Purpose: Percutaneous endoscopic lumbar interbody fusion (PELIF) is one of the least invasive procedures for lumbar degenerative disorders (LDD). There is limited knowledge of the learning curve for PELIF.
Methods: A total of 93 consecutive patients who underwent PELIF performed by a single spine surgeon for LDD failed with conservative treatment were retrospectively reviewed. The case series was split into three groups based on timing: A (earliest third of patients); B (middle third of patients); and C (latest third of patients). The following were also recorded: operating time, X-ray exposure time, complications, radiologic fusion rates, pre- and postoperative patient-reported outcome measures (PROMs) scores (visual analogue scale (VAS) for back pain, VAS for leg pain, Japanese Orthopaedic Association, Oswestry Disability Index and MacNab criteria), length of hospital stay, and need for revision surgeries. A learning curve was then developed by a logarithmic curve-fit regression analysis.
Results: The operative time gradually decreased over time, and an asymptote was reached after about 25 cases. Compared with group B or C, group A had significantly longer operative time, significantly longer length of hospital stay, needed significantly more x-ray exposure time. Though not significantly different, there are fewer complications and revision surgeries over time. There is no significant difference over time in PROMs scores except for the VAS back scores.
Conclusions: PELIF is an alternative for minimal invasive surgery for LDD, PELIF presents a learning curve to the practicing spine surgeon with regard to operative time, x-ray exposure time, length of hospital stay, clinical PROMs and radiographic outcomes and complications. The presented PELIF learning curve provided valuable insight to surgeons interested in performing this surgery.
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http://dx.doi.org/10.1186/s13018-023-03682-z | DOI Listing |
Exp Biol Med (Maywood)
January 2025
Department of Pediatric Surgery, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease with a poor prognosis. Its non-specific clinical symptoms make accurate prediction of disease progression challenging. This study aimed to develop molecular-level prognostic models to personalize treatment strategies for IPF patients.
View Article and Find Full Text PDFJAMIA Open
February 2025
Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN 55905, United States.
Objectives: In the general hospital wards, machine learning (ML)-based early warning systems (EWSs) can identify patients at risk of deterioration to facilitate rescue interventions. We assess subpopulation performance of a ML-based EWS on medical and surgical adult patients admitted to general hospital wards.
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Front Immunol
January 2025
Department of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Background: Sepsis is an uncontrolled reaction to infection that causes severe organ dysfunction and is a primary cause of ARDS. Patients suffering both sepsis and ARDS have a poor prognosis and high mortality. However, the mechanisms behind their simultaneous occurrence are unclear.
View Article and Find Full Text PDFFront Oncol
December 2024
NeuroRadiology Unit, Ospedale del Mare, Azienda Sanitaria Locale Napoli 1 Centro (ASL NA1 Centro), Naples, Italy.
Introduction: Precision medicine refers to managing brain tumors according to each patient's unique characteristics when it was realized that patients with the same type of tumor differ greatly in terms of survival, responsiveness to treatment, and toxicity of medication. Precision diagnostics can now be advanced through the establishment of imaging biomarkers, which necessitates quantitative image acquisition and processing. The VASARI (Visually AcceSAble Rembrandt Images) manual annotation methodology is an ideal and suitable way to determine the accurate association between genotype and imaging phenotype.
View Article and Find Full Text PDFBackground: Diagnosis of cardiac amyloidosis (CA) is often missed or delayed due to confusion with other causes of increased left ventricular wall thickness. Conventional transthoracic echocardiographic measurements like global longitudinal strain (GLS) has shown promise in distinguishing CA, but with limited specificity. We conducted a study to investigate the performance of a computer vision detection algorithm in across multiple international sites.
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