Introduction: Implementing new approaches or new implants is always related with a certain learning curve in total hip arthroplasty (THA). Currently, many surgeons are switching to minimally invasive approaches combined with short stems for performing THA. Therefore, we aimed to asses and compare the learning curve of switching from an anterolateral Watson Jones approach (ALA) to a direct anterior approach (DAA) with the learning curve of switching from a neck-resecting to a partially neck-sparing short stem in cementless THA.
Materials And Methods: The first 150 consecutive THA performed through a DAA (Group A) and the first 150 consecutive THA using a partially neck-sparing short stem (Group B) performed by a single surgeon were evaluated within this retrospective cohort study. All cases were screened for surgery related adverse events (AE). Furthermore, the operative time of each surgery was evaluated and the learning curve assessed performing a cumulative sum (CUSUM) analysis.
Results: Overall, significantly more AE occurred in Group A compared to Group B (18.0% vs. 10.0%; p = 0.046). The sub-analysis of the AE revealed higher rates of periprosthetic joint infections (2.7% vs. 0.7%; p = 0.176), periprosthetic fractures (4.0% vs. 2.0%; p = 0.310) and overall revisions (4.7% vs. 1.3% p = 0.091) within Group A without statistical significance. The CUSUM analysis revealed a consistent reduction of operative time after 97 cases in Group A and 79 cases in Group B.
Conclusion: A significantly higher overall rate of AE was detected while switching approach compared to switching implant for performing THA. However, according to the results of this study, surgeons should be aware of the learning curve of the adoption to a new implant with different fixation philosophy as well.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11564367 | PMC |
http://dx.doi.org/10.1007/s00402-024-05518-9 | DOI Listing |
Front Oncol
December 2024
Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China.
Background: This study aimed to develop and validate a multiregional radiomic-based composite model to predict symptomatic radiation pneumonitis (SRP) in non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiation therapy (SBRT).
Materials And Methods: 189 patients from two institutions were allocated into training, internal validation and external testing cohorts. The associations between the SRP and clinic-dosimetric factors were analyzed using univariate and multivariate regression.
Front Oncol
December 2024
Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Objective: To evaluate the efficacy of a machine learning model for predicting prostate-specific antigen (PSA) persistence after radical prostatectomy (RP).
Methods: Data from 470 patients who underwent RP at the Affiliated Hospital of Qingdao University from January 2018 to June 2021 were retrospectively analyzed. Ten risk factors, including age, body mass index (BMI), preoperative PSA, biopsy Gleason score, total prostate specific antigen density (PSAD), clinical tumor stage, clinical lymph node status, seminal vesicle invasion, capsular invasion and positive surgical margin, were included in the analysis.
Ann Surg Open
December 2024
Department of Surgery, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
Objective: To compare nationwide outcomes of robotic liver resection (RLR) with laparoscopic liver resection (LLR).
Background: Minimally invasive liver resection is increasingly performed using the robotic approach as this could help overcome inherent technical limitations of laparoscopy. It is unknown if this translates to improved patient outcomes.
While deep brain stimulation (DBS) remains an effective therapy for Parkinson's disease (PD), sources of variance in patient outcomes are still not fully understood, underscoring a need for better prognostic criteria. Here we leveraged routinely collected T1-weighted (T1-w) magnetic resonance imaging (MRI) data to derive patient-specific measures of brain structure and evaluate their usefulness in predicting changes in PD medications in response to DBS. Preoperative T1-w MRI data from 231 patients with PD were used to extract regional measures of fractal dimension (FD), sensitive to the structural complexities of cortical and subcortical areas.
View Article and Find Full Text PDFIn the early stages of atrial fibrillation (AF), most cases are paroxysmal (pAF), making identification only possible with continuous and prolonged monitoring. With the advent of wearables, smartwatches equipped with photoplethysmographic (PPG) sensors are an ideal approach for continuous monitoring of pAF. There have been numerous studies demonstrating successful capture of pAF events, especially using deep learning.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!