The lack of therapeutic options to fight Covid-19 has contributed to the current global pandemic. Despite the emergence of effective vaccines, development of broad-spectrum antiviral treatment remains a significant challenge, in which antimicrobial photodynamic therapy (aPDT) may play a role, especially at early stages of infection. aPDT of the nares with methylene blue (MB) and non-thermal light has been successfully utilized to inactivate both bacterial and viral pathogens in the perioperative setting. Here, we investigated the effect of MB-aPDT to inactivate human betacoronavirus OC43 and SARS-CoV-2 in vitro and in a proof-of-principle COVID-19 clinical trial to test, in a variety of settings, the practicality, technical feasibility, and short-term efficacy of the method. aPDT yielded inactivation of up to 6-Logs in vitro, as measured by RT-qPCR and infectivity assay. From a photo-physics perspective, the in vitro results suggest that the response is not dependent on the virus itself, motivating potential use of aPDT for local destruction of SARS-CoV-2 and its variants. In the clinical trial we observed variable effects on viral RNA in nasal-swab samples as assessed by RT-qPCR attributed to aPDT-induced RNA fragmentation causing falsely-elevated counts. However, the viral infectivity in clinical nares swabs was reduced in 90% of samples and undetectable in 70% of samples. This is the first demonstration based on quantitative clinical viral infectivity measurements that MB-aPDT is a safe, easily delivered and effective front-line technique that can reduce local SARS-CoV-2 viral load.

Percutaneous vertebroplasty produces higher intravertebral pressures in vertebrae containing a simulated lytic metastasis than in intact vertebrae. Pressures generated in the tumor specimens are sufficiently elevated to cause embolic phenomena.

ImportanceArtificial intelligence (AI) enables powerful models for establishment of clinical diagnostic and prognostic tools for hip fractures; however the performance and potential impact of these newly developed algorithms are currently unknown.ObjectiveTo evaluate the performance of AI algorithms designed to diagnose hip fractures on radiographs and predict postoperative clinical outcomes following hip fracture surgery relative to current practices.Data SourcesA systematic review of the literature was performed using the MEDLINE, Embase, and Cochrane Library databases for all articles published from database inception to January 23, 2023. A manual reference search of included articles was also undertaken to identify any additional relevant articles.Study SelectionStudies developing machine learning (ML) models for the diagnosis of hip fractures from hip or pelvic radiographs or to predict any postoperative patient outcome following hip fracture surgery were included.Data Extraction and SynthesisThis study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses and was registered with PROSPERO. Eligible full-text articles were evaluated and relevant data extracted independently using a template data extraction form. For studies that predicted postoperative outcomes, the performance of traditional predictive statistical models, either multivariable logistic or linear regression, was recorded and compared with the performance of the best ML model on the same out-of-sample data set.Main Outcomes and MeasuresDiagnostic accuracy of AI models was compared with the diagnostic accuracy of expert clinicians using odds ratios (ORs) with 95% CIs. Areas under the curve for postoperative outcome prediction between traditional statistical models (multivariable linear or logistic regression) and ML models were compared.ResultsOf 39 studies that met all criteria and were included in this analysis, 18 (46.2%) used AI models to diagnose hip fractures on plain radiographs and 21 (53.8%) used AI models to predict patient outcomes following hip fracture surgery. A total of 39 598 plain radiographs and 714 939 hip fractures were used for training, validating, and testing ML models specific to diagnosis and postoperative outcome prediction, respectively. Mortality and length of hospital stay were the most predicted outcomes. On pooled data analysis, compared with clinicians, the OR for diagnostic error of ML models was 0.79 (95% CI, 0.48-1.31; P = .36; I2 = 60%) for hip fracture radiographs. For the ML models, the mean (SD) sensitivity was 89.3% (8.5%), specificity was 87.5% (9.9%), and F1 score was 0.90 (0.06). The mean area under the curve for mortality prediction was 0.84 with ML models compared with 0.79 for alternative controls (P = .09).Conclusions and RelevanceThe findings of this systematic review and meta-analysis suggest that the potential applications of AI to aid with diagnosis from hip radiographs are promising. The performance of AI in diagnosing hip fractures was comparable with that of expert radiologists and surgeons. However, current implementations of AI for outcome prediction do not seem to provide substantial benefit over traditional multivariable predictive statistics.

This event is an accredited group learning activity as defined by the Maintenance of Certification Program of the Royal College of Physicians and Surgeons of Canada. The Annual Scientific Conference of the Canadian Spine Society provides a yearly review of spine care in Canada. This year the first combined conference widens its perspective to encompass participation by both the Spine Society of Australia and the New Zealand Orthopaedic Spine Society. There is also an increased contribution from paediatric spine. In addition to a review of surgical advances, the agenda covers a range of non-operative innovations and epidemiological studies. Presentations by members of the three societies will highlight the similarities, differences and common problems in three separate health care systems. Of particular interest are the management of neuromuscular spinal deformity and motion preserving surgery for degenerative back pain. A special focus is the development of national spine registries. Parallel efforts in all three countries will be compared and the conference will consider the possibility of international cooperation.

Radiographic reporting in adolescent idiopathic scoliosis:Is there a discrepancy comparing radiologists' reports and surgeons' assessments? Karamjot Sidhu,

No abstract

No abstract

Background:The beneficial treatment effect surgery demonstrates over conservative care for radiculopathy secondary to acute lumbar disc herniation (LDH), occurs in the first 3 to 6 months; thereafter outcomes are recognized to be similar. This is not surprising given the favourable natural history; 90% will experience gradual resolution of their symptoms within 4 months. In Canada, owing to the inherent wait time to see a surgeon and the referring physician's expectation that most patients will improve without surgery, symptomatic patients presenting to surgeons are often the 10% that have remained symptomatic longer than the expected 4 months. The purpose is to determine whether surgery is superior to conservative care in a patient population that has had persistent symptoms for more than 4 months, and therefore create a study population which is generalizable to the Canadian health care experience. Methods: This single blinded (assessor) RCT enrolled 18-to 60-year-old patients with a unilateral, single radiculopathy from a posterolateral L4-5 or L5-S1 disc herniation. Radiculopathy duration was longer than 4 months but less than 12 months. Patients on a waiting list to see surgeons at 1 academic hospital centre were randomized to early microdiscectomy or standardized nonoperative care, including medications, education, physiotherapy and steroid injections. Patients were excluded if they had previously received these conservative modalities. The primary outcome was intensity of sciatica (scale 0-10) measured at 6 months following randomization. Secondary outcome measures included back pain, Oswestry Disability Index (ODI), SF-36, work status and satisfaction. Results: This interim analysis reports on 40 nonoperative and 39 surgical patients. No difference existed between their demographic or preoperative data. At 6 months follow-up 32 of 39 surgical patients and 36 of 40 nonoperative patients had data available. Treatment effect for all outcome measures favoured surgery for the intent-to-treat, as-treat and last-value carried forward analysis (p < 0.05). To date 13 of 40 nonoperative patients have undergone microdiscectomy (performed after the primary outcome measure of 6 mo); they have had persistent inferior scores than early surgical patients (p < 0.05). Conclusion: At the interim analysis microdiscectomy is superior to nonoperative care for patients presenting with sciatica secondary to LDH. This study will continue to confirm robustness and validity of results.