Efficacy of supervised self-reduction vs. physician-assisted techniques for anterior shoulder dislocations: a systematic review and meta-analysis.

BACKGROUND AND OBJECTIVE: Reduction manipulation using self-reduction procedures such as Stimson, Milch, and Boss-Holtzach should be easy and effective and also require less force, pain medication, and outside assistance. This technique should not cause damage to arteries, nerves, or shoulder joint components. Self-reduction is straightforward and can be done in clinics, making it ideal for people who suffer from shoulder joint dislocation frequently. The goal of this study is to compare the effectiveness of supervised self-reduction procedures vs. physician-assisted treatments in the treatment of anterior shoulder dislocations. METHOD: We conducted a comprehensive search on PubMed, Scopus, Web of Science, and Cochrane up to March 22, 2023, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Relevant articles were reviewed, with a focus on studies comparing supervised self-reduction techniques to physician-assisted techniques in cases of anterior shoulder dislocation. RESULTS: Four papers in all were included in the meta-analysis. One prospective trial, one case-control study, one randomized clinical trial, and one retrospective trial made up these studies. The studies involved 283 patients in the physician-assisted group and 180 patients in the supervised self-reduction group. They were carried out in four European countries: Italy, Germany, Portugal, and Spain. The success rate of supervised self-reduction techniques was significantly higher, with an odds ratio of 2.71 (95% CI 1.25-5.58, p-value = 0.01). Based on the Visual Analog Scale (VAS) score, the physician-assisted group reported significantly higher maximum pain, with a mean difference of 1.98 (95% CI 1.24-2.72, p-value < 0.01). The self-reduction approaches exhibit shorter reduction time in comparison to physician-assisted groups. In addition, the self-reduction groups do not document any complications. Based on the GRADE system, the level of assurance in the evidence was high. CONCLUSION: Supervised self-reduction techniques outperform in terms of success rate and reduction-related maximum pain. These techniques could be used as an effective first-line treatment for anterior shoulder dislocation, potentially reducing the need for analgesics and emergency room visits.

Predicting the Outcome and Survival of Patients with Spinal Cord Injury Using Machine Learning Algorithms: A Systematic Review.

BACKGROUND: Spinal cord injury (SCI) is a significant public health issue, leading to physical, psychological, and social complications. Machine learning (ML) algorithms have shown potential in diagnosing and predicting the functional and neurologic outcomes of subjects with SCI. ML algorithms can predict scores for SCI classification systems and accurately predict outcomes by analyzing large amounts of data. This systematic review aimed to examine the performance of ML algorithms for diagnosing and predicting the outcomes of subjects with SCI. METHODS: The literature was comprehensively searched for the pertinent studies from inception to May 25, 2023. Therefore, electronic databases of PubMed, Embase, Scopus, and Web of Science were systematically searched with individual search syntax. RESULTS: A total of 9424 individuals diagnosed with SCI across multiple studies were analyzed. Among the 21 studies included, 5 specifically aimed to evaluate diagnostic accuracy, while the remaining 16 focused on exploring prognostic factors or management strategies. CONCLUSIONS: ML and deep learning (DL) have shown great potential in various aspects of SCI. ML and DL algorithms have been employed multiple times in predicting and diagnosing patients with SCI. While there are studies on diagnosing acute SCI using DL algorithms, further research is required in this area.

Pre-Hospital and Post-Hospital Quality of Care in Traumatic Spinal Column and Cord Injuries in Iran.

STUDY DESIGN: A retrospective study. OBJECTIVES: The quality of care (QoC) for spinal column/cord injury patients is a major health care concern. This study aimed to implement the QoC assessment tool (QoCAT) in the National Spinal Cord/Column Injury Registry of Iran (NSCIR-IR) to define the current state of pre- and post-hospital QoC of individuals with Traumatic Spinal Column and Spinal Cord Injuries (TSC/SCIs). METHODS: The QoCAT, previously developed by our team to measure the QoC in patients with TSC/SCIs, was implemented in the NSCIR-IR. The pre-hospital QoC was evaluated through a retrospective analysis of NSCIR-IR registry data. Telephone interviews and follow-ups of patients with SCI evaluated the QoC in the post-hospital phase. RESULTS: In the pre-hospital phase, cervical collars and immobilization were implemented in 46.4% and 48.5% of the cases, respectively. Transport time from the scene to the hospital was documented as <1 hour and <8 hours in 33.4% and 93.9% of the patients, respectively. Post-hospital indicators in patients with SCI revealed a first-year mortality rate of 12.5% (20/160), a high incidence of secondary complications, reduced access to electrical wheelchairs (4.2%) and modified cars (7.7%), and low employment rate (21.4%). CONCLUSION: These findings revealed a significant delay in transport time to the first care facilities, low use of immobilization equipment indicating low pre-hospital QoC. Further, the high incidence of secondary complications, low employment rate, and low access to electrical wheelchairs and modified cars indicate lower post-hospital QoC in patients with SCI. These findings imply the need for further planning to improve the QoC for patients with TSC/SCIs.