Implementation of a Fascia Iliaca Compartment Block Program in Geriatric Hip Fractures: The Experience at a Level I Academic Trauma Center.

OBJECTIVES: Determine adherence to a newly implemented protocol of fascia iliaca compartment block (FICB) in geriatric hip fractures. DESIGN: Retrospective review. SETTING: Level I trauma center. PATIENT SELECTION CRITERIA: Patients with a hip fracture treated with cephalomedullary nailing or hemiarthroplasty (CPT codes 27245 or 27236). OUTCOME MEASURES AND COMPARISONS: Adherence to a protocol for FICB, time intervals between emergency department arrival, FICB, and surgery stratified by time of admission. RESULTS: Three hundred eighty patients were studied (average age 78 years, 70% female). Approximately 53.2% of patients received an FICB, which was less than a predefined acceptable adherence rate of 75% ( P < 0.001). Approximately 5.0% received an FICB within 4 hours and 17.3% within 6 hours from admission. Admission during daylight hours (7 am -7p m ) when compared with evening hours (7 pm -7 am ) was associated with improved timeliness ([8.3% vs. 0% within 4 hours, P < 0.001] [27.5% vs. 2.4% within 6 hours, P < 0.001]). Improved adherence to the protocol was observed over time (odds ratio: 1.0013, 95% confidence interval, 1.0001-1.0025, P = 0.0388). CONCLUSIONS: FICB implementation was poor but gradually improved over time. Few patients received an FICB promptly, especially during night hours. Overall, this study demonstrates that implementation of an FICB program at a Level I academic trauma center can be difficult; however, many hurdles can be overcome with institutional support and dedication of resources such as staff, space, and additional training.

Machine learning-based prediction of upgrading on magnetic resonance imaging targeted biopsy in patients eligible for active surveillance.

OBJECTIVE: To examine the ability of machine learning methods to predict upgrading of Gleason score on confirmatory magnetic resonance imaging-guided targeted biopsy (MRI-TB) of the prostate in candidates for active surveillance. SUBJECTS AND METHODS: Our database included 592 patients who received prostate multiparametric magnetic resonance imaging in the evaluation for active surveillance. Upgrading to significant prostate cancer on MRI-TB was defined as upgrading to G 3+4 (definition 1 - DF1) and 4+3 (DF2). Machine learning classifiers were applied on both classification problems DF1 and DF2. RESULTS: Univariate analysis showed that older age and the number of positive cores on pre-MRI-TB were positively correlated with upgrading by DF1 (P-value ≤ 0.05). Upgrading by DF2 was positively correlated with age and the number of positive cores and negatively correlated with body mass index. For upgrading prediction, the AdaBoost model was highly predictive of upgrading by DF1 (AUC 0.952), while for prediction of upgrading by DF2, the Random Forest model had a lower but excellent prediction performance (AUC 0.947). CONCLUSION: We show that machine learning has the potential to be integrated in future diagnostic assessments for patients eligible for AS. Training our models on larger multi-institutional databases is needed to confirm our results and improve the accuracy of these models' prediction.

Biomanufacturing organized collagen-based microfibers as a Tissue ENgineered Device (TEND) for tendon regeneration.

Approximately 800, 000 surgical repairs are performed annually in the U.S. for debilitating injuries to ligaments and tendons of the foot, ankle, knee, wrist, elbow and shoulder, presenting a significant healthcare burden. To overcome current treatment shortcomings and advance the treatment of tendon and ligament injuries, we have developed a novel electrospun Tissue ENgineered Device (TEND), comprised of type I collagen and poly(D,L-lactide) (PDLLA) solubilized in a benign solvent, dimethyl sulfoxide (DMSO). TEND fiber alignment, diameter and porosity were engineered to enhance cell infiltration leading to promote tissue integration and functional remodeling while providing biomechanical stability. TEND rapidly adsorbs blood and platelet-rich-plasma (PRP), and gradually releases growth factors over two weeks. TEND further supported cellular alignment and upregulation of tenogenic genes from clinically relevant human stem cells within three days of culture. TEND implanted in a rabbit Achilles tendon injury model showed new in situ tissue generation, maturation, and remodeling of dense, regularly oriented connective tissue in vivo. In all, TEND's organized microfibers, biological fluid and cell compatibility, strength and biocompatiblility make significant progress towards clinically translating electrospun collagen-based medical devices for improving the clinical outcomes of tendon injuries.