RESUMEN
BACKGROUND: Autologous nasoseptal cartilage grafts are used to correct nasal asymmetry and deviation in rhinoplasty, but patients who have undergone multiple surgeries may have limited autologous cartilage tissue available. 3D-printed L-strut implants may address these challenges in the future, but their mechanical strength is understudied. Silk fibroin-gelatin (SFG), polycaprolactone (PCL), and polylactide (PLA) are bio-inks known for their strength. We present Finite Element Analysis (FEA) models comparing the mechanical strength of 3D-printed SFG, PCL, and PLA implants with nasoseptal cartilage grafts when autologous or allografts are not available. METHODS: FEA models compared the stress and deformation responses of 3D-printed solid and scaffold implant replacements to cartilage. To simulate a daily force from overlying soft tissue, a unidirectional load was applied at the "keystone" region given its structural role and compared with native cartilaginous properties. RESULTS: 3D-printed solid SFG, PCL, and PLA and scaffold PCL and PLA models demonstrated lower deformations compared to cartilage. Solid SFG balanced strength and flexibility. The maximum stress was below all materials' yield stresses suggesting their deformations are unlikely permanent under a daily load. CONCLUSIONS: Our FEA models suggest that 3D-printed L-strut implants carry promising mechanical strength. Solid SFG's results mimicked cartilage's mechanical behavior. Thus, scaffold SFG merits further geometric optimization for potential use for cartilage substitution. 3D-printed septal cartilage replacement implants can potentially enhance surgical management of patients who lack available donor cartilage in select settings. CLINICAL RELEVANCE STATEMENT: Computational simulations can evaluate 3D-printed implant strength and their potential to replace septal cartilage in septorhinoplasty.
RESUMEN
BACKGROUND: Outcomes of trauma "walk-in" patients (using private vehicles or on foot) are understudied. We compared outcomes of ground ambulance vs walk-ins, hypothesizing that delayed resuscitation and uncoordinated care may worsen walk-in outcomes. METHODS: A retrospective analysis 2020 American College of Surgeons Trauma Quality Programs (ACS-TQP) databases compared outcomes between ambulance vs "walk-ins." The primary outcome was in-hospital mortality, excluding external facility transfers and air transports. Data was analyzed with descriptive statistics, bivariate, multivariable logistic regression, including an Inverse Probability Weighted Regression Adjustment with adjustments for injury severity and vital signs. The primary outcome for the 2019 (pre-COVID-19 pandemic) data was similarly analyzed. RESULTS: In 2020, 707,899 patients were analyzed, 556,361 (78.59%) used ambulance, and 151,538 (21.41%) were walk-ins. We observed differences in demographics, hospital attributes, medical comorbidities, and injury mechanism. Ambulance patients had more chronic conditions and severe injuries. Walk-ins had lower in-hospital mortality (850 (.56%) vs 23,131 (4.16%)) and arrived with better vital signs. Multivariable logistic regression models (inverse probability weighting for regression adjustment), adjusting for injury severity, demographics, injury mechanism, and vital signs, confirmed that walk-in status had lower odds of mortality. For the 2019 (pre-COVID-19 pandemic) database, walk-ins also had lower in-hospital mortality. DISCUSSION: Our results demonstrate better survival rates for walk-ins before and during COVID-19 pandemic. Despite limitations of patient selection bias, this study highlights the need for further research into transportation modes, geographic and socioeconomic factors affecting patient transport, and tailoring management strategies based on their mode of arrival.
