Evidence mapPaperPMID 39635335Full record

ArticleJournal of clinical medicine research2024

Construction of a Clinical Prediction Model for Complications After Femoral Head Replacement Surgery.

Ke Wei Li, Shuai Rong, Hao Li

Abstract read
In one paragraph

Article in Journal of clinical medicine research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ke Wei LiPediatric Orthopedics, The Third Hospital of Shijiazhuang, Shijiazhuang City, Hebei Province, China.
Shuai RongPediatric Orthopedics, The Third Hospital of Shijiazhuang, Shijiazhuang City, Hebei Province, China.
Hao LiPediatric Orthopedics, The Third Hospital of Shijiazhuang, Shijiazhuang City, Hebei Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: While femoral head replacement is widely used with remarkable efficacy, the complexity and diversity of postoperative complications pose a serious prognostic challenge. There is an urgent need to develop a clinical prediction model that can integrate multiple factors and accurately predict the risk of postoperative complications to guide clinical practice and optimize patient management strategies. This study is dedicated to constructing a postoperative complication prediction model based on statistics and machine learning techniques, in order to provide patients with a safer and more effective treatment experience. Methods: A total of 186 patients who underwent femoral head replacement in the Orthopedic Department of our hospital were collected in this study. Forty-two of the patients had at least one postoperative complication, and 144 had no complications. The preoperative and postoperative data of patients were collected separately and medical history was collected to study the correlation factors affecting the occurrence of postoperative complications in patients and to establish a prediction model. Results: Possibly relevant factors were included in a one-way logistic regression, which included the patient's gender, age, body mass index, preoperative diagnosis of the mode of injury, osteoporosis or lack thereof, as well as medical history, surgical-related information, and laboratory indices. After analyzing the results, it was concluded that operation time, alanine transaminase (ALT), aspartate aminotransferase (AST), white blood cell count, serum albumin, and osteoporosis, were the risk factors affecting the development of complications after femoral head replacement in patients (P < 0.2). The data obtained were further included in a multifactorial regression, and the results showed that operation time, AST, white blood cell count, serum albumin, and osteoporosis were independent risk factors for complications after the patients underwent femoral head replacement (P < 0.05). Conclusion: Based on the results of this study, five factors, including duration of surgery, AST, white blood cell count, serum albumin, and osteoporosis, were identified as independent risk factors for complications after patients underwent femoral head replacement. In addition, the prediction model developed in this study has a high scientific and clinical application value, providing clinicians and patients with an important tool for assessing the risk of complications after affected femoral head replacement.

Indexed as

ComplicationsFemoral head replacement surgeryLine graphLogistic regressionRisk factor

Identifiers

PMID39635335
PMCPMC11614405

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.