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Background: This study assessed the accuracy of three International Classification of Diseases (ICD) codes methods derived from Global Burden of Disease (GBD) sepsis study (modified GBD method) in identifying sepsis, compared to the Angus method. Sources of errors in these methods were also reported.
Methods: Prospective multicentre, observational, study. Emergency Department patients aged ≥ 16 years with high sepsis risk from nine hospitals in NSW, Australia were screened for clinical sepsis using Sepsis 3 criteria and coded as having sepsis or not using the modified GBD and Angus methods. The three modified GBD methods were: Explicit-sepsis-specific ICD code recorded; Implicit-sepsis-specific code or infection as primary ICD code plus organ dysfunction code; Implicit plus-as for Implicit but infection as primary or secondary ICD code. Agreement between clinical sepsis and ICD coding methods was assessed using Cronbach alpha (α). For false positive cases (ICD-coded sepsis but not clinically diagnosed), the ICD codes leading to those errors were documented. For false negatives (clinically diagnosed sepsis but ICD-coded), uncoded sources of infection and organ dysfunction were documented.
Results: Of 6869 screened patients, 450 (median age 72.4 years, 48.9% females) met inclusion criteria. Clinical sepsis was diagnosed in 215/450 (47.8%). The explicit, implicit, implicit plus and Angus methods identified sepsis in 108/450 (24.0%), 175/450 (38.9%), 222/450 (49.3%) and 170/450 (37.8%), respectively. Sensitivity was 41.4%, 58.1%, 67.4% and 55.8%, and specificity 91.9%, 78.7%, 67.2% and 79.1%, respectively. Agreement between clinical sepsis and all ICD coding methods was low (α = 0.52-0.56). False positives were 19, 50, and 77, while false negatives were 126, 90, and 70 for the explicit, implicit, and implicit plus methods, respectively. For false positive cases, unspecified urinary tract infection, hypotension and acute kidney failure were commonly assigned infection and organ dysfunction codes. About half (44.3%-55.6%) of the false negative cases didn't have a pathogen documented.
Conclusion: The modified GBD method demonstrated low accuracy in identifying sepsis; with the implicit plus method being the most accurate. Errors in identifying sepsis using ICD codes arise mostly from coding for unspecified urinary infections and associated organ dysfunction.
Trial Registration: The study was registered at the ANZCTR (ACTRN12621000333819) on 24 March 2021.
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http://dx.doi.org/10.1186/s13054-025-05448-x | DOI Listing |
Ann Intern Med
September 2025
Department of Medicine, Johns Hopkins University School of Medicine, and Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (J.B.S.).
Electronic health record (EHR) data are increasingly used to develop prediction models that guide clinical decision making at the point of care. These include algorithms that use high-frequency data, like in sepsis prediction, as well as simpler equations, such as the Pooled Cohort Equations for cardiovascular outcome prediction. Although EHR data used in prediction models are often highly granular and more current than other data, there is systematic and nonsystematic missingness in EHR data as there is with most data.
View Article and Find Full Text PDFJ Intensive Care Med
September 2025
Independent Researcher, Outcomes Research, Atlanta, GA, USA.
Purpose: Obesity is a risk factor for sepsis complications in older adults. We assessed the impact of metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO) on outcomes in septic shock.
Methods: We conducted a retrospective analysis using the National Inpatient Sample (2016-2020) to identify a cohort of 1,737,075 patients aged 65 years and older who were hospitalized with septic shock, as defined by ICD-10 diagnosis codes.
Int J Cancer
September 2025
Laboratory for Computational Physiology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
The rise in cancer patients could lead to an increase in intensive care units (ICUs) admissions. We explored differences in treatment practices and outcomes of invasive therapies between patients with sepsis with and without cancer. Adults from 2008 to 2019 admitted to the ICU for sepsis were extracted from the databases MIMIC-IV and eICU-CRD.
View Article and Find Full Text PDFDiabetes Obes Metab
September 2025
Phase I Clinical Trial Research Ward, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China.
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is an emerging global health concern, and its presence increases the risk of multi-system diseases. This study aimed to investigate the multimorbidity trajectories of chronic diseases in people living with MASLD.
Methods: We identified 137 859 MASLD patients in UK Biobank and used 'propensity score matching' to match an equal number of non-MASLD controls.
Front Cell Infect Microbiol
September 2025
Bacterial Resistance Research Laboratory (LABRESIS), Hospital de clínicas de Porto Alegre (HCPA), Experimental Research Center, Porto Alegre, Brazil.
Background: Critically ill patients, including those with systemic inflammatory response syndrome (SIRS) and sepsis, frequently exhibit gut microbiota disruption due to physiological stress and broad-spectrum antimicrobial therapy (AT). Although antibiotics are essential for controlling infection, they can destabilize the gut microbiota and may contribute to poorer clinical outcomes. The characterization of the gut microbiota of these patients may inform microbiota-based interventions to mitigate antibiotic-induced dysbiosis.
View Article and Find Full Text PDF