ArticleCanadian respiratory journal
Influenza infection screening tools fail to accurately predict influenza status for patients during pandemic H1N1 influenza season.
Article in Canadian respiratory journal. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Pooled it
- Influenza-attributable burden in United Kingdom primary care.Epidemiology and infection · 2016Trial
- Predictors of Influenza Diagnosis Among Patients With Laboratory-Confirmed Influenza.The Journal of infectious diseases · 2015Article
- Is influenza-like illness a useful concept and an appropriate test of influenza vaccine effectiveness?Vaccine · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFollowing the severe acute respiratory syndrome outbreak in 2003, hospitals have been mandated to use infection screening questionnaires to determine which patients have infectious respiratory illness and, therefore, require isolation precautions. Despite widespread use of symptom-based screening tools in Ontario, there are no data supporting the accuracy of these screening tools in hospitalized patients.
objectiveTo measure the performance characteristics of infection screening tools used during the H1N1 influenza season.
methodsThe present retrospective cohort study was conducted at The Ottawa Hospital (Ottawa, Ontario) between October and December, 2009. Consecutive inpatients admitted from the emergency department were included if they were ≥18 years of age, underwent a screening tool assessment at presentation and had a most responsible diagnosis that was cardiac, respiratory or infectious. The gold-standard outcome was laboratory diagnosis of influenza.
resultsThe prevalence of laboratory-confirmed influenza was 23.5%. The sensitivity and specificity of the febrile respiratory illness screening tool were 74.5% (95% CI 60.5% to 84.8%) and 32.7% (95% CI 25.8% to 40.5%), respectively. The sensitivity and specificity of the influenza-like illness screening tool were 75.6% (95% CI 61.3% to 85.8%) and 46.3% (95% CI 38.2% to 54.7%), respectively.
conclusionsThe febrile respiratory illness screening tool missed 26% of active influenza cases, while 67% of noninfluenza patients were unnecessarily placed under respiratory isolation. Results of the present study suggest that infection-control practitioners should re-evaluate their strategy of screening patients at admission for contagious respiratory illness using symptom- and sign-based tests. Future efforts should focus on the derivation and validation of clinical decision rules that combine clinical features with laboratory tests.
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.