ArticleInfection and drug resistance2026
The Analysis of Risk Factors of Stroke-Associated Pneumonia in Patients with Acute Stroke Based on Lasso Regression and the Construction of a Nomogram Prediction Model.
Article in Infection and drug resistance, 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To identify the risk factors for stroke-associated pneumonia (SAP) in patients with acute cerebrovascular stroke (ACS) using LASSO regression analysis and to construct a nomogram-based prediction model. Methods: Clinical data of 253 patients with ACS admitted to our hospital between March 2022 and May 2024 were retrospectively collected as the modeling cohort. In addition, clinical data of 143 patients with ACS admitted between June 2024 and August 2025 were collected as the validation cohort. Patients were divided into the SAP group and the non-SAP group according to the occurrence of SAP. Results: Logistic regression analysis of variables selected by LASSO regression demonstrated that age, diabetes mellitus, NIHSS score, nasogastric tube placement, dysphagia, neutrophil-to-lymphocyte ratio (NLR), systemic inflammation response index (SIRI), and hypoproteinemia were independent risk factors for SAP in patients with ACS (all P < 0.05). In internal validation, the area under the receiver operating characteristic curve (AUC) was 0.907, the Hosmer-Lemeshow test showed χ Conclusion: The nomogram model constructed based on LASSO regression analysis demonstrates good discriminative ability and potential clinical applicability for predicting SAP in patients with ACS.
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.