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Effectiveness of Telemedicine for Musculoskeletal Disorders: Umbrella Review

Effectiveness of Telemedicine for Musculoskeletal Disorders: Umbrella Review

In this umbrella review, we considered inclusion criteria according to the PICOS (population, intervention, comparison, outcomes, study design) format: patients with any musculoskeletal or orthopedic condition (population); any kind of interventions based on advanced technology systems named as “telemedicine,” “telerehabilitation,” “health technologies” and “digital medicine,” delivered both in synchronous and asynchronous modalities (intervention); in-person treatment or usual care or no treatment (comparison

Silvia Bargeri, Greta Castellini, Jacopo Antonino Vitale, Stefania Guida, Giuseppe Banfi, Silvia Gianola, Federico Pennestrì

J Med Internet Res 2024;26:e50090

Using Hypothesis-Led Machine Learning and Hierarchical Cluster Analysis to Identify Disease Pathways Prior to Dementia: Longitudinal Cohort Study

Using Hypothesis-Led Machine Learning and Hierarchical Cluster Analysis to Identify Disease Pathways Prior to Dementia: Longitudinal Cohort Study

To overcome the limitations of this literature, our hypothesis posits that the occurrence of specific disease patterns or clusters of symptoms, as well as their sequential development preceding the onset of dementia, greatly elevates the risk of developing this condition. Notably, medical records and claims data readily provide information on these symptoms and diseases, which could potentially facilitate clinical applications for preventing dementia in the real world.

Shih-Tsung Huang, Fei-Yuan Hsiao, Tsung-Hsien Tsai, Pei-Jung Chen, Li-Ning Peng, Liang-Kung Chen

J Med Internet Res 2023;25:e41858

Cervical Myelopathy and Social Media: Mixed Methods Analysis

Cervical Myelopathy and Social Media: Mixed Methods Analysis

To our knowledge, there exists only one study examining outcomes of DCM through the lens of patients living with the condition. The study, by Davies and colleagues [11], used an online survey of DCM patients to identify symptoms and handicaps caused by the illness. Otherwise, little is known about patient and caretaker perspectives on DCM [9,10]. One of the best ways to understand these perspectives is through social media, where patients often post about living with their disease [12].

Lior M Elkaim, Jordan J Levett, Farbod Niazi, Mohammed A Alvi, Nathan A Shlobin, Joseph R Linzey, Faith Robertson, Rakan Bokhari, Naif M Alotaibi, Oliver Lasry

J Med Internet Res 2023;25:e42097

The Use of Patient-Generated Health Data From Consumer-Grade Mobile Devices in Clinical Workflows: Protocol for a Systematic Review

The Use of Patient-Generated Health Data From Consumer-Grade Mobile Devices in Clinical Workflows: Protocol for a Systematic Review

The extracted data will be organized in the table by type of technology, type of condition, type of participants, and type of data being collected or used to identify any interesting findings, trends, relationships, and limitations that can assist in addressing the proposed review questions. A data coding strategy is suggested for the analysis. NVivo (QSR International) will be used to assist in the data coding strategy. The codes will be defined in accordance with the research objectives of the review.

Sharon Guardado Medina, Minna Isomursu

JMIR Res Protoc 2023;12:e39389

Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media

Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media

Patients who once had COVID-19 and experienced lasting symptoms referred to their condition as “long COVID” and themselves as “Long Haulers” [1]. Long COVID is defined as a persistence of symptoms for several weeks after the onset of COVID-19, with over 20% of those afflicted with it describing them after at least 4 weeks, and over 10% of patients after 3 months [2].

Amélia Déguilhem, Joelle Malaab, Manissa Talmatkadi, Simon Renner, Pierre Foulquié, Guy Fagherazzi, Paul Loussikian, Tom Marty, Adel Mebarki, Nathalie Texier, Stephane Schuck

JMIR Infodemiology 2022;2(2):e39849