Evidence map›Paper›PMID 39633406›Full record

ArticleBMC women's health2024

Exploring heterogeneity of perimenopause with application of multivariable analysis approaches.

Zhongyu Huang, Huazhi You, Lijuan Li, Shuang Wang, Zipan Lyu, Xiaoqin Zeng, Changyan Zhu, Minqing Li, Han Yan, Yaojuan He

Abstract read
In one paragraph

Article in BMC women's health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Zhongyu Huang *Institute of Clinical Medicine, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, 510000, China. zy1717086@163.com.
Huazhi You *First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510405, China.
Lijuan LiTraditional Chinese Medicine Clinic, Guangzhou Women and Children's Medical Center,Guangzhou Medical University, Guangzhou, 510632, China.
Shuang WangGynecology Clinic, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510632, China.
Zipan LyuSchool of Biological Sciences, Nanyang Technological University, Nanyang Ave, Singapore, 639798, Singapore.
Xiaoqin ZengGynecology Clinic, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510632, China.
Changyan ZhuGynecology Clinic, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510632, China.
Minqing LiGynecology Clinic, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510632, China.
Han YanSpinal Orthopedics Department, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, 510000, China. eyyanhan@scut.edu.cn.
Yaojuan HeGynecology Clinic, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510632, China. miracle_he@126.com.

Funding

Natural science fund of China 82004256The Guangdong Basic and Applied Basic Research Foundation No. 2023A1515011432The Guangzhou Science and Technology Planning Project No. 2023A04J0627
6 · The paper itself

Abstract

objectivesHeterogeneity of clinical appearance had made it a challenge to make individualized and comprehensive management of perimenopause. This study aimed to estimate the profiles over heterogenous appearances of perimenopause with application of latent variable analysis methods over an optimized multidimensional assessing framework.

methodsA two-phase clinical study was designed and advanced in the research center in Guangzhou, China. The assessing framework was developed over the initial item pool as integration of 4 scales including Insomnia severity index, Modified Kupperman index, Self-rating anxiety scale, and Self-rating depression scale. Validity and reliability of the instrument were evaluated and the psychometric properties of the items were estimated with multidimensional item response theory(MIRT). And then computer adaptive testing(CAT) was developed with the estimated model. We used latent profile analysis (LPA) to cluster patients into subgroups as patterns characterized by multidimensional latent trait scores. Finally, interpretability and efficiency were analyzed via comparison between the two assessing strategies.

resultThere were in total 336 patients diagnosed with perimenopause enrolled for the assessment. A conceptual framework was estimated consisting of 6 factors including sleep disturbance, mood swings, vasomotor symptoms, positive attitude towards life, multisystem abnormality, and fatigue. The construct validity was evaluated as optimized with CMIN/df = 1.814, GFI = 0.619, CFI = 0.721, TLI = 0.707 and RMSEA = 0.075. With scores in the simulated CAT, the 4 latent profiles model was estimated indicating the heterogeneity of perimenopause characterized by different severity of psychological and physical discomforts in the LPA.

conclusionThe quantitative paradigm raised in this study revealed the potential patterns presenting heterogeneity of perimenopause offering better interpretation for clinical assessment.

Indexed as

PerimenopausePsychometricsAdultAnxietyChinaDepressionFatigueFemaleHumansMiddle AgedMultivariate AnalysisReproducibility of ResultsSleep Initiation and Maintenance DisordersSurveys and QuestionnairesComputer adaptive testingFactor analysisLatent profile analysisMultidimensional item response theoryPerimenopause

Identifiers

PMID39633406
PMCPMC11619569

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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.