ArticleCancer management and research2026
Development and Validation of a Nomogram for Predicting Postoperative Deep Vein Thrombosis Risk in Patients After Laparoscopic Partial Nephrectomy.
Article in Cancer management and research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
Objective: To construct a nomogram model for individualized prediction of risk of deep vein thrombosis (DVT) in renal cell carcinoma (RCC) patients after laparoscopic partial nephrectomy (PN). Methods: A retrospective study was conducted on 556 RCC patients admitted to our hospital from January 2015 to January 2025. Patients were randomly divided into a modeling group (n=389) and a validation group (n=167) at a ratio of 7:3. The modeling group was further subdivided into DVT and non-DVT groups based on postoperative DVT occurrence. Clinical data were collected. Logistic regression was used to analyze the influencing factors. R software was used to construct the nomogram. ROC curves were generated to evaluate the discrimination ability of the nomogram. Decision curve analysis (DCA) was performed to assess its clinical utility. Results: Of 556 patients, 100 (17.98%) developed DVT, including 70 (17.99%) in the modeling group. Logistic regression identified age, operation time, time in bed, pneumoperitoneum pressure, duration of indwelling drains, total cholesterol (TC), and D-dimer as significant risk factors (P < 0.05). The area under the curve (AUC) was 0.889 for the modeling group and 0.866 for the validation group. Hosmer-Lemeshow test indicated good calibration (modeling group: χ²=7.120, P=0.714; validation group: χ²=7.058, P=0.724). DCA showed clinical utility for predicted probabilities between 0.08 and 0.96. Conclusion: Age, operation time, time in bed, pneumoperitoneum pressure, duration of indwelling drains, TC, and D-dimer are risk factors for DVT in patients after laparoscopic PN. The constructed nomogram demonstrates good predictive performance and can be used for individualized risk assessment of postoperative DVT in RCC patients.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.