ArticlePloS one2016
Identifying Patients with Bacteremia in Community-Hospital Emergency Rooms: A Retrospective Cohort Study.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Utility of shaking chills as a diagnostic sign for bacteremia in adults: a systematic review and meta-analysis.BMC medicine · 2024Pooled it
- A Prediction Score Versus Procalcitonin and Presepsin for Predicting Bacteremia in the Emergency Department: A Single-Center Retrospective Cohort Study.Diagnostics (Basel, Switzerland) · 2026Article
- Development and validation of a machine learning model for predicting positive blood cultures using vital signs in ICU patients.Scientific reports · 2026Article
- Derivation and validation of a new prediction score for bacteremia in the emergency department.Scientific reports · 2026Article
- Geographic Validation of the SADFUL Scores for Identifying Bacteremia in the Unscheduled Emergency Department Revisit Cohorts.Emergency medicine international · 2026Article
- First Signs at Admission: Prognostic Value of Initial Proinflammatory Markers for Sepsis and Mortality in ICU Patients.Pathogens (Basel, Switzerland) · 2025Article
- Added Value of Shaking Chills for Predicting Bacteremia in Patients with Suspected Infection.Journal of general internal medicine · 2025Observational
- Timing and prediction of secondary bacteremia in patients with COVID-19: A retrospective cohort study.Journal of general and family medicine · 2024Article
- Article
- Clinical evaluation of droplet digital PCR in the early identification of suspected sepsis patients in the emergency department: a prospective observational study.Frontiers in cellular and infection microbiology · 2024Observational
- Clinical predictors of hospital-acquired bloodstream infections: A healthcare system analysis.Spartan medical research journal · 2024Article
- Development of an artificial intelligence bacteremia prediction model and evaluation of its impact on physician predictions focusing on uncertainty.Scientific reports · 2023Article
- Predicting Bacteremia among Septic Patients Based on ED Information by Machine Learning Methods: A Comparative Study.Diagnostics (Basel, Switzerland) · 2022Article
- Diagnostic accuracy of quick SOFA score and inflammatory biomarkers for predicting community-onset bacteremia.Scientific reports · 2022Article
- Bandemia as an Early Predictive Marker of Bacteremia: A Retrospective Cohort Study.International journal of environmental research and public health · 2022Observational
- Diagnostic performance of food consumption for bacteraemia in patients admitted with suspected infection: a prospective cohort study.BMJ open · 2021Article
- Early prediction of blood stream infection in a prospectively collected cohort.BMC infectious diseases · 2021Article
- Added value of clinical prediction rules for bacteremia in hemodialysis patients: An external validation study.PloS one · 2021Article
- The Shapiro-Procalcitonin algorithm (SPA) as a decision tool for blood culture sampling: validation in a prospective cohort study.Infection · 2020Article
- Blood cultures of adult patients discharged from the emergency department-is the safety net reliable?European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2020Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectives(1) To develop a clinical prediction rule to identify patients with bacteremia, using only information that is readily available in the emergency room (ER) of community hospitals, and (2) to test the validity of that rule with a separate, independent set of data.
designMulticenter retrospective cohort study.
settingTo derive the clinical prediction rule we used data from 3 community hospitals in Japan (derivation). We tested the rule using data from one other community hospital (validation), which was not among the three "derivation" hospitals.
participantsAdults (age ≥ 16 years old) who had undergone blood-culture testing while in the ER between April 2011 and March 2012. For the derivation data, n = 1515 (randomly sampled from 7026 patients), and for the validation data n = 467 (from 823 patients). ANALYSIS: We analyzed 28 candidate predictors of bacteremia, including demographic data, signs and symptoms, comorbid conditions, and basic laboratory data. Chi-square tests and multiple logistic regression were used to derive an integer risk score (the "ID-BactER" score). Sensitivity, specificity, likelihood ratios, and the area under the receiver operating characteristic curve (i.e., the AUC) were computed.
resultsThere were 241 cases of bacteremia in the derivation data. Eleven candidate predictors were used in the ID-BactER score: age, chills, vomiting, mental status, temperature, systolic blood pressure, abdominal sign, white blood-cell count, platelets, blood urea nitrogen, and C-reactive protein. The AUCs was 0.80 (derivation) and 0.74 (validation). For ID-BactER scores ≥ 2, the sensitivities for derivation and validation data were 98% and 97%, and specificities were 20% and 14%, respectively.
conclusionsThe ID-BactER score can be computed from information that is readily available in the ERs of community hospitals. Future studies should focus on developing a score with a higher specificity while maintaining the desired sensitivity.
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