ArticleTherapeutics and clinical risk management2024
Risk Factors for Digital Replantation Failure: A Nomogram Prediction Model.
Article in Therapeutics and clinical risk management, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
Who cites it
2 citing papers in PubMed.
- Composite inflammatory biomarkers for predicting vascular crisis after finger replantation: a two-center retrospective study identifying a promising inflammatory biomarker and its multidimensional evaluation.Frontiers in immunology · 2026Article
- Risk factors associated with postoperative necrosis after digital replantation: a systematic review and meta-analysis.Frontiers in surgery · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Study Design: A Retrospective study. Objective: Digital necrosis (DN) after replantation can cause some serious complication. Few articles focused on the risk factors of DN; therefore, we aim to investigate the risk factors of necrosis after multiple digital replantation. Methods: We collected the data of patients receiving multiple digital replantation in our hospital between Jan. 2017 and Jan. 2024. Based on the necrosis or not after replantation, patients with DN were as necrosis group (NG), and patients without DN were as success group (SG). The demographics, comorbidities, and admission laboratory examinations of patients were computed by univariate analysis, logistic regression analysis, and receiver operating characteristic (ROC) curve analysis. We then construct a nomogram prediction model, plot ROC curves, calibration curves, and DCA decision curves using R language software. Results: The survival rate in our study was 83.7% (278 of 332). Univariate analysis indicated that there were significant differences in the level of D-dimer, white blood cell, neutrophil, monocyte, monocyte-to-lymphocyte ratio, systemic immune-inflammation index, system inflammation response index, C-reactive protein (CRP), neutrophils/high density lipoprotein (HDL), monocytes/HDL were significantly higher in NG than in SG. However, logistic regression analysis showed that D-dimer and CRP were independent risk factors of DN, and we identified their cut-off values. Then, we constructed a nomogram prediction model with 0.7538 in AUC of the prediction model with good consistency in the correction curve and good clinical practicality by decision curve analysis. Conclusion: The level of D-dimer and CRP was found to be closely related to DN. We constructed a nomogram prediction model that can effectively predict DN in patients with multiple digital replantation.
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Registered trials
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 Socratic graph.