ArticleClinical interventions in aging2025
A Nomogram for Predicting Pulmonary Complications Following Laparoscopic Surgery in Elderly Patients After the COVID-19 Pandemic.
Article in Clinical interventions in aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed.
- Prediction of Postoperative Pulmonary Complications in Geriatric Patients with Hip Fracture Using Lung Ultrasonography Score and Diaphragmatic Mobility.Clinical interventions in aging · 2026Observational
- Risk Factors Analysis and Nomogram Prediction Model Construction for Pulmonary Infection After Laparoscopic Cholecystectomy.Infection and drug resistance · 2026Article
- Development and validation of a risk prediction model for postoperative pneumonia in elderly non-cardiac surgery patients: a retrospective cohort study.Scientific reports · 2025Article
- A Comparative Clinical Analysis of Esophagogastrostomy Versus Double-Tract Reconstruction Following Laparoscopic Proximal Gastrectomy.Juntendo medical journal · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Postoperative pulmonary complications (PPCs) are common and serious after laparoscopic surgery, better than cardiac complications in predicting long-term mortality after non-cardiac surgery. In the post-epidemic era, the specific incidence of PPCs and their risk factors remain unclear. Methods: This two-center retrospective study used the eligible patients' demographics and clinical characteristics to develop a prediction model. These patients who had undergone laparoscopic surgery from January 2023 to April 2024 were randomized into the training set and validation set. The main outcome was the incidence of PPCs. The multi-input processing method was used for missing data imputation. The variables with a Results: 278 patients (21.21%) developed PPCs. Surgical site and the comorbidities (except pulmonary diseases), pulmonary abnormalities, 24-h white blood cell count, and 24-h neutrophil percentage before surgery were independent risk factors for PPCs and used for the establishment of a nomogram prediction model for PPC risk in elderly patients. The AUC value, sensitivity, and specificity were 0.88, 75.4%, and 87.6% respectively in the model's ROC curve. Internal verification (AUC: 0.86) confirmed the model's good calibration and discrimination abilities. Clinical decision curve analysis showed that the model had a positive clinical net benefit within the risk threshold range of 0%~30%. Conclusion: This study identified the high-risk individuals of PPCs in elderly patients. PPC risk in elderly patients after laparoscopic surgery could be effectively reduced by optimizing surgical site selection, controlling preoperative comorbidities, adjusting preoperative lung conditions, and monitoring preoperative 24-h white blood cell count and neutrophil percentage.
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.