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IntroductionFragility fractures are a major threat to geriatric patients. However, it is unclear whether this patient population's inherent frailty and comorbidity or the physiologic insult caused by the fracture and its surgery contribute more to undesirable patient outcomes. Hence, this study examines if frailty and comorbidity can predict 30 day postoperative outcomes while the effects of multiple fracture sites are accounted for. MethodsA retrospective review of patients ≥ 65 years of age in the National Surgical Quality Improvement Program who underwent surgical treatment between 2013 and 2017 was performed. A total of 52,497 patients were included in the final analysis, including fracture cases of the extremities, limbs, and hip. Demographics, several metrics of preoperative health, temporal variables, and fracture location were tested in bivariate analysis of 30 day postoperative mortality, length of stay in hospital, discharge outcome, and complications. Significant variables were considered for multivariate logistic regression models for each outcome.ResultsFrailty, comorbidity, and time to surgery were found to be the significant predictors in multivariate analysis of each 30 day postoperative outcome, independent of the effects of fracture site (p < 0.05). Examination of 30 day mortality found that American Society of Anesthesiologists Class ≥ 3 (2.30 Odds Ratio), modified Frailty Index > 0 (1.37 OR), Charleston Comorbidity Index ≥ 6 (1.63 OR), and time to surgery (1.45 OR) were especially important (all p < 0.05). Additionally, the worst outcomes were associated with fractures of the pelvis/hip and femur/knee, including 30 day mortality (5.90 and 5.12 OR, respectively; both p < 0.05). ConclusionThe effects of the preoperative health were found to be independent of patient demographics and fracture site. Additionally, specific high-risk fracture sites are significant predictors of outcome, supporting the need to prioritize these patients. Clinical care pathways for geriatric patients may benefit from emphasis on these high-risk fractures and preoperative patient health.

Poor pain alleviation remains a problem following orthopedic surgery, leading to prolonged recovery time, increased morbidity, and prolonged opioid use after hospitalization. Wearable device data, collected during postsurgical recovery, may help ameliorate poor pain alleviation because a patient’s physiological state during the recovery process may be inferred from sensor data. In this study, we collected smart ring data from 37 inpatients following orthopedic surgery and developed machine learning models to predict if a patient had postsurgical poor pain alleviation. Machine learning models based on the smart ring data were able to predict if a patient had poor pain alleviation during their hospital stay with an accuracy of 70.0%, an F1-score of 0.769, and an area under the receiver operating characteristics curve of 0.762 on an independent test dataset. These values were similar to performance metrics from existing models that rely on static, preoperative patient factors. Our results provide preliminary evidence that wearable device data may help control pain after orthopedic surgery by incorporating real-time, objective estimates of a patient’s pain during recovery.

There are currently no standardized methods for assessing fracture healing, with physicians relying on X-rays which are only useful at later stages of repair. Using in vivo mouse fracture models, we present the first evidence that microscale instrumented implants provide a route for post-operative fracture monitoring, utilizing electrical impedance spectroscopy (EIS) to track the healing tissue with high sensitivity. In this study, we fixed mouse long bone fractures with external fixators and bone plates. EIS measurements taken across two microelectrodes within the fracture gap were able to track longitudinal differences between individual mice with good versus poor healing. We additionally present an equivalent circuit model that combines the EIS data to classify fracture repair states. Lastly, we show that EIS measurements strongly correlated with standard quantitative µCT values and that these correlations validate clinically-relevant operating frequencies for implementation of this technique. These results demonstrate that EIS can be integrated into current fracture management strategies such as bone plating, providing physicians with quantitative information about the state of fracture repair to guide clinical decision-making for patients.

There is an unmet need for improved, clinically relevant methods to longitudinally quantify bone healing during fracture care. Here we develop a smart bone plate to wirelessly monitor healing utilizing electrical impedance spectroscopy (EIS) to provide real-time data on tissue composition within the fracture callus. To validate our technology, we created a 1-mm rabbit tibial defect and fixed the bone with a standard veterinary plate modified with a custom-designed housing that included two impedance sensors capable of wireless transmission. Impedance magnitude and phase measurements were transmitted every 48 h for up to 10 weeks. Bone healing was assessed by X-ray, µCT, and histology. Our results indicated the sensors successfully incorporated into the fracture callus and did not impede repair. Electrical impedance, resistance, and reactance increased steadily from weeks 3 to 7—corresponding to the transition from hematoma to cartilage to bone within the fracture gap—then plateaued as the bone began to consolidate. These three electrical readings significantly correlated with traditional measurements of bone healing and successfully distinguished between union and not-healed fractures, with the strongest relationship found with impedance magnitude. These results suggest that our EIS smart bone plate can provide continuous and highly sensitive quantitative tissue measurements throughout the course of fracture healing to better guide personalized clinical care.

Background and Objectives: Outcome data from wearable devices are increasingly used in both research and clinics. Traditionally, a dedicated device is chosen for a given study or clinical application to collect outcome data as soon as the patient is included in a study or undergoes a procedure. The current study introduces a new measurement strategy, whereby patients’ own devices are utilized, allowing for both a pre-injury baseline measure and ability to show achievable results. Materials and Methods: Patients with a pre-existing musculoskeletal injury of the upper and lower extremity were included in this exploratory, proof-of-concept study. They were followed up for a minimum of 6 weeks after injury, and their wearable outcome data (from a smartphone and/or a body-worn sensor) were continuously acquired during this period. A descriptive analysis of the screening characteristics and the observed and achievable outcome patterns was performed. Results: A total of 432 patients was continuously screened for the study, and their screening was analyzed. The highest success rate for successful inclusion was in younger patients. Forty-eight patients were included in the analysis. The most prevalent outcome was step count. Three distinctive activity data patterns were observed: patients recovering, patients with slow or no recovery, and patients needing additional measures to determine treatment outcomes. Conclusions: Measuring outcomes in trauma patients with the Bring Your Own Device (BYOD) strategy is feasible. With this approach, patients were able to provide continuous activity data without any dedicated equipment given to them. The measurement technique is especially suited to particular patient groups. Our study’s screening log and inclusion characteristics can help inform future studies wishing to employ the BYOD design.

PurposeAugmentation strategies for surgical fixation of proximal humerus fractures (PHF) are available to address their relatively high failure rate. The purpose of this study was to compare two medial-buttress augmentation strategies for PHF fixation.MethodsA two-part PHF model with loss of medial buttress was created in 16 synthetic bones. The PHFs were fixed with locking plates and either calcium phosphate cement (CPC) or fibula strut (FS) augmentation. After cadaveric validations, the fixation constructs were subjected to nondestructive axial compression tests, followed by a cyclic test. Construct stiffness and angular displacement of the humerus head were recorded.ResultsHumeral head angular displacement was statistically greater in the CPC group than in the FS group at the applied force of 300 N and higher (p < 0.05). Axial stiffness was statistically greater in the FS fixation group than in the CPC group at initial and final phases of cyclic loading protocol (p < 0.05).ConclusionsIn an osteoporotic cadaveric model of a 2-part PHF with loss of a medial buttress, locked plate constructs augmented with FS have a higher resistance to varus collapse compared to those augmented with CPC.

Purpose Hemipelvis reduction in the setting of AO/OTA 61-C1.2 (APC3) pelvic injuries can be challenging. A common strategy is to provisionally reduce or fix the anterior ring prior to definitive fixation of the posterior ring. In this scenario, it is difficult to assess whether residual sacroiliac joint (SIJ) widening is due to hemipelvis flexion/extension or lateral displacement. This simulation sought to identify a radiographic marker for posterior ilium flexion or extension malreduction in the setting of a reduced anterior ring. Methods Symphyseal and both anterior and posterior SIJ ligaments were cut in 8 cadaveric pelvis. The symphysis was reduced and wired. One centimeter of posterior flexion or extension at the SIJ was created to mimic the clinical scenario of hemipelvis flexion or extension malreduction, and a lateral compressive force was applied. SIJ widening and the direction of anterior or posterior ileal displacement relative to the contralateral joint were assessed via inlet views. SIJ widening and the direction of cranial or caudal ileal displacement were assessed using outlet views. Comparisons between flexion and extension models used Fisher’s exact test. Results On outlet views, all flexed hemipelvis demonstrated caudal ileal translation at the superior SIJ, in contrast to all extended hemipelvis demonstrated cranial translation ( p  < 0.0005); the scenarios were easily distinguishable. Conversely, inlet imaging was unable to identify the direction of malreduction. Flexion/extension scenarios resulted in similar amounts of SIJ widening. Conclusion Residual flexion and extension hemipelvis malreductions in APC3 injuries after provisional anterior fixation can be differentiated by the direction of ileal displacement at the superior SIJ on the outlet view.

Purpose Reduction of AO/OTA 61-B2.3 (APC2) pelvic fractures is challenging in the setting of anterior ring comminution. The anterior ring is visually much simpler to evaluate for flexion or extension hemipelvis deformity than the posterior ring, except in the setting of comminution, necessitating some other visual reference to judge hemipelvis reduction. We sought to test whether pelvic inlet and outlet fluoroscopy of the contours of the sacroiliac joint could be used in isolation to judge hemipelvis flexion or extension. Methods Symphyseal and anterior SIJ ligaments were cut (6 cadaveric pelvis). The symphysis was held malreduced to produce one centimeter flexion and extension deformity: 1 cm was selected to mimic a maximum clinical scenario. The SIJ was assessed using inlet and outlet fluoroscopy. The scaled width of the SIJ was assessed at the joint apertures and midjoint on both inlet and outlet views. Joint widths in flexion and extension were compared against joint widths measured on the reduced SIJ using paired t -tests. Results There was no statistical difference in the superior ( p  = 0.227, 0.675), middle ( p  = 0.203, 0.693), and inferior ( p  = 0.232, 0.961) SIJ widths between hemipelvis flexion or extension models against reduced SIJ on outlet views. There was no statistical difference in the anterior ( p  = 0.731, 0.662), middle ( p  = 0.257, 0.655), and posterior ( p  = 0.657, 0.363) SIJ widths between flexion or extension models against reduced SIJ on inlet views. Conclusion Inspection of SIJ width on inlet and outlet fluoroscopy cannot detect up to one centimeter of hemipelvis flexion or extension malreduction in the setting of AO/OTA 61-B2.3 (APC2) pelvic fractures with complex anterior injuries.

Purpose Poor pain alleviation (PPA) after orthopaedic surgery is known to increase recovery time, readmissions, patient dissatisfaction, and lead to chronic postsurgical pain. This study’s goal was to identify the magnitude of PPA and its risk factors in the orthopaedic trauma patient population. Methods A single-institution's electronic medical records from 2015 to 2018 were available for retrospective analysis. Inclusion criteria included orthopaedic fracture surgery patients admitted to the hospital for 24 h or more. Collected variables included surgery type, basic demographics, comorbidities, inpatient medications, pain scores, and length of stay. PPA was defined as a pain score of ≥ 8 on at least three occasions 4–12 h apart. Associations between collected variables and PPA were derived using a multivariable logistic regression model and expressed in adjusted odds ratios. Results A total of 1663 patients underwent fracture surgeries from 2015 to 2018, and 25% of them reported PPA. Female sex, previous use of narcotics, increased ASA, increased baseline pain score, and younger age without comorbidities were identified as significant risk factors for PPA. Spine procedures were associated with increased risk of PPA, while procedures in the hip, shoulder, and knee had reduced risk. Patients experiencing PPA were less likely to receive NSAIDs compared to other pain medications. Conclusions This study found an unacceptably high rate of PPA after fracture surgery. While the identified risk factors for PPA were all non-modifiable, our results highlight the necessity to improve application of current multimodal approaches to pain alleviation including a more personalized approach to pain alleviation.

The use of wearable technology is steadily increasing. In orthopedic trauma surgery, where the musculoskeletal system is directly affected, focus has been directed towards assessing aspects of physical functioning, activity behavior, and mobility/disability. This includes sensors and algorithms to monitor real-world walking speed, daily step counts, ground reaction forces, or range of motion. Several specific reviews have focused on this domain. In other medical fields, wearable sensors and algorithms to monitor digital biometrics have been used with a focus on domain-specific health aspects such as heart rate, sleep, blood oxygen saturation, or fall risk. This review explores the most common clinical and research use cases of wearable sensors in other medical domains and, from it, derives suggestions for the meaningful transfer and application in an orthopedic trauma context.