Skin and soft tissue infections in hospitalized cancer patients
Bibliographic record
Abstract
OBJECTIVES: To assess the clinical and epidemiological characteristics of hospitalized cancer patients with skin and soft-tissue infections (SSTIs). METHODS: An observational retrospective study was conducted between March 2016 and December 2020 at the Oncology Department of King Saudi Medical City, Riyadh, Saudi Arabia. Patients with complicated and uncomplicated SSTIs were included. RESULTS: A total of 204 cancer patients with SSTIs were evaluated. The incidence of SSTIs was 1.67% (204/12,203). Breast cancer (39%) was the most common solid tumor in all patients with SSTIs. Exit site infection (n=84, 41.2%) was the most common SSTI in cancer patients, followed by wound infection (n=72, 35.3%), and cellulitis (n=44, 21.5%). The majority of patients received appropriate antimicrobial therapy (n=150, 73.5%). CONCLUSION: This study has shown a modest incidence of SSTIs in hospitalized cancer patients, with many of the patients received appropriate antimicrobial therapy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".