Evidence map›Paper›PMID 36030211›Full record

ArticleBMC cardiovascular disorders2022

Development and validation of a predictive model for adverse left ventricular remodeling in NSTEMI patients after primary percutaneous coronary intervention.

Lili Wang, Tao Liu, Chaofan Wang, Haochen Xuan, Xianzhi Xu, Jie Yin, Xiaoqun Li, Junhong Chen, Dongye Li, Tongda Xu

Abstract read
In one paragraph

Article in BMC cardiovascular disorders, 2022. 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.

Lili Wang *Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221000, Jiangsu, China.
Tao Liu *Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221000, Jiangsu, China.
Chaofan WangDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221000, Jiangsu, China.
Haochen XuanDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221000, Jiangsu, China.
Xianzhi XuSchool of Stomatology, Xuzhou Medical University, Xuzhou, 221000, Jiangsu, China.
Jie YinDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221000, Jiangsu, China.
Xiaoqun LiDepartment of General Practice, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221000, Jiangsu, China.
Junhong ChenDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221000, Jiangsu, China.
Dongye LiDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221000, Jiangsu, China.
Tongda XuDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221000, Jiangsu, China. xutongda3004@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTo develop and validate clinical evaluators that predict adverse left ventricular remodeling (ALVR) in non-ST-elevation myocardial infarction (NSTEMI) patients after primary percutaneous coronary intervention (PCI).

methodsThe retrospective study analyzed the clinical data of 507 NSTEMI patients who were treated with primary PCI from the Affiliated Hospital of Xuzhou Medical University and the Second Affiliated Hospital of Xuzhou Medical University, between January 1, 2019 and September 31, 2021. The training cohort consisted of patients admitted before June 2020 (n = 287), and the remaining patients (n = 220) were assigned to an external validation cohort. The endpoint event was the occurrence of ALVR, which was described as an increase ≥ 20% in left ventricular end-diastolic volume (LVEDV) at 3-4 months follow-up CMR compared with baseline measurements. The occurrence probability of ALVR stemmed from the final model, which embodied independent predictors recommended by logistic regression analysis. The area under the receiver operating characteristic curve (AUC), Calibration plot, Hosmer-Lemeshow method, and decision curve analysis (DCA) were applied to quantify the performance.

resultsIndependent predictors for ALVR included age (odds ratio (OR): 1.040; 95% confidence interval (CI): 1.009-1.073), the level of neutrophil to lymphocyte ratio (OR: 4.492; 95% CI: 1.906-10.582), the cardiac microvascular obstruction (OR: 3.416; 95% CI: 1.170-9.970), peak global longitudinal strain (OR: 1.131; 95% CI: 1.026-1.246), infarct size (OR: 1.082; 95% CI: 1.042-1.125) and left ventricular ejection fraction (OR: 0.925; 95% CI: 0.872-0.980), which were screened by regression analysis then merged into the nomogram model. Both internal validation (AUC: 0.805) and external validation (AUC: 0.867) revealed that the prediction model was capable of good discrimination. Calibration plot and Hosmer-Lemeshow method showed high consistency between the probabilities predicted by the nomogram (P = 0.514) and the validation set (P = 0.762) and the probabilities of actual occurrence. DCA corroborated the clinical utility of the nomogram.

conclusionsIn this study, the proposed nomogram model enabled individualized prediction of ALVR in NSTEMI patients after reperfusion and conduced to guide clinical therapeutic schedules.

Indexed as

Non-ST Elevated Myocardial InfarctionPercutaneous Coronary InterventionST Elevation Myocardial InfarctionHumansPredictive Value of TestsRetrospective StudiesStroke VolumeVentricular Function, LeftVentricular RemodelingAdverse left ventricular remodelingNomogram modelNon-ST-elevation myocardial infarctionPercutaneous coronary intervention

Identifiers

PMID36030211
PMCPMC9420298

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.