and a small number of ICU beds per population, Hong Kong consistently provides a high-quality and efficient ICU service. Number of adult ICU admissions has increased, whilst adjusted mortality has decreased over the last decade. Although APACHE IV had good discrimination for hospital mortality, it overestimated hospital mortality of critically ill patients in Hong Kong.

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