Use of laboratory and administrative data to understand the potential impact of human parainfluenza virus 4 on cases of bronchiolitis, croup, and pneumonia in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: Human Parainfluenza Virus (hPIV) causes severe respiratory illness in infants and adults. Our study describes the association of hPIV1-4 with bronchiolitis, croup, and pneumonia using retrospective laboratory, administrative and public health data. Due to issues including the historic lack of hPIV4 in some commercial respiratory virus panels, the description of the impact of hPIV4 on croup, bronchiolitis, and pneumonia at population levels has often been limited. This study will use routine clinical laboratory data, and administrative data to provide a preliminary description of the impact of hPIV4 on these diseases in our population. METHODS: A three year cohort of patients positive for hPIV was linked with data from physician visits and hospital admissions to define cases and hospitalization status. International Classification of Disease (ICD-9) codes were used to determine if cases had croup, bronchiolitis, and pneumonia. We also looked at differences in hospitalization status, age and gender among hPIV1-4. All statistical analysis was done using SPSS (Version 19.0.0, IBM Corp© 2010) and Graphpad Prism V6 (GraphPad Software, Inc., 2012). RESULTS: Only hPIV1 and hPIV4 specimens had positivity rates greater than 5 % of all specimens sent for respiratory virus panel testing. hPIV1 exhibited a biennial pattern while the pattern for hPIV3 was less interpretable due to lower positivity rates. Circulation patterns for hPIV2 and hPIV4 were not assessed due to the low positivity rates of theses specimens. From 2010 to 2013, there were 2300 hPIV cases with hPIV3 (46 %) being the most common, followed by hPIV1 (27 %), hPIV4 (16 %) and hPIV2 (11 %). The median age was 2 years for all hPIV types. Males were slightly greater than females for hPIV1 and hPIV2, with an equal distribution for hPIV3 and slightly more females than males for hPIV4. hPIV1 and hPIV2 had the highest or proportion of croup while hPIV3 and hPIV4 had the highest proportion of pneumonia. Within hPIV4 cases, distributions of diseases were; pneumonia (21 %, 95 % CI 17.1-25.7), bronchiolitis (18 %, 95 % CI 14.3-22.5), croup (2 %, 95 % CI 0.8-3.9), mixed illness of any of pneumonia, bronchiolitis or croup (4 %, 95 % CI 2.5-7.0) or other respiratory diseases (54 %, 95 % CI 49.1-59.6). CONCLUSIONS: We used laboratory and administrative data to undertake a descriptive analysis of the association of hPIV1-4 with croup, bronchiolitis and pneumonia. hPIV4 appears to be more associated more with bronchiolitis and pneumonia and less with croup in our population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".