Evidence map›Paper›PMID 36567839›Full record

ArticleJournal of medicine and life2022

Surgical treatment results in patients with defects of the integumentary tissues of the trunk and limbs of mechanical origin.

Olena Vasylivna Ponomarenko, Ludmila Nylsivna Serhieieva, Kyrylo Yuriiovych Parkhomenko

Abstract read
In one paragraph

Article in Journal of medicine and life, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Olena Vasylivna PonomarenkoDepartment of Medicine of Catastrophes, Military Medicine and Neurosurgery, Zaporizhzhia State Medical University, Zaporizhzhia, Ukraine.
Ludmila Nylsivna SerhieievaDepartment of Medical Physics, Biophysics and Higher Mathematics, Zaporizhzhia State Medical University, Zaporizhzhia, Ukraine.
Kyrylo Yuriiovych ParkhomenkoDepartment of General Practice Family Medicine and Internal Medicine, Kharkiv National Medical University, Kharkiv, Ukraine.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to develop and implement a universal method for the quantitative assessment of treatment effectiveness in patients with skin and underlying soft tissue defects of the trunk and extremities. The study involved 242 patients, including 46 patients with upper extremity injuries, 179 with lesions of lower extremity tissues, and 17 patients with defects of the integumentary tissues of the trunk. The greatest treatment effectiveness was observed in patients with upper limb injury: excellent result - 60.0%, good - 33.3%, unsatisfactory - 6.7% of patients. In the group of patients with lower extremity injuries, an excellent result was recorded in 19.6% of cases, good (58.1%), satisfactory (15.1%), and unsatisfactory in 7.2% of patients. In patients with trunk injuries, an excellent treatment result was obtained in 23.5%, good - 35.5%, satisfactory - 23.5%, and unsatisfactory - 17.6%. The universal quantitative method for evaluating treatment effectiveness in patients with various types of damage to the trunk and extremities tissues was proposed. This method makes it possible to objectively determine the level of medical service provided to each patient, which is of great importance in the context of medical service reorganization in the state.

Indexed as

Leg InjuriesPlastic Surgery ProceduresSoft Tissue InjuriesHumansLower ExtremitySkinSkin TransplantationTreatment Outcomeintegumentary tissue defectsreconstructive interventionsskintreatment effectivenesswound surface

Identifiers

PMID36567839
PMCPMC9762375

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Registered trials

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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.