Evidence map›Paper›PMID 42337727›Full record

ArticleBMC musculoskeletal disorders2026

The cervicovertebral angle as an associated factor of neck pain in female manufacturing workers: a dual-model cutoff analysis using logistic regression and decision trees.

Seung-Yoon Han, Ui-Jae Hwang, Yoon-Ji Lee, Il-Kyu Ahn, Yul-Ji Won, Ji-Hoo Moon, Oh-Yun Kwon

Abstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2026. 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

7 authors.

Seung-Yoon HanDepartment of Physical Therapy, The Graduate School, Yonsei University, Wonju, Gangwon-do, South Korea.
Ui-Jae HwangDepartment of Physical Therapy, College of Health Sciences, Laboratory of KEMA AI Research (KAIR), Yonsei University, Wonju, South Korea.
Yoon-Ji LeeDepartment of Physical Therapy, The Graduate School, Yonsei University, Wonju, Gangwon-do, South Korea.
Il-Kyu AhnDepartment of Physical Therapy, The Graduate School, Yonsei University, Wonju, Gangwon-do, South Korea.
Yul-Ji WonDepartment of Physical Therapy, The Graduate School, Yonsei University, Wonju, Gangwon-do, South Korea.
Ji-Hoo MoonDepartment of Physical Therapy, The Graduate School, Yonsei University, Wonju, Gangwon-do, South Korea.
Oh-Yun KwonDepartment of Physical Therapy, College of Health Sciences, Laboratory of Kinetic Ergocise Based on Movement Analysis, Yonsei University, Wonju, Gangwon-do, South Korea. kwonoy@yonsei.ac.kr.ORCID https://orcid.org/0000-0002-9699-768X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundForward head posture is commonly quantified using the cervicovertebral angle (CVA), a simple static postural measure used in clinical and occupational settings. Although reduced CVA has been associated with nonspecific neck pain (NSNP), its discriminative utility as a single postural metric remains uncertain because NSNP is multifactorial. This study aimed to examine the association between CVA and NSNP in female manufacturing workers and to identify exploratory CVA cutoff values using logistic regression (LR) and decision tree (DT) models.

methodsThis cross-sectional study included 135 female manufacturing workers, classified into an NSNP group (n = 64) and a non-pain group (n = 71). CVA was measured using standardized sagittal-view digital photography and ImageJ software. Unadjusted and adjusted binary LR analyses were performed to examine the association between CVA and NSNP. Receiver operating characteristic curve analysis was used to determine the optimal LR-based cutoff value using the Youden index. A DT algorithm was applied to identify hierarchical cutoff values. Model performance was evaluated using accuracy, sensitivity, specificity, and area under the curve (AUC).

resultsThe NSNP group showed a significantly smaller CVA than the non-pain group (51.16° ± 5.47° vs. 53.21° ± 4.11°, p = 0.015). In the unadjusted LR model, CVA was significantly associated with NSNP (odds ratio [OR] = 0.914, 95% confidence interval [CI]: 0.849-0.984, p = 0.017). This association remained significant after adjustment for age, height, weight, and body mass index (OR = 0.911, 95% CI: 0.830-0.999, p = 0.047). The LR model identified an optimal cutoff value of 51.40°, with an AUC of 0.623. The DT model identified a primary cutoff of 51.54° and a secondary threshold of 42.27°, with an AUC of 0.645.

conclusionsCVA was significantly associated with NSNP in female manufacturing workers, and both models identified a consistent primary cutoff of approximately 51.5°. However, CVA alone showed limited classification ability. Therefore, the identified cutoff values should be interpreted as supplementary screening references.

trial registrationThis study was registered by the Korea Clinical Research Information Service (KCT0011501).

Indexed as

Cervical VertebraeDecision TreesManufacturing IndustryNeck PainOccupational DiseasesPostureAdultCross-Sectional StudiesFemaleHumansLogistic ModelsMiddle AgedCervicovertebral angleCutoff valueDecision treeFemale workersForward head postureLogistic regressionNonspecific neck pain

Identifiers

PMID42337727
PMCPMC13548721

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.