ArticleMedicine2019
Quick-SOFA score to predict mortality among geriatric patients with influenza in the emergency department.
Article in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 20 citations in OpenAlex.
- Impact of prehospital antibiotic therapy differs depending on septic shock origin.Journal of intensive care · 2026Article
- Performance of established disease severity scores in predicting severe outcomes among adults hospitalized with influenza-FluSurv-NET, 2017-2018.Influenza and other respiratory viruses · 2023Article
- Two-stage prediction model for in-hospital mortality of patients with influenza infection.BMC infectious diseases · 2021Article
- Severity Scores in COVID-19 Pneumonia: a Multicenter, Retrospective, Cohort Study.Journal of general internal medicine · 2021Article
- Predictive value of geriatric-quickSOFA in hospitalized older people with sepsis.BMC geriatrics · 2021Observational
- Comparison of quick SOFA and SIRS scales at the bedside of patients with Staphylococcus aureus bacteremiaBiomedica : revista del Instituto Nacional de Salud · 2020Observational
- Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The quick sequential organ failure assessment (qSOFA) score is widely used to assess the risk of sepsis and predict in-hospital mortality in patients with suspected infection. However, its ability to predict mortality among geriatric patients with influenza in the emergency department (ED) remains unclear. Therefore, this study was conducted to delineate this issue.A retrospective case-control study was conducted on geriatric patients (age ≥65 years) with influenza who visited the ED of a medical center between January 01, 2010, and December 31, 2015. Demographic data, vital signs, past histories, influenza subtypes, and treatment outcomes were included in the analysis. We assessed the accuracy of the qSOFA score in predicting 30-day mortality via logistic regression. Covariate adjustment of the area under the receiver operating characteristic curve (AUROC) via regression modeling was performed too.In total, 409 geriatric ED patients with mean age of 79.5 years and nearly equal sex ratio were recruited. The mean qSOFA score was 0.55 ± 0.7. The Hosmer-Lemeshow goodness-of-fit test was 0.79 for qSOFA score. Patients with qSOFA score of ≥2 (odds ratio, 4.21; 95% confidence interval [CI], 1.56-11.40) had increased in-hospital mortality. qSOFA score of ≥2 also had excellent in-hospital mortality discrimination with an adjusted AUROC of 0.81 (95% CI, 0.71-0.90). A qSOFA of ≥2 had prominent specificity of 0.89 (95% CI, 0.86-0.92).An increase in qSOFA score of 2 greatly predicts mortality in geriatric patients with influenza.
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.