Diagnosis of Stroke-Associated Pneumonia
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Lower respiratory tract infections frequently complicate stroke and adversely affect outcome. There is currently no agreed terminology or gold-standard diagnostic criteria for the spectrum of lower respiratory tract infections complicating stroke, which has implications for clinical practice and research. The aim of this consensus was to propose standardized terminology and operational diagnostic criteria for lower respiratory tract infections complicating acute stroke. METHODS: Systematic literature searches of multiple electronic databases were undertaken. An evidence review and 2 rounds of consensus consultation were completed before a final consensus meeting in September 2014, held in Manchester, United Kingdom. Consensus was defined a priori as ≥75% agreement between the consensus group members. RESULTS: Consensus was reached for the following: (1) stroke-associated pneumonia (SAP) is the recommended terminology for the spectrum of lower respiratory tract infections within the first 7 days after stroke onset; (2) modified Centers for Disease Control and Prevention (CDC) criteria are proposed for SAP as follows-probable SAP: CDC criteria met, but typical chest x-ray changes absent even after repeat or serial chest x-ray; definite SAP: CDC criteria met, including typical chest x-ray changes; (3) there is limited evidence for a diagnostic role of white blood cell count or C-reactive protein in SAP; and (4) there is insufficient evidence for the use of other biomarkers (eg, procalcitonin). CONCLUSIONS: Consensus operational criteria for the terminology and diagnosis of SAP are proposed based on the CDC criteria. These require prospective evaluation in patients with stroke to determine their reliability, validity, impact on clinician behaviors (including antibiotic prescribing), and clinical outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".