Evidence map›Paper›PMID 27758078›Full record

ArticleInternational wound journal2017

Skin property can predict the development of skin tears among elderly patients: a prospective cohort study.

Yuiko Koyano, Gojiro Nakagami, Shinji Iizaka, Junko Sugama, Hiromi Sanada

Abstract read
In one paragraph

Article in International wound journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Sampling the skin surface chemistry for diagnosis and prognosis.Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society · 2022
    Pooled it
  2. Observational
  3. Review
  4. Reliability and validity of the Japanese version of the overall dry skin score in older patients.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2022
    Article
  5. Observational
  6. Models for predicting skin tears: A comparison.International wound journal · 2020
    Article
  7. Article
  8. Article
  9. Article
  10. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yuiko KoyanoDepartment of Gerontological Nursing/ Wound Care Management, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Gojiro NakagamiDepartment of Gerontological Nursing/ Wound Care Management, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Shinji IizakaDepartment of Gerontological Nursing/ Wound Care Management, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Junko SugamaWellness Promotion Science Center, Institute of Medical Pharmaceutical and Health Sciences, Kanazawa University, Ishikawa, Japan.
Hiromi SanadaDepartment of Gerontological Nursing/ Wound Care Management, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to identify skin properties that may be used to predict the development of a skin tear (ST) among elderly patients. A prospective cohort study was conducted among elderly patients aged 65 and older (N = 149) at a long-term medical facility in Japan over an 8-month period. Skin properties at baseline were measured on the forearm using a 20-MHz ultrasound scanner, which measured the thickness of the dermis layer and low-echogenic pixels, and skin blotting method, which evaluated the levels of collagen type IV, matrix metalloproteinase-2 and tumour necrosis factor-alpha. Adjusted hazard ratios (HRs) for the main confounders were obtained using the Cox proportional hazard model. A total of 52 STs were recorded among the 21 patients, resulting in an incidence rate of 1·13/1000 person-days. The predictor of STs was dermis thickness (HR = 0·52; 95% confidence interval = 0·33-0·81; P-value = 0·004). The cut-off point for dermis thickness was 0·80 mm (area under the curve = 0·77; 95% confidence interval = 0·66-0·88; P-value = 0·006). Our results suggest that measuring the dermis thickness at baseline is an easy and accurate way to identify a high-risk patient.

Indexed as

Skin Physiological PhenomenaAgedAged, 80 and overCohort StudiesFemaleForearmHumansJapanLacerationsMaleProportional Hazards ModelsProspective StudiesRisk FactorsRupture, SpontaneousSkinSkin AgingAgedLong-term careNursingTraumatic woundUltrasound scanner

Identifiers

PMID27758078
PMCPMC7950065

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.