Risultati per: Terapia del dolore da osteo-artropatie degenerative

Analizza le informazioni facciali

Utilizza un coniugato anticorpo-farmaco anti cellule tumorali

Finora tra 6 regioni prive. Il contributo del ‘Progetto Noemi’

8 italiani su 10 ignorano possa essere stesso dolore dei grandi

8 italiani su 10 ignorano possa essere stesso dolore dei grandi

La Commissione europea ha concesso il trasferimento alla Fondazione dell’autorizzazione all’immissione in commercio della terapia genica per l’immunodeficienza Ada-Scid. È la prima volta al mondo

Una bimba palestinese la prima curata con terapia genica

Introduction
Lumbar degenerative disease (LDD) is one of the most common reasons for patients to present with low back pain. Proper evaluation and treatment of patients with LDD are important, which clinicians perform using a variety of predictors for guidance in choosing the most appropriate treatment. Because evidence on which treatment is best for LDD is limited, the purpose of this study is to establish a clinical prediction model based on machine learning (ML) to accurately predict outcomes of patients with LDDs in the early stages by their clinical characteristics and imaging changes.

Methods and analysis
In this study, we develop and validate a clinical prognostic model to determine whether patients will experience complications within 6 months after percutaneous endoscopic lumbar discectomy (PELD). Baseline data will be collected from patients’ electronic medical records. As of now, we have recruited a total of 580 participants (n=400 for development, n=180 for validation). The study’s primary outcome will be the incidence of complications within 6 months after PELD. We will use an ML algorithm and a multiple logistic regression analysis model to screen factors affecting surgical efficacy. We will evaluate the calibration and differentiation performance of the model by the area under the curve. Sensitivity (Sen), specificity, positive predictive value and negative predictive value will be reported in the validation data set, with a target of 80% Sen. The results of this study could better illustrate the performance of the clinical prediction model, ultimately helping both clinicians and patients.

Ethics and dissemination
Ethical approval was obtained from the medical ethics committee of the Affiliated Hospital of Gansu University of Traditional Chinese Medicine (Lanzhou, China; No. 2022-57). Findings and related data will be disseminated in peer-reviewed journals, at conferences, and through open scientific frameworks.

Trial registration number
Chinese Clinical Trial Register (www.chictr.org.cn) No. ChiCTR2200064421.

Esperimento alla Cleveland Clinic, allevia preoccupazioni

Gli operatori: “Reazione sorprendente” con la bambola iconica

Gli operatori: “Reazione sorprendente” con la bambola iconica

Studio, 5 minuti in più scoprono pazienti a rischio effetti collaterali

Objectives
To explore whether a James Lind Alliance Priority Setting Partnership could provide insights on knowledge translation within the field of degenerative cervical myelopathy (DCM).

Design
Secondary analysis of a James Lind Alliance Priority Setting Partnership process for DCM.

Participants and setting
DCM stake holders, including spinal surgeons, people with myelopathy and other healthcare professionals, were surveyed internationally. Research suggestions submitted by stakeholders but considered answered were identified. Sampling characteristics of respondents were compared with the overall cohort to identify subgroups underserved by current knowledge translation.

Results
The survey was completed by 423 individuals from 68 different countries. A total of 22% of participants submitted research suggestions that were considered ‘answered’. There was a significant difference between responses from different stakeholder groups (p