ArticleBMJ open2016
Bacteraemia predictive factors among general medical inpatients: a retrospective cross-sectional survey in a Japanese university hospital.
Article in BMJ open, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Proportion of Neutrophils in White Blood Cells as a Useful Marker for Predicting Bacteremic Acute Cholangitis.Internal medicine (Tokyo, Japan) · 2023Article
- Clinical prediction rule for bacterial arthritis: Chi-squared automatic interaction detector decision tree analysis model.SAGE open medicine · 2023Article
- The impact of bloodstream infection in patients undergoing appendectomy due to acute appendicitis.Surgery in practice and science · 2022Article
- Clinical prediction rule for bacteremia with pyelonephritis and hospitalization judgment: chi-square automatic interaction detector (CHAID) decision tree analysis model.The Journal of international medical research · 2022Article
- Bacterial profile, antimicrobial susceptibility patterns, and associated factors among bloodstream infection suspected patients attending Arba Minch General Hospital, Ethiopia.Scientific reports · 2021Article
- Useful Predictive Factors for Bacteremia among Outpatients with Pyelonephritis.Internal medicine (Tokyo, Japan) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe precise criteria for obtaining blood cultures have not been established; they depend on the physician's judgement. We examined clinical parameters to determine predictive factors of bacteraemia and the need for blood cultures among general medical inpatients.
designA retrospective cross-sectional survey.
settingA Japanese university hospital.
participantsAll general inpatients who had blood cultures taken from 1 January 2011 to 31 December 2012. MAIN MEASURES: Clinical information at or just before blood culture sampling was extracted from medical charts. Factors potentially predictive of bacteraemia were analysed using Fisher's exact test, followed by multivariable logistic regression model analysis. MAIN
resultsA total of 200 patients (male: female=119:81, 64.3±19.1 years old) comprised this study; 57 (28.5%) had positive blood culture results. Multivariable logistic regression analysis revealed that age >60 years (OR=2.75, 95% CI 1.23 to 6.48, p=0.015), female sex (OR=2.21, 95% CI 1.07 to 4.67, p=0.038), pulse rate >90 bpm (OR=5.18, 95% CI 2.25 to 12.48, p<0.001) and neutrophil percentage >80% (OR=3.61, 95% CI 1.71 to 8.00, p=0.001) were independent risk factors for positive blood culture results. The area under the receiver operating characteristic curve analysis of this model was 0.796.
conclusionsOur results emphasise the importance of taking blood cultures if the pulse rate is >90 bpm, in elderly patients and in women, and for ordering a differential white cell count.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.