Effects of seasonal changes in temperature and humidity on incidence of necrotizing soft tissue infections in Halifax, Canada, 2001-2015
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To explore weather seasonal variation in Necrotizing soft tissue infections (NSTI) in Halifax, Nova Scotia, Canada could be attributed to changes in environmental factors of temperature and humidity specifically. METHODS: A retrospective chart review of NSTIs between 2001 and 2015. Regional temperature and humidity data were obtained from the Environment Canada Agency, Halifax, Canada. Chi-square was used for categorical variables and continuous data was used for correlation analyses. Logistic regression was performed to analyze mortality. Results: Of 170 NSTI patients identified, more presented from March to July, especially when the temperature was greater than 10ºC. Higher incidence per 100,000 persons correlated with increased monthly temperatures (p less than 0.01). Monthly NSTI incidence was inversely related to mean humidity (p=0.005). Causative organism was associated with mean weekly temperature (p less than 0.01) but not humidity (p=0.66). Low body mass index, higher American Society of Anesthesiologists class, long intensive care unit stay, and shorter overall hospital stay were associated with mortality. No correlation was identified between temperature and humidity and mortality. CONCLUSION: This study demonstrates a tendency toward more frequent cases of NSTI with warmer, but less humid weather, without effect on severity or mortality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it