Evidence map›Paper›PMID 38149163›Full record

ArticleCureus2023

Establishment and Clinical Application of the General Comfort Scale for Postoperative Lung Cancer Patients.

Lisha Jiang, Mingming Wang, Guowei Che

Abstract read
In one paragraph

Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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.

Lisha JiangDay Surgery Center, West China Hospital of Sichuan University, Chengdu, CHN.
Mingming WangDepartment of Cardio-Thoracic Surgery, Chengdu Second People's Hospital, Chengdu, CHN.
Guowei CheLung Cancer Center/Department of Thoracic Surgery, West China Hospital of Sichuan University, Chengdu, CHN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose The concept of enhanced recovery after surgery (ERAS) not only reflects rapid perioperative recovery but also focuses on the comfort experience of inpatients. This study intends to establish a clinically applicable general comfort questionnaire (GCQ) for patients with lung cancer after surgery and verify its clinical application effect. Methods The comfort index items for postoperative lung cancer were formed by combining previous research and literature, clinically applied comfort scales, and expert interviews. The Delphi method was used to conduct two rounds of expert consultations to determine the final index and establish a postoperative comfort scale for lung cancer patients. This scale was used to conduct a questionnaire survey on 200 patients to test the reliability and validity of the scale. Results The comfort scale contains 3 dimensions and 10 items and is easy to operate and evaluate in clinical applications. The Cronbach's α coefficient of the comfort scale is 0.801, and the scale content validity index (SCVI/ave) is 0.97. The common factor 1 and 2 characteristic roots of scale structural validity evaluation are 3.257 and 1.352 respectively, both greater than 1, with cumulative variance contribution rates of 32.57% and 13.52%. Pain and getting out of bed are the main factors influencing patient comfort. Conclusion The postoperative comfort scale for lung cancer patients has high clinical application reliability and validity. This study identified pain and mobility (early ambulation or getting out of bed) as the primary factors influencing the postoperative comfort of lung cancer patients.

Indexed as

delphi methodenhanced recovery after surgerygeneral comfort questionnairelung cancerpostoperative comfort scale for lung cancer patients

Identifiers

PMID38149163
PMCPMC10750135

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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.