Comparison of Classically and Machine Learning Generated Survival Prediction Models for Patients With Spinal Metastasis - A meta-Analysis of Two Recently Developed Algorithms.

Study Design: A systemic review and a meta-analysis. We also provided a retrospective cohort for validation in this study.

Objective: (1) Using a meta-analysis to determine the pooled discriminatory ability of The Skeletal Oncology Research Group (SORG) classical algorithm (CA) and machine learning algorithms (MLA); and (2) test the hypothesis that SORG-CA has less variability in performance than SORG-MLA in non-American validation cohorts as SORG-CA does not incorporates regional-specific variables such as body mass index as input.

Impact of intraoperative imaging on decision-making during spine surgery: a survey among spine surgeons using simulated intraoperative images.

Purpose: To assess whether the intention to intraoperatively reposition pedicle screws differs when spine surgeons evaluate the same screws with 2D imaging or 3D imaging.

Methods: In this online survey study, 21 spine surgeons evaluated eight pedicle screws from patients who had undergone posterior spinal fixation. In a simulated intraoperative setting, surgeons had to decide if they would reposition a marked pedicle screw based on its position in the provided radiologic imaging.

Stereotactic Body and Conventional Radiotherapy for Painful Bone Metastases: A Systematic Review and Meta-Analysis.

Importance: Conventional external beam radiotherapy (cEBRT) and stereotactic body radiotherapy (SBRT) are commonly used treatment options for relieving metastatic bone pain. The effectiveness of SBRT compared with cEBRT in pain relief has been a subject of debate, and conflicting results have been reported.

Objective: To compare the effectiveness associated with SBRT vs cEBRT for relieving metastatic bone pain.

Comparison of eight modern preoperative scoring systems for survival prediction in patients with extremity metastasis.

Background: Survival is an important factor to consider when clinicians make treatment decisions for patients with skeletal metastasis. Several preoperative scoring systems (PSSs) have been developed to aid in survival prediction. Although we previously validated the Skeletal Oncology Research Group Machine-learning Algorithm (SORG-MLA) in Taiwanese patients of Han Chinese descent, the performance of other existing PSSs remains largely unknown outside their respective development cohorts.

Assessing the accuracy of a new 3D2D registration algorithm based on a non-invasive skin marker model for navigated spine surgery.

Purpose: We assessed the accuracy of a new 3D2D registration algorithm to be used for navigated spine surgery and explored anatomical and radiologic parameters affecting the registration accuracy. Compared to existing 3D2D registration algorithms, the algorithm does not need bone-mounted or table-mounted instruments for registration. Neither does the intraoperative imaging device have to be tracked or calibrated.

The Systemic Immune Response in COVID-19 Is Associated with a Shift to Formyl-Peptide Unresponsive Eosinophils.

A malfunction of the innate immune response in COVID-19 is associated with eosinopenia, particularly in more severe cases. This study tested the hypothesis that this eosinopenia is COVID-19 specific and is associated with systemic activation of eosinophils. Blood of 15 healthy controls and 75 adult patients with suspected COVID-19 at the ER were included before PCR testing and analyzed by point-of-care automated flow cytometry (CD10, CD11b, CD16, and CD62L) in the absence or presence of a formyl peptide (fNLF).

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.

Machine learning prediction models in orthopedic surgery: A systematic review in transparent reporting.

Machine learning (ML) studies are becoming increasingly popular in orthopedics but lack a critically appraisal of their adherence to peer-reviewed guidelines. The objective of this review was to (1) evaluate quality and transparent reporting of ML prediction models in orthopedic surgery based on the transparent reporting of multivariable prediction models for individual prognosis or diagnosis (TRIPOD), and (2) assess risk of bias with the Prediction model Risk Of Bias ASsessment Tool. A systematic review was performed to identify all ML prediction studies published in orthopedic surgery through June 18th, 2020.

Flow cytometric evaluation of the neutrophil compartment in COVID-19 at hospital presentation: A normal response to an abnormal situation.

Coronavirus disease 2019 (COVID-19) is a rapidly emerging pandemic disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Critical COVID-19 is thought to be associated with a hyper-inflammatory process that can develop into acute respiratory distress syndrome, a critical disease normally mediated by dysfunctional neutrophils. This study tested the hypothesis whether the neutrophil compartment displays characteristics of hyperinflammation in COVID-19 patients.

An increase in CD62L neutrophils precedes the development of pulmonary embolisms in COVID-19 patients.

Objectives: A high incidence of pulmonary embolism (PE) is reported in patients with critical coronavirus disease 2019 (COVID-19). Neutrophils may contribute to this through a process referred to as immunothrombosis. The aim of this study was to investigate the occurrence of neutrophil subpopulations in blood preceding the development of COVID-19 associated PE.

Thirty-day Postoperative Complications After Surgery For Metastatic Long Bone Disease Are Associated With Higher Mortality at 1 Year.

Background: The benefits of surgical treatment of a metastasis of the extremities may be offset by drawbacks such as potential postoperative complications. For this group of patients, the primary goal of surgery is to improve quality of life in a palliative setting. A better comprehension of factors associated with complications and the impact of postoperative complications on mortality may prevent negative outcomes and help surgeons in surgical decision-making.

Development and Internal Validation of Machine Learning Algorithms for Preoperative Survival Prediction of Extremity Metastatic Disease.

Background: A preoperative estimation of survival is critical for deciding on the operative management of metastatic bone disease of the extremities. Several tools have been developed for this purpose, but there is room for improvement. Machine learning is an increasingly popular and flexible method of prediction model building based on a data set.