Regional differences in the three-dimensional bone microstructure of the radial head:implications for observed fracture patterns

Introduction: A characterization of the internal bone microstructure of the radial head could provide a better understanding of commonly occurring fracture patterns frequently involving the (antero)lateral quadrant, for which a clear explanation is still lacking. The aim of this study is to describe the radial head bone microstructure using micro-computed tomography (micro-CT) and to relate it to gross morphology, function and possible fracture patterns. Materials and methods: Dry cadaveric human radii were scanned by micro-CT (17 μm/pixel, isotropic). The trabecular bone microstructure was quantified on axial image stacks in four quadrants: the anterolateral (AL), posterolateral (PL), posteromedial (PM) and anteromedial (AM) quadrant. Results: The AL and PL quadrants displayed the significantly lowest bone volume fraction and trabecular number (BV/TV range 12.3–25.1%, Tb.N range 0.73–1.16 mm−1) and highest trabecular separation (Tb.Sp range 0.59–0.82 mm), compared to the PM and AM quadrants (BV/TV range 19.9–36.9%, Tb.N range 0.96–1.61 mm−1, Tb.Sp range 0.45–0.74 mm) (p = 0.03). Conclusions: Our microstructural results suggest that the lateral side is the “weaker side”, exhibiting lower bone volume faction, less trabeculae and higher trabecular separation, compared to the medial side. As the forearm is pronated during most falls, the underlying bone microstructure could explain commonly observed fracture patterns of the radial head, particularly more often involving the AL quadrant. If screw fixation in radial head fractures is considered, surgeons should take advantage of the “stronger” bone microstructure of the medial side of the radial head, should the fracture line allow this

Correction:Intraoperative fluoroscopic protocol to avoid rotational malalignment after nailing of tibia shaft fractures: introduction of the ‘C-Arm Rotational View (CARV)’ (European Journal of Trauma and Emergency Surgery, (2022), 10.1007/s00068-022-02038-2)

In the Acknowledgements section the following part was missing: On behalf of the Traumaplatform 3D Consortium: L. M. Goedhart, B. de Cort, L. A. M. Hendrickx, M. ter Horst, J. Gorter, R. J. van Luit, P. Nieboer, W. Füssenich, T. Zwerver, R. Koster, J. J. Valk, L. Reinke, J. G. Bleeker, M. Cain, F. J. P. Beeres, G. M. M. J. Kerkhoffs. The original article has been corrected

Are 3D-printed Models of Tibial Plateau Fractures a Useful Addition to Understanding Fractures for Junior Surgeons?

Background Tibial plateau fractures are often complex, and they can be challenging to treat. Classifying fractures is often part of the treatment process, but intra- and interobserver reliability of fracture classification systems often is inadequate to the task, and classifications that lack reliability can mislead providers and result in harm to patients. Three-dimensionally (3D)-printed models might help in this regard, but whether that is the case for the classification of tibial plateau fractures, and whether the utility of such models might vary by the experience of the individual classifying the fractures, is unknown. Questions/purposes (1) Does the overall interobserver agreement improve when fractures are classified with 3D-printed models compared with conventional radiology? (2) Does interobserver agreement vary among attending and consultant trauma surgeons, senior surgical residents, and junior surgical residents? (3) Do surgeons' and surgical residents' confidence and accuracy improve when tibial plateau fractures are classified with an additional 3D model compared with conventional radiology? Methods Between 2012 and 2020, 113 patients with tibial plateau fractures were treated at a Level 1 trauma center. Forty-four patients were excluded based on the presence of bone diseases (such as osteoporosis) and the absence of a CT scan. To increase the chance to detect an improvement or deterioration and to prevent observers from losing focus during the classification, we decided to include 40 patients with tibial plateau fractures. Nine trauma surgeons, eight senior surgical residents, and eight junior surgical residents-none of whom underwent any study-specific pretraining-classified these fractures according to three often-used classification systems (Schatzker, OA/OTA, and the Luo three-column concept), with and without 3D-printed models, and they indicated their overall confidence on a 10-point Likert scale, with 0 meaning not confident at all and 10 absolutely certainty. To set the gold standard, a panel of three experienced trauma surgeons who had special expertise in knee surgery and 10 years to 25 years of experience in practice also classified the fractures until consensus was reached. The Fleiss kappa was used to determine interobserver agreement for fracture classification. Differences in confidence in assessing fractures with and without the 3D-printed model were compared using a paired t-test. Accuracy was calculated by comparing the participants' observations with the gold standard. Results The overall interobserver agreement improved minimally for fracture classification according to two of three classification systems (Schatzker: kappa(conv) = 0.514 versus kappa(3Dprint) = 0.539; p = 0.005; AO/OTA:kappa(conv) = 0.359 versus kappa(3Dprint) = 0.372; p = 0.03). However, none of the classification systems, even when used by our most experienced group of trauma surgeons, achieved more than moderate interobserver agreement, meaning that a large proportion of fractures were misclassified by at least one observer. Overall, there was no improvement in self-assessed confidence in classifying fractures or accuracy with 3D-printed models; confidence was high (about 7 points on a 10-point scale) as rated by all observers, despite moderate or worse accuracy and interobserver agreement Conclusion Although 3D-printed models minimally improved the overall interobserver agreement for two of three classification systems, none of the classification systems achieved more than moderate interobserver agreement. This suggests that even with 3D-printed models, many fractures would be misclassified, which could result in misleading communication, inaccurate prognostic assessments, unclear research, and incorrect treatment choices. Therefore, we cannot recommend the use of 3D-printed models in practice and research for classification of tibial plateau fractures

3D virtual pre-operative planning may reduce the incidence of dorsal screw penetration in volar plating of intra-articular distal radius fractures

Purpose: To evaluate the effect of three-dimensional virtual pre-operative planning (3DVP) on the incidence of dorsal screw penetration after volar plating of distal radius fractures. Methods: A cross-sectional diagnostic imaging study was performed. Twenty out of 50 patients were randomly selected from our index prospective cohort (IPC): a prior study evaluating dorsal tangential views (DTVs) in reducing dorsal screw penetration in internal fixation of intra-articular distal radius fractures using post-operative CT scans to quantify screw protrusion. Pre-operative CTs from this cohort were now used for 3DVP by three experienced orthopaedic trauma surgeons (supplementary video). 3DVP was compared with the corresponding post-operative CT for assessing screw lengths and incidence of dorsal penetration. The Wilcoxon Signed Ranks test was used to compare screw lengths and the Fishers’ exact for incidence of penetration. Results: Three surgeons performed 3DVP for 20 distal radius fractures and virtually applied 60 volar plates and 273 screws. Median screw length was shorter in the 3DVP when compared to IPC: 18 mm (range, 12–22) versus 20 mm (range, 14–26) (p < 0.001). The number of penetrating screws was 5% (13/273 screws) in the 3DVP group compared to 11% (10/91 screws) in the IPC (p = 0.047). Corresponding to a reduction in incidence of at least one dorsally penetrating screw in 40% of patients in the IPC group, to 18% in the 3DVP group (p = 0.069). Conclusion: Three-Dimensional Virtual Pre-Operative Planning (3DVP) may reduce the incidence of dorsally penetrating screws in patients treated with volar plating for intra-articular distal radius fractures. Level of evidence: II, diagnostic imaging study

Does the SORG Orthopaedic Research Group Hip Fracture Delirium Algorithm Perform Well on an Independent Intercontinental Cohort of Patients With Hip Fractures Who Are 60 Years or Older?

Background Postoperative delirium in patients aged 60 years or older with hip fractures adversely affects clinical and functional outcomes. The economic cost of delirium is estimated to be as high as USD 25,000 per patient, with a total budgetary impact between USD 6.6 to USD 82.4 billion annually in the United States alone. Forty percent of delirium episodes are preventable, and accurate risk stratification can decrease the incidence and improve clinical outcomes in patients. A previously developed clinical prediction model (the SORG Orthopaedic Research Group hip fracture delirium machine-learning algorithm) is highly accurate on internal validation (in 28,207 patients with hip fractures aged 60 years or older in a US cohort) in identifying at-risk patients, and it can facilitate the best use of preventive interventions; however, it has not been tested in an independent population. For an algorithm to be useful in real life, it must be valid externally, meaning that it must perform well in a patient cohort different from the cohort used to "train" it. With many promising machine-learning prediction models and many promising delirium models, only few have also been externally validated, and even fewer are international validation studies. Question/purpose Does the SORG hip fracture delirium algorithm, initially trained on a database from the United States, perform well on external validation in patients aged 60 years or older in Australia and New Zealand? Methods We previously developed a model in 2021 for assessing risk of delirium in hip fracture patients using records of 28,207 patients obtained from the American College of Surgeons National Surgical Quality Improvement Program. Variables included in the original model included age, American Society of Anesthesiologists (ASA) class, functional status (independent or partially or totally dependent for any activities of daily living), preoperative dementia, preoperative delirium, and preoperative need for a mobility aid. To assess whether this model could be applied elsewhere, we used records from an international hip fracture registry. Between June 2017 and December 2018, 6672 patients older than 60 years of age in Australia and New Zealand were treated surgically for a femoral neck, intertrochanteric hip, or subtrochanteric hip fracture and entered into the Australian & New Zealand Hip Fracture Registry. Patients were excluded if they had a pathological hip fracture or septic shock. Of all patients, 6% (402 of 6672) did not meet the inclusion criteria, leaving 94% (6270 of 6672) of patients available for inclusion in this retrospective analysis. Seventy-one percent (4249 of 5986) of patients were aged 80 years or older, after accounting for 5% (284 of 6270) of missing values; 68% (4292 of 6266) were female, after accounting for 0.06% (4 of 6270) of missing values, and 83% (4690 of 5661) of patients were classified as ASA III/IV, after accounting for 10% (609 of 6270) of missing values. Missing data were imputed using the missForest methodology. In total, 39% (2467 of 6270) of patients developed postoperative delirium. The performance of the SORG hip fracture delirium algorithm on the validation cohort was assessed by discrimination, calibration, Brier score, and a decision curve analysis. Discrimination, known as the area under the receiver operating characteristic curves (c-statistic), measures the model's ability to distinguish patients who achieved the outcomes from those who did not and ranges from 0.5 to 1.0, with 1.0 indicating the highest discrimination score and 0.50 the lowest. Calibration plots the predicted versus the observed probabilities, a perfect plot has an intercept of 0 and a slope of 1. The Brier score calculates a composite of discrimination and calibration, with 0 indicating perfect prediction and 1 the poorest. Results The SORG hip fracture algorithm, when applied to an external patient cohort, distinguished between patients at low risk and patients at moderate to high risk of developing postoperative delirium. The SORG hip fracture algorithm performed with a c-statistic of 0.74 (95% confidence interval 0.73 to 0.76). The calibration plot showed high accuracy in the lower predicted probabilities (intercept -0.28, slope 0.52) and a Brier score of 0.22 (the null model Brier score was 0.24). The decision curve analysis showed that the model can be beneficial compared with no model or compared with characterizing all patients as at risk for developing delirium. Conclusion Algorithms developed with machine learning are a potential tool for refining treatment of at-risk patients. If high-risk patients can be reliably identified, resources can be appropriately directed toward their care. Although the current iteration of SORG should not be relied on for patient care, it suggests potential utility in assessing risk. Further assessment in different populations, made easier by international collaborations and standardization of registries, would be useful in the development of universally valid prediction models. The model can be freely accessed at: https://sorg-apps.shinyapps.io/hipfxdelirium/

Quantifying the Differences between 3D Virtual Planning and Attained Postoperative Reduction on CT for Patients with Tibial Plateau Fractures; a Clinical Feasibility Study

Background: Three-Dimensional Virtual Planning (3DVP) has been proven to be effective for limiting intra-articular screw penetration and improving the quality of reduction for numerous fractures. However, the value of 3DVP for patients with tibial plateau fractures has yet to be determined. Purposes: The research question of this study is: Can Computed Tomography Micromotion Analysis (CTMA) provide a reliable quantification of the difference between 3DVP and the postoperative reduction on CT for tibial plateau fractures? Methods: Nine consecutive adult patients who received surgical treatment for a tibial plateau fracture and received pre- and postoperative CT scans were included from a level I trauma center in the Netherlands. The preoperative CT scans of the patients were uploaded in a 3DVP software. In this software, fracture fragments were reduced and the reduction was saved as a 3D file (STL). The quality of the reduction from the 3DVP software was compared with the postoperative results using CT Micromotion Analysis (CTMA). In this analysis, the translation of the largest intra-articular fragment was calculated by aligning the postoperative CT with the 3DVP. Coordinates and measurement points were defined in the X, Y, and Z axes. The combined values of X and Y were used to define the intra-articular gap. The Z-axis was defined as the line from cranial to caudal and was used to define intra-articular step-off. Results: The intra-articular step-off was 2.4 mm (Range 0.5–4.6). Moreover, the mean translation of the X-axis and Y-axis, which was defined as the intra-articular gap, was 4.2 mm (Range 0.6–10.7). Conclusions: 3DVP provides excellent insight into the fracture and its fragments. Utilizing the largest intra-articular fragment, it is feasible to quantify the difference between 3DVP and a postoperative CT using CTMA. A prospective study to further analyze the use of 3DVP in terms of intra-articular reduction and surgical and patient-related outcomes has been started by our team.</p

Do symptoms of anxiety and/or depression and pain intensity before primary Total knee arthroplasty influence reason for revision? Results of an observational study from the Dutch arthroplasty register in 56,233 patients

Objective: Anxiety, depression and greater pain intensity before total knee arthroplasty (TKA) may increase the probability of revision surgery for remaining symptoms even without clear pathology or technical issues. We aimed to assess whether preoperative anxiety/depression and pain intensity are associated with revision TKA for less clear indications. Methods: Less clear indications for revision were defined after a Delphi process in which consensus was reached among 59 orthopaedic knee experts. We performed a cox regression analyses on primary TKA patients registered in the Dutch Arthroplasty Registry (LROI) who completed the EuroQol 5D 3 L (EQ5D-3 L) anxiety/depression score to examine associations between preoperative anxiety/depression and pain (Numeric Rating Scale (NRS)) with TKA revision for less clear reasons. These analyses were adjusted for age, BMI, sex, smoking, ASA score, EQ5D-3 L thermometer and OKS score. Results: In total, 25.9% patients of the 56,233 included patients reported moderate or severe symptoms of anxiety/depression on the EQ5D-3 L anxiety/depression score. Of those, 615 revisions (45.5%) were performed for less clear reasons for revision (patellar pain, malalignment, instability, progression of osteoarthritis or arthrofibrosis). Not EQ5D-3 L anxiety/depression score, but higher NRS pain at rest and EQ5D-3 L pain score were associated with revision for less clear reason (HR: 1.058, 95% CI 1.019-1.099 & HR: 1.241, 95% CI 1.044-1.476, respectively). Conclusion: Our findings suggest that pain intensity is a risk factor for TKA revision for a less clear reason. The finding that preoperative pain intensity was associated with reason for revision confirms a likely influence of subjective, personal factors on offer and acceptance of TKA revision. The association between anxiety/depression and reason for revision after TKA may also be found when including more specific outcome measures to assess anxiety/depression and we therefore hope to encourage further research on this topic with our study, ideally in a prospective setting. Study design: Longitudinal Cohort Study Level III, Delphi Consensu

Can We Geographically Validate a Natural Language Processing Algorithm for Automated Detection of Incidental Durotomy Across Three Independent Cohorts From Two Continents?

Background Incidental durotomy is an intraoperative complication in spine surgery that can lead to postoperative complications, increased length of stay, and higher healthcare costs. Natural language processing (NLP) is an artificial intelligence method that assists in understanding free-text notes that may be useful in the automated surveillance of adverse events in orthopaedic surgery. A previously developed NLP algorithm is highly accurate in the detection of incidental durotomy on internal validation and external validation in an independent cohort from the same country. External validation in a cohort with linguistic differences is required to assess the transportability of the developed algorithm, referred to geographical validation. Ideally, the performance of a prediction model, the NLP algorithm, is constant across geographic regions to ensure reproducibility and model validity. Question/purpose Can we geographically validate an NLP algorithm for the automated detection of incidental durotomy across three independent cohorts from two continents? Methods Patients 18 years or older undergoing a primary procedure of (thoraco)lumbar spine surgery were included. In Massachusetts, between January 2000 and June 2018, 1000 patients were included from two academic and three community medical centers. In Maryland, between July 2016 and November 2018, 1279 patients were included from one academic center, and in Australia, between January 2010 and December 2019, 944 patients were included from one academic center. The authors retrospectively studied the free-text operative notes of included patients for the primary outcome that was defined as intraoperative durotomy. Incidental durotomy occurred in 9% (93 of 1000), 8% (108 of 1279), and 6% (58 of 944) of the patients, respectively, in the Massachusetts, Maryland, and Australia cohorts. No missing reports were observed. Three datasets (Massachusetts, Australian, and combined Massachusetts and Australian) were divided into training and holdout test sets in an 80:20 ratio. An extreme gradient boosting (an efficient and flexible tree-based algorithm) NLP algorithm was individually trained on each training set, and the performance of the three NLP algorithms (respectively American, Australian, and combined) was assessed by discrimination via area under the receiver operating characteristic curves (AUC-ROC; this measures the model's ability to distinguish patients who obtained the outcomes from those who did not), calibration metrics (which plot the predicted and the observed probabilities) and Brier score (a composite of discrimination and calibration). In addition, the sensitivity (true positives, recall), specificity (true negatives), positive predictive value (also known as precision), negative predictive value, Fl-score (composite of precision and recall), positive likelihood ratio, and negative likelihood ratio were calculated. Results The combined NLP algorithm (the combined Massachusetts and Australian data) achieved excellent performance on independent testing data from Australia (AUC-ROC 0.97 [95% confidence interval 0.87 to 0.99]), Massachusetts (AUC-ROC 0.99 [95% CI 0.80 to 0.99]) and Maryland (AUC-ROC 0.95 [95% CI 0.93 to 0.97]). The NLP developed based on the Massachusetts cohort had excellent performance in the Maryland cohort (AUC-ROC 0.97 [95% CI 0.95 to 0.99]) but worse performance in the Australian cohort (AUC-ROC 0.74 [95% CI 0.70 to 0.77]). Conclusion We demonstrated the clinical utility and reproducibility of an NLP algorithm with combined datasets retaining excellent performance in individual countries relative to algorithms developed in the same country alone for detection of incidental durotomy. Further multi-institutional, international collaborations can facilitate the creation of universal NLP algorithms that improve the quality and safety of orthopaedic surgery globally. The combined NLP algorithm has been incorporated into a freely accessible web application that can be found at https://sorg-apps.shinyapps.io/nlp_incidental_durotomy/. Clinicians and researchers can use the tool to help incorporate the model in evaluating spine registries or quality and safety departments to automate detection of incidental durotomy and optimize prevention efforts

Difference in Pain, Complication Rates, and Clinical Outcomes After Suprapatellar Versus Infrapatellar Nailing for Tibia Fractures?:A Systematic Review of 1447 Patients

OBJECTIVES: To assess the effectiveness of suprapatellar (SP)-nailing versus infrapatellar (IP)-nailing of tibia fractures in anterior knee pain, complications (retropatellar chondropathy, infection, and malalignment) and physical functioning and quality of life. A clinical question-driven and thorough systematic review of current literature is provided. DATA SOURCE: PubMed and Embase databases were searched for studies published between 2010 and 2020 relating to SP and IP-nailing of tibia fractures. The study is performed in concordance with PRISMA-guidelines. STUDY SELECTION: Studies eligible for inclusion were randomized controlled trials, prospective and retrospective observational studies reporting on outcomes of interest. DATA EXTRACTION: Data extraction was performed independently by 2 assessors. Methodological quality and risk of bias was assessed according to the guidelines of the McMaster Critical Appraisal. DATA SYNTHESIS: Continuous variables are presented as means with SD and dichotomous variables as frequency and percentages. The weighted mean, standardized weighted mean differences, and 95% confidence interval were calculated. A pooled analysis could not be performed because of differences in outcome measures, time-points, and heterogeneity. RESULTS: Fourteen studies with 1447 patients were analyzed. The weighted incidence of anterior knee pain was 29% after SP-nailing and 39% after IP-nailing, without reported significance. There was a significant lower rate of malalignment after the SP-approach (4% vs. 26%) with small absolute differences in all planes. No substantial differences were observed in retropatellar chondropathy, infection, physical functioning, and quality of life. CONCLUSIONS: This systematic review does not reveal superiority of either technique in any of the respective outcomes of interest. Definitive choice should depend on the surgeon's experience and available resources. LEVEL OF EVIDENCE: Therapeutic Level II. See Instructions for Authors for a complete description of levels of evidence