Augmented and virtual reality in spine surgery, current applications and future potentials

BACKGROUND CONTEXT: The field of artificial intelligence (AI) is rapidly advancing, especially with recent improvements in deep learning (DL) techniques. Augmented (AR) and virtual reality (VR) are finding their place in healthcare, and spine surgery is no exception. The unique capabilities and advantages of AR and VR devices include their low cost, flexible integration with other technologies, user-friendly features and their application in navigation systems, which makes them beneficial across different aspects of spine surgery. Despite the use of AR for pedicle screw placement, targeted cervical foraminotomy, bone biopsy, osteotomy planning, and percutaneous intervention, the current applications of AR and VR in spine surgery remain limited. PURPOSE: The primary goal of this study was to provide the spine surgeons and clinical researchers with the general information about the current applications, future potentials, and accessibility of AR and VR systems in spine surgery. STUDY DESIGN/SETTING: We reviewed titles of more than 250 journal papers from google scholar and PubMed with search words: augmented reality, virtual reality, spine surgery, and orthopaedic, out of which 89 related papers were selected for abstract review. Finally, full text of 67 papers were analyzed and reviewed. METHODS: The papers were divided into four groups: technological papers, applications in surgery, applications in spine education and training, and general application in orthopaedic. A team of two reviewers performed paper reviews and a thorough web search to ensure the most updated state of the art in each of four group is captured in the review. RESULTS: In this review we discuss the current state of the art in AR and VR hardware, their preoperative applications and surgical applications in spine surgery. Finally, we discuss the future potentials of AR and VR and their integration with AI, robotic surgery, gaming, and wearables. CONCLUSIONS: AR and VR are promising technologies that will soon become part of standard of care in spine surgery. (C) 2021 Published by Elsevier Inc

Journeys to Tadmor: History and Cultural Heritage in Palmyra and the Middle East

Posten inneholder 69 bilder som dokumenterer utstillingen.Katalog til utstillingen Reiser til Tadmor: Historie og kulturarv i Palmyra og Midtøsten, som ble vist på Bryggens Museum sommeren 2017.publishedVersio

Social Determinants of Health and Health Literacy in Orthopaedic Surgery

This thesis conducts a thorough exploration of the complex social determinants of health that affect orthopaedic patients, with a specific emphasis on health literacy. Through rigorous analysis and examination, it provides valuable insights into the prevalence of limited health literacy and the significant risk factors associated with it. Through the investigations in this thesis, a new understanding of the dangers posed by limited health literacy emerges, underscoring the critical importance of early identification of patients with low health literacy to improve health outcomes. Moreover, by evaluating the impact of limited health literacy on patient-reported outcome measures, it offers a vital perspective on how to improve aspects of patient-centered care that optimizes health outcomes. Furthermore, an evaluation of a self-reported health literacy screening measure is presented that offers potential for identifying patients with limited health literacy while being mindful of clinical resources. This screening tool can aid health care providers in personalizing patient care to meet the unique needs of those with low health literacy, thereby improving overall health equity. Overall, this thesis provides a wealth of information and insights into the social determinants of health and health literacy among orthopaedic patients, emphasizing the urgent need to identify and address these critical factors to achieve optimal health outcomes

The Influence of Patient Characteristics and Social Determinants of Health on Post-Operative Complications Following Achilles Tendon Ruptures

Category: Sports; Hindfoot Introduction/Purpose: While patient comorbidities are known to affect surgical complication rates after Achilles tendon rupture (ATR) repair, the correlation between social determinants of health (SDH) and postoperative complication rates is poorly understood. Two validated indices representative of SDH include the Area Deprivation Index (ADI), which ranks neighborhoods by social disadvantage, and the Social Vulnerability Index (SVI), which uses 16 US census variables to identify communities at risk before or after natural disasters. In this study, we aim to determine whether there is any correlation between patient demographics, SDH, and postoperative complication rates following surgical treatment of ATR. Methods: A retrospective chart review identified 521 patients who underwent surgical repair of an acute ATR between 2015 and 2021. Inclusion criteria included age ≥ 18 years, a minimum 30 day follow up, and patients who underwent acute repair within 28 days of ATR. Collected variables included patient demographics, time to surgery (TTS), injury characteristics, and postoperative complications sub-categorized into venous thromboembolism (VTE), re-rupture, surgical site infection (SSI), wound dehiscence, and sural nerve injury. SDH variables included age, race, smoking status, insurance status, level of education, and employment status. The ADI and SVI measurements of patient deprivation or vulnerability were also extracted from the data. A univariate regression test was performed to determine the correlation between each complication and each SDH indicator. Variables that showed significance (p < 0.05) were then included in a multivariate regression to determine the correlation coefficients and significance. Results: Sixty-eight complications occurred in 59 patients (11.3%). Multivariate regression showed higher ADI was associated with VTE occurrence (OR = 0.39, 95% CI: 0.16 –0.91, p = 0.03). Female patients and open surgical approach correlated with decreased VTE occurrence (OR = 0.24, 95% CI: 0.09 – 0.66, p< 0.01), (OR = 0.15, 95% CI: 0.04 – 0.55, p< 0.01), respectively. Higher BMI was associated with VTE (OR = 1.62, 95% CI: 1.05 – 2.51, p=0.03) and re-rupture (OR = 3.86, 95% CI: 1.51 – 9.08, p< 0.01). Women experienced decreased wound dehiscence rates (OR = 0.25, 95% CI: 0.09 – 0.69, p< 0.01) and SSI (OR = 0.31, 95% CI: 0.11 – 0.93, p=0.04) compared to men. TTS correlated with sural nerve injuries (OR=2.09, 95% CI: 1.32 – 3.31, p< 0.01). Conclusion: This study found that SDH, such as ADI, impacts complication rates after ATR repair, though the nature of this relationship remains unclear. Patient demographic and anthropometric factors such as gender and BMI also have an impact. Future studies should include a larger, more diverse sample population to better understand the impact of these factors on surgical outcomes

Availability and reporting quality of external validations of machine-learning prediction models with orthopedic surgical outcomes: a systematic review

Background and purpose — External validation of machine learning (ML) prediction models is an essential step before clinical application. We assessed the proportion, performance, and transparent reporting of externally validated ML prediction models in orthopedic surgery, using the Transparent Reporting for Individual Prognosis or Diagnosis (TRIPOD) guidelines. Material and methods — We performed a systematic search using synonyms for every orthopedic specialty, ML, and external validation. The proportion was determined by using 59 ML prediction models with only internal validation in orthopedic surgical outcome published up until June 18, 2020, previously identified by our group. Model performance was evaluated using discrimination, calibration, and decision-curve analysis. The TRIPOD guidelines assessed transparent reporting. Results — We included 18 studies externally validating 10 different ML prediction models of the 59 available ML models after screening 4,682 studies. All external validations identified in this review retained good discrimination. Other key performance measures were provided in only 3 studies, rendering overall performance evaluation difficult. The overall median TRIPOD completeness was 61% (IQR 43–89), with 6 items being reported in less than 4/18 of the studies. Interpretation — Most current predictive ML models are not externally validated. The 18 available external validation studies were characterized by incomplete reporting of performance measures, limiting a transparent examination of model performance. Further prospective studies are needed to validate or refute the myriad of predictive ML models in orthopedics while adhering to existing guidelines. This ensures clinicians can take full advantage of validated and clinically implementable ML decision tools