The Role of the Gut Microbiome in Orthopedic Surgery-a Narrative Review.

PURPOSE OF REVIEW: The importance of the gut microbiome has received increasing attention in recent years. New literature has revealed significant associations between gut health and various orthopedic disorders, as well as the potential for interventions targeting the gut microbiome to prevent disease and improve musculoskeletal outcomes. We provide a broad overview of available literature discussing the links between the gut microbiome and pathogenesis and management of orthopedic disorders. RECENT FINDINGS: Human and animal models have characterized the associations between gut microbiome dysregulation and diseases of the joints, spine, nerves, and muscle, as well as the physiology of bone formation and fracture healing. Interventions such as probiotic supplementation and fecal transplant have shown some promise in ameliorating the symptoms or slowing the progression of these disorders. We aim to aid discussions regarding optimization of patient outcomes in the field of orthopedic surgery by providing a narrative review of the available evidence-based literature involving gut microbiome dysregulation and its effects on orthopedic disease. In general, we believe that the gut microbiome is a viable target for interventions that can augment current management models and lead to significantly improved outcomes for patients under the care of orthopedic surgeons.

Impact of Social Determinants of Health in Spine Surgery.

PURPOSE OF REVIEW: Social determinants of health (SDH) are factors that affect patient health outcomes outside the hospital. SDH are "conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks." Current literature has shown SDH affecting patient reported outcomes in various specialties; however, there is a dearth in research relating spine surgery with SDH. The aim of this review article is to identify connections between SDH and post-operative outcomes in spine surgery. These are important, yet understudied predictors that can impact health outcomes and affect health equity. RECENT FINDINGS: Few studies have shown associations between SDH pillars (environment, race, healthcare, economic, and education) and spine surgery outcomes. The most notable relationships demonstrate increased disability, return to work time, and pain with lower income, education, environmental locations, healthcare status and/or provider. Despite these findings, there remains a significant lack of understanding between SDH and spine surgery. Our manuscript reviews the available literature comparing SDH with various spine conditions and surgeries. We organized our findings into the following narrative themes: 1) education, 2) geography, 3) race, 4) healthcare access, and 5) economics.

Using Machine Learning and Deep Learning Algorithms to Predict Postoperative Outcomes Following Anterior Cervical Discectomy and Fusion.

STUDY DESIGN: A retrospective cohort study from a multisite academic medical center. OBJECTIVE: To construct, evaluate, and interpret a series of machine learning models to predict outcomes related to inpatient health care resource utilization for patients undergoing anterior cervical discectomy and fusion (ACDF). SUMMARY OF BACKGROUND DATA: Reducing postoperative health care utilization is an important goal for improving the delivery of surgical care and serves as a metric for quality assessment. Recent data has shown marked hospital resource utilization after ACDF surgery, including readmissions, and ED visits. The burden of postoperative health care use presents a potential application of machine learning techniques, which may be capable of accurately identifying at-risk patients using patient-specific predictors. METHODS: Patients 18-88 years old who underwent ACDF from 2011 to 2021 at a multisite academic center and had preoperative lab values within 3 months of surgery were included. Outcomes analyzed included 90-day readmissions, postoperative length of stay, and nonhome discharge. Four machine learning models-Extreme Gradient Boosted Trees, Balanced Random Forest, Elastic-Net Penalized Logistic Regression, and a Neural Network-were trained and evaluated through the Area Under the Curve estimates. Feature importance scores were computed for the highest-performing model per outcome through model-specific metrics. RESULTS: A total of 1026 cases were included in the analysis cohort. All machine learning models were predictive for outcomes of interest, with the Random Forest algorithm consistently demonstrating the strongest average area under the curve performance, with a peak performance of 0.84 for nonhome discharge. Important features varied per outcome, though age, body mass index, American Society of Anesthesiologists classification >2, and medical comorbidities were highly weighted in the studied outcomes. CONCLUSIONS: Machine learning models were successfully applied and predictive of postoperative health utilization after ACDF. Deployment of these tools can assist clinicians in determining high-risk patients. LEVEL OF EVIDENCE: III.

Sex-Based Difference in Bone Healing: A Review of Recent Pre-clinical Literature.

PURPOSE OF REVIEW: Recent literature has sought to understand differences in fusion failure, specifically considering how patient sex may play a role. Overall, there exists inconclusive data regarding any sex-based differences in bone healing. RECENT FINDINGS: In vitro studies examining the roles of sex hormones, 5-LO, IGF-1, VEGF, osteoclasts, and OPCs seem to show sexually dimorphic actions. Additionally, donor characteristics and stem cell environment seem to also determine osteogenic potential. Building on this biomolecular basis, in vivo work investigates the aforementioned elements. Broadly, males tend to have a more robust healing compared to females. Taking these findings together, differences in sex hormones levels, their timing and action, and composition of the inflammatory milieu underlie variations in bone healing by sex. Clinically, a robust understanding of bone healing mechanics can inform care of the transgender patient. Transgender patients undergoing hormone therapy present a clinically nuanced scenario for which limited long-term data exist. Such advances would help inform treatment for sports-related injury due to hormonal changes in biomechanics and treatment of transgender youth. While recent advances provide more clarity, conclusive answers remain elusive.

A New Normal: Trends of Upper Extremity Orthopaedic Injuries Nationwide During the COVID-19 Pandemic.

Background The widespread societal effects of the COVID-19 pandemic connote public health and epidemiological changes for orthopedic injuries. The epidemiology of upper extremity injuries and the effects of the pandemic on these nationwide trends is poorly defined. Methods This cross-sectional, descriptive epidemiological study compares epidemiological trends among upper extremity (UE) orthopedic injuries presenting to emergency departments (EDs) prior to and during the COVID-19 pandemic. Upper extremity fracture and dislocation data was sourced from the National Electronic Injury Surveillance System (NEISS) database in years prior to (2015-2019) and during the pandemic (2020-2021). Data on incidence, patient demographics, injury patterns, mechanisms of injury, incident locale, and patient disposition were collected and compared between years. Results The pre-COVID-19 incidence rate (IR) of UE fractures at 2.03 per 1,000 persons (n=3038930 from 2015-2019) decreased to 1.84 per 1,000 in 2020 (n=474805) and 1.82 per 1,000 in 2021 (n=471793). Dislocation rates were largely unchanged at 0.34 per 1,000 people (n=476740) prior to the pandemic and with incidence rates of 0.33 per 1,000 (n=85582) and 0.34 per 1,000 (n=89386) in 2020 and 2021, respectively. Female patients over 65 had the highest injury IR at 4.85 per 1,000 (n=976948). Finger fractures (IR=0.38 per 1000, n=96009) overtook hand fractures (IR=0.51 per 1000, n=310710) as more common during COVID-19 in males, while wrist (IR=0.55 per 1000, n=350650) fractures remained most common in females. Injuries from individual sports, such as skateboarding and bicycling, increased during the pandemic, while injuries from team sports decreased. Hospital admission and observation increased in 2020, while discharge and transfer rates decreased. Admission, observation, and discharge rates moved closer to pre-pandemic levels in 2021. Conclusions The COVID-19 pandemic was associated with epidemiological and activity changes regarding UE fractures and dislocations presenting to EDs. The present study demonstrates notable decreases in rates of upper extremity fractures and dislocations, increases in rates of injuries related to outdoor and individual sports such as skateboarding with corresponding decreases in rates of injuries related to organized sports such as basketball, increases in the rates of injuries occurring in homes and in association with pet supplies, and decreases in rates of injuries occurring in schools and places of recreation observed during the pandemic. Additionally, trends observed among patient disposition specific to the pandemic, such as increasing rates of patient admission, observation, and against medical advice (AMA) departure with decreasing rates of discharge and transfer, offer insight into the burden of upper extremity injuries on the healthcare system during this critical time. While upper extremity orthopedic injuries remained common through the pandemic, the early pandemic was associated with higher rates of hospital admission that normalized closer to pre-pandemic levels by 2021, which may herald a shift and return to pre-pandemic trends. Future research will determine the long-term downstream effects of COVID-19 on activity-related orthopedic injuries and bone health.