Risk prediction of poor wound healing in patients with thoracoscopic lung cancer resection with drainage tube.

Yuguo Chen, Congying Ji, Chuan Huang, Ting Zhou, Xia Wang

Open access · greenAbstract read

In one paragraph

Article in American journal of cancer research, 2023. 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, top 54% of its field

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, 0 citations in OpenAlex.

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

5 authors at 1 institution in 1 country.

Yuguo ChenDressing Room of Surgical Outpatient Department, Beijing Hospital, National Center of Gerontology Beijing 100730, China.

Congying JiDressing Room of Surgical Outpatient Department, Beijing Hospital, National Center of Gerontology Beijing 100730, China.

Chuan HuangInstitute of Geriatric Medicine, Chinese Academy of Medical Sciences Beijing 100021, China.

Ting ZhouInstitute of Geriatric Medicine, Chinese Academy of Medical Sciences Beijing 100021, China.

Xia WangInstitute of Geriatric Medicine, Chinese Academy of Medical Sciences Beijing 100021, China.

Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work established a risk prediction (RP) model for poor wound healing (PWH) in patients with thoracoscopic lung cancer (LC) resection (TLCR) after drainage tube placement to explore its application effect. 359 patients with TLCR were categorized into a good wound healing group (GWH group, 275 cases) and a poor wound healing group (PWH group, 84 cases) based on incision healing condition. The independent prediction risk factors (IPRFs) of PWH were analyzed and a RP model was constructed. 70% of the patients were classified as the model group (Mod group) and 30% were in the validation group (Val group). Resolution of the RP model was evaluated by the area under receiver operating characteristic (ROC) curve (AUC). The Hosmer-Lemeshow goodness of fit (HLGF) test was employed to evaluate the calibration of RP model. Results from the multivariate logistic regression analysis (MLRA) showed that age, preoperative albumin levels, diabetes history, dressing change frequency, and type of wound cleaning fluid were independent risk factors (IRFs) for postoperative PWH (

Indexed as

Lung cancerpoor wound healingrisk factorsrisk prediction modelthoracoscopy

Identifiers

PMID38187071

PMCPMC10767345

OpenAlexW4390689848

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.