ArticleInternational journal of environmental research and public health2022
Is It Possible to Predict the Length of Stay of Patients Undergoing Hip-Replacement Surgery?
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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.
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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.
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Who cites it
6 citing papers in PubMed.
- Utilizing a nomogram to predict the one-year postoperative mortality risk for geriatric patients with a hip fracture.Scientific reports · 2023Article
- Fast Track Protocols and Early Rehabilitation after Surgery in Total Hip Arthroplasty: A Narrative Review.Clinics and practice · 2023Review
- Improving Resource Utilization for Arthroplasty Care by Leveraging Machine Learning and Optimization: A Systematic Review.Arthroplasty today · 2023Article
- Implementation of Predictive Algorithms for the Study of the Endarterectomy LOS.Bioengineering (Basel, Switzerland) · 2022Article
- Risk Factors Analysis of Surgical Infection Using Artificial Intelligence: A Single Center Study.International journal of environmental research and public health · 2022Article
- Predictive model for prolonged length of hospital stay in patients with osteoporotic femoral neck fracture: A 5-year retrospective study.Frontiers in medicine · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The proximal fracture of the femur and hip is the most common reason for hospitalization in orthopedic departments. In Italy, 115,989 hip-replacement surgeries were performed in 2019, showing the economic relevance of studying this type of procedure. This study analyzed the data relating to patients who underwent hip-replacement surgery in the years 2010-2020 at the "San Giovanni di Dio e Ruggi d'Aragona" University Hospital of Salerno. The multiple linear regression (MLR) model and regression and classification algorithms were implemented in order to predict the total length of stay (LOS). Lastly, using a statistical analysis, the impact of COVID-19 was evaluated. The results obtained from the regression analysis showed that the best model was MLR, with an R
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Registered trials
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