ArticleInternational wound journal2020
Models for predicting skin tears: A comparison.
Article in International wound journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- Development and Validation of the Content of a Mobile Digital Board-Game Application, Constituting a Playful Tool for the Management of Friction Injuries.Nursing reports (Pavia, Italy) · 2026Article
- Development of a multivariable prognostic prediction model for skin tears in older nursing home residents.Scientific reports · 2025Article
- External validation of a predictive model for aged-related skin tears in Fitzpatrick skin types I-IV cohort.International wound journal · 2024Article
- Skin tear prevalence in an Australian acute care hospital: A 10-year analysis.International wound journal · 2022Article
- Models for predicting skin tears: A comparison.International wound journal · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A recently published model that predicted the risk of skin tears in older adults was compared with seven additional published models. Four models were excluded because of limitations in research design. Four models were compared for their relative predictive performance and accuracy using sensitivity, specificity, and the area under the curve (AUC), which involved using receiver-operating characteristic analysis. The predictive ability of the skin tear models differed with the AUC ranging between 0.673 and 0.854. Based on the predictive ability, the selection of models could lead to different clinical decisions and health outcomes. The model, which had been adjusted for potential confounders consisted of five variables (male gender, history of skin tears, history of falls, clinical skin manifestations of elastosis, and purpura), was found to be the most parsimonious for predicting skin tears in older adults (AUC 0.854; 81.7% sensitivity; 81.4% specificity). Effective models serve as important clinical tools for identifying older individuals at risk of skin tears and can better direct more timely and targeted prevention strategies that improve health outcomes and reduce health care expenditure.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.