Use of Hydrocolloid Dressings in Preventing Pressure Ulcers in High-risk Patients: a Retrospective Cohort
Bibliographic record
Abstract
OBJECTIVES: This work sought to evaluate the association between using preventive hydrocolloid dressings and the onset of pressure ulcers in hospitalized patients. METHODS: Retrospective cohort study that included adult patients with high risk of pressure ulcers (PU) evaluated according to the Braden scale and who had been admitted with preventive purposes to a skin care program. The preventive care prescribed by the nursing staff included using hydrocolloid dressing plus conventional care (HD+CC) or only conventional care (CC), in a tier IV hospital in Bogotá, Colombia. Information was obtained from the clinical records of the demographic variables, health, and complications during hospitalization. RESULTS: One-hundred seventy subjects were included in the study (23 in HD+CC and 147 in CC). In all, 30.4% of the patients in the HD+CC group and 17% in the CC group had PU during follow up (p=0.15). The ratio between the type of preventive treatment received and the development of PU obtained a raw Hazzard ratio (HR) of 1.35 (CI95%: 0.58-3.14; p=0.48) and HR adjusted for confounding variables of 1.06 (CI95%: 0.29-3.84 p=0.92). CONCLUSIONS: Our results showed no superiority of HD+CC against CC in preventing PU in adult patients with high risk according to the Braden scale. The cohort study did not reveal significant differences between both interventions. It is necessary to promote and develop clinical trials to evaluate the effectiveness of using dressings and other conventional care in high-risk patients for this type of event.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".