Influenza surveillance case definitions miss a substantial proportion of older adults hospitalized with laboratory-confirmed influenza: A report from the Canadian Immunization Research Network (CIRN) Serious Outcomes Surveillance (SOS) Network
Bibliographic record
Abstract
OBJECTIVE: Older adults often have atypical presentation of illness and are particularly vulnerable to influenza and its sequelae, making the validity of influenza case definitions particularly relevant. We sought to assess the performance of influenza-like illness (ILI) and severe acute respiratory illness (SARI) criteria in hospitalized older adults. DESIGN: Prospective cohort study. SETTING: The Serious Outcomes Surveillance Network of the Canadian Immunization Research Network undertakes active surveillance for influenza among hospitalized adults. METHODS: Data were pooled from 3 influenza seasons: 2011/12, 2012/13, and 2013/14. The ILI and SARI criteria were defined clinically, and influenza was laboratory confirmed. Frailty was measured using a validated frailty index. RESULTS: Of 11,379 adult inpatients (7,254 aged ≥65 years), 4,942 (2,948 aged ≥65 years) had laboratory-confirmed influenza. Their median age was 72 years (interquartile range [IQR], 58-82) and 52.6% were women. The sensitivity of ILI criteria was 51.1% (95% confidence interval [CI], 49.6-52.6) for younger adults versus 44.6% (95% CI, 43.6-45.8) for older adults. SARI criteria were met by 64.1% (95% CI, 62.7-65.6) of younger adults versus 57.1% (95% CI, 55.9-58.2) of older adults with laboratory-confirmed influenza. Patients with influenza who were prefrail or frail were less likely to meet ILI and SARI case definitions. CONCLUSIONS: A substantial proportion of older adults, particularly those who are frail, are missed by standard ILI and SARI case definitions. Surveillance using these case definitions is biased toward identifying younger cases, and does not capture the true burden of influenza. Because of the substantial fraction of cases missed, surveillance definitions should not be used to guide diagnosis and clinical management of influenza.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".