Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies.

Many growth factors and cytokines signal by binding to the extracellular domains of their receptors and driving association and transphosphorylation of the receptor intracellular tyrosine kinase domains, initiating downstream signaling cascades. To enable systematic exploration of how receptor valency and geometry affect signaling outcomes, we designed cyclic homo-oligomers with up to 8 subunits using repeat protein building blocks that can be modularly extended. By incorporating a de novo-designed fibroblast growth factor receptor (FGFR)-binding module into these scaffolds, we generated a series of synthetic signaling ligands that exhibit potent valency- and geometry-dependent Ca2+ release and mitogen-activated protein kinase (MAPK) pathway activation. The high specificity of the designed agonists reveals distinct roles for two FGFR splice variants in driving arterial endothelium and perivascular cell fates during early vascular development. Our designed modular assemblies should be broadly useful for unraveling the complexities of signaling in key developmental transitions and for developing future therapeutic applications.

Safety and efficacy of ibrutinib in combination with rituximab and lenalidomide in previously untreated follicular and marginal zone lymphoma: An open label, phase 2 study.

BACKGROUND: Follicular lymphoma (FL) and marginal zone lymphoma (MZL) are indolent non-Hodgkin lymphomas (iNHL). Median survival for iNHL is approximately 20 years. Because standard treatments are not curative, patients often receive multiple lines of therapy with associated toxicity-rationally designed, combination therapies with curative potential are needed. The immunomodulatory drug lenalidomide was evaluated in combination with rituximab for the frontline treatment of FL in the phase 3 RELEVANCE study. Ibrutinib, an oral Bruton tyrosine kinase inhibitor, is active in NHL and was evaluated in combination with lenalidomide, rituximab, and ibrutinib (IRR) in a phase 1 study. METHODS: The authors conducted an open-label, phase 2 clinical trial of IRR for previously untreated FL and MZL. The primary end point was progression-free survival (PFS) at 24 months. RESULTS: This study included 48 participants with previously untreated FL grade 1-3a (N = 38), or MZL (N = 10). Participants received 12, 28-day cycles of lenalidomide (15 mg, days 1-21 cycle 1; 20 mg, cycles 2-12), rituximab (375 mg/m2 weekly in cycle 1; day 1 cycles 2-12), and ibrutinib 560 mg daily. With a median follow-up of 65.3 months, the estimated PFS at 24 months was 78.8% (95% confidence interval [CI], 68.0%-91.4%) and 60-month PFS was 59.7% (95% CI, 46.6%-76.4%). One death occurred unrelated to disease progression. Grade 3-4 adverse events were observed in 64.6%, including 50% with grade 3-4 rash. CONCLUSIONS: IRR is highly active as frontline therapy for FL and MZL. Compared to historical results with lenalidomide and rituximab, PFS is similar with higher grade 3-4 toxicity, particularly rash. The study was registered with ClinicalTrials.gov (NCT02532257).

FER and LecRK show haplotype-dependent cold-responsiveness and mediate freezing tolerance in Lotus japonicus.

Many plant species have succeeded in colonizing a wide range of diverse climates through local adaptation, but the underlying molecular genetics remain obscure. We previously found that winter survival was a direct target of selection during colonization of Japan by the perennial legume Lotus japonicus and identified associated candidate genes. Here, we show that two of these, FERONIA-receptor like kinase (LjFER) and a S-receptor-like kinase gene (LjLecRK), are required for non-acclimated freezing tolerance and show haplotype-dependent cold-responsive expression. Our work suggests that recruiting a conserved growth regulator gene, FER, and a receptor-like kinase gene, LecRK, into the set of cold-responsive genes has contributed to freezing tolerance and local climate adaptation in L. japonicus, offering functional genetic insight into perennial herb evolution.

Development and validation of an artificial intelligence model for the classification of hip fractures using the AO-OTA framework.

BACKGROUND AND PURPOSE: Artificial intelligence (AI) has the potential to aid in the accurate diagnosis of hip fractures and reduce the workload of clinicians. We primarily aimed to develop and validate a convolutional neural network (CNN) for the automated classification of hip fractures based on the 2018 AO-OTA classification system. The secondary aim was to incorporate the model's assessment of additional radiographic findings that often accompany such injuries. METHODS: 6,361 plain radiographs of the hip taken between 2002 and 2016 at Danderyd University Hospital were used to train the CNN. A separate set of 343 radiographs representing 324 unique patients was used to test the performance of the network. Performance was evaluated using area under the curve (AUC), sensitivity, specificity, and Youden's index. RESULTS: The CNN demonstrated high performance in identifying and classifying hip fracture, with AUCs ranging from 0.76 to 0.99 for different fracture categories. The AUC for hip fractures ranged from 0.86 to 0.99, for distal femur fractures from 0.76 to 0.99, and for pelvic fractures from 0.91 to 0.94. For 29 of 39 fracture categories, the AUC was ≥ 0.95. CONCLUSION: We found that AI has the potential for accurate and automated classification of hip fractures based on the AO-OTA classification system. Further training and modification of the CNN may enable its use in clinical settings.

Artificial intelligence can be used in the identification and classification of shoulder osteoarthritis and avascular necrosis on plain radiographs: a training study of 7,139 radiograph sets.

BACKGROUND AND PURPOSE: Knowledge concerning the use AI models for the classification of glenohumeral osteoarthritis (GHOA) and avascular necrosis (AVN) of the humeral head is lacking. We aimed to analyze how a deep learning (DL) model trained to identify and grade GHOA on plain radiographs performs. Our secondary aim was to train a DL model to identify and grade AVN on plain radiographs. PATIENTS AND METHODS: A modified ResNet-type network was trained on a dataset of radiographic shoulder examinations from a large tertiary hospital. A total of 7,139 radiographs were included. The dataset included various projections of the shoulder, and the network was trained using stochastic gradient descent. Performance evaluation metrics, area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were used to assess the network's performance for each outcome. RESULTS: The network demonstrated AUC values ranging from 0.73 to 0.93 for GHOA classification and > 0.90 for all AVN classification classes. The network exhibited lower AUC for mild cases compared with definitive cases of GHOA. When none and mild grades were combined, the AUC increased, suggesting difficulties in distinguishing between these 2 grades. CONCLUSION: We found that a DL model can be trained to identify and grade GHOA on plain radiographs. Furthermore, we show that a DL model can identify and grade AVN on plain radiographs. The network performed well, particularly for definitive cases of GHOA and any level of AVN. However, challenges remain in distinguishing between none and mild GHOA grades.

ChatGPT-4 generates orthopedic discharge documents faster than humans maintaining comparable quality: a pilot study of 6 cases.

BACKGROUND AND PURPOSE: Large language models like ChatGPT-4 have emerged. They hold the potential to reduce the administrative burden by generating everyday clinical documents, thus allowing the physician to spend more time with the patient. We aimed to assess both the quality and efficiency of discharge documents generated by ChatGPT-4 in comparison with those produced by physicians. PATIENTS AND METHODS: To emulate real-world situations, the health records of 6 fictional orthopedic cases were created. Discharge documents for each case were generated by a junior attending orthopedic surgeon and an advanced orthopedic resident. ChatGPT-4 was then prompted to generate the discharge documents using the same health record information. The quality assessment was performed by an expert panel (n = 15) blinded to the source of the documents. As secondary outcome, the time required to generate the documents was compared, logging the duration of the creation of the discharge documents by the physician and by ChatGPT-4. RESULTS: Overall, both ChatGPT-4 and physician-generated notes were comparable in quality. Notably, ChatGPT-4 generated discharge documents 10 times faster than the traditional method. 4 events of hallucinations were found in the ChatGPT-4-generated content, compared with 6 events in the human/physician produced notes. CONCLUSION: ChatGPT-4 creates orthopedic discharge notes faster than physicians, with comparable quality. This shows it has great potential for making these documents more efficient in orthopedic care. ChatGPT-4 has the potential to significantly reduce the administrative burden on healthcare professionals.

Long-term outcomes in patients with chronic lymphocytic leukemia treated with ibrutinib: Focus on hypertension and cardiovascular toxicity.

BACKGROUND: Continuous ibrutinib administration is needed to maintain efficacy in patients with chronic lymphocytic leukemia (CLL) and, as such, long-term toxicity is a concern. The authors report the 5-year follow-up of patients with CLL who received treatment with ibrutinib with a focus on hypertension and cardiovascular toxicities. METHODS: Patient characteristics were assessed, including blood pressure, cardiovascular disease, disease progression, and death. Univariate logistic regression analysis assessed the relation of patient characteristics and the development of new or worsened hypertension. The incidence of hypertensive outcomes was evaluated using competing risk. Survival was estimated using the Kaplan-Meier method. RESULTS: Three hundred patients with CLL who were treated with ibrutinib on clinical trials were included. The median patient age at study enrollment was 65 years (range, 29-83 years). Seventy percent of patients were men, and 88% were Caucasian. Sixty-nine percent of patients had hypertension at baseline, and 47% were on antihypertensive medication. Eighty-eight percent had relapsed or refractory CLL. New-onset and worsening hypertension were common, occurring in 68.5% and 38% of patients, respectively. Systolic blood pressure ≥160 mm Hg or diastolic blood pressure ≥100 mm Hg was observed in 16.9% of patients. Hypertension was reversible after ibrutinib discontinuation. Older age, male sex, tobacco use, and chronic kidney disease were associated with ibrutinib-related hypertension. Baseline hypertension was not associated with major adverse cardiovascular events in ibrutinib-treated patients nor with event-free or overall survival. CONCLUSIONS: Hypertension is a common toxicity in patients with CLL who receive ibrutinib but is manageable in most patients. Other than chronic kidney disease, baseline cardiovascular disease did not affect ibrutinib-related hypertension nor was hypertension associated with major adverse cardiovascular events or survival. PLAIN LANGUAGE SUMMARY: Ibrutinib is an effective treatment for patients with chronic lymphocytic leukemia. Ibrutinib is a well tolerated therapy, however hypertension can develop or worsen in patients receiving ibrutinib and other cardiovascular events are significant challenges to the use of this drug. This may be particularly true in patients with heart disease. Short-term side effects may worsen heart disease, but the long-term impact is unknown. The long-term results of ibrutinib on heart disease and hypertension are described.

Relationships between T-lymphocytes and physical function in adults with chronic lymphocytic leukemia: Results from the HEALTH4CLL pilot study.

OBJECTIVE: Examine physical function and T-cell phenotype in patients with chronic lymphocytic leukemia (CLL) before and after a physical activity (PA) intervention. METHODS: Physical function measures and blood samples were collected from CLL patients (Rai stage 0-4, 50% receiving targeted therapy, N = 24) enrolled in a 16-week intervention of at-home aerobic and/or resistance exercise. Flow cytometry characterized T-cells in cryopreserved peripheral blood cells. Wilcoxon signed-rank test compared physical function and T-cell phenotype at baseline and 16-weeks; Kendall's Tau assessed associations between variables. RESULTS: Godin leisure-time PA score increased from baseline to 16-weeks (mean difference: 14.61, p < .01) and fatigue decreased (mean difference: 6.71, p < .001). At baseline, lower fatigue correlated with a lower proportion of CD8+ T-cells (τ = 0.32, p = .03) and cardiorespiratory fitness (CRF) inversely correlated with the percentage of PD-1+CD8+ T-cells (τ -0.31, p = .03). At 16-weeks, CRF inversely correlated with the proportion of PD-1+CD4+ T-cells (τ -0.34, p = .02). Reduced fatigue at 16-weeks correlated with an increased CD4:CD8 ratio (τ = 0.36, p = .02) and lower percentage of HLA-DR+PD-1+CD4+ T-cells (τ = -0.37, p = .01). CONCLUSIONS: This intervention increased leisure-time PA and decreased fatigue in CLL patients. These changes correlated with an increased CD4:CD8 T-cell ratio and reduced proportion of T-cells subsets previously associated with poor outcomes in CLL patients. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02194387.

Increased mortality after total hip prosthetic joint infection is mainly caused by the comorbidities rather than the infection itself.

BACKGROUND AND PURPOSE: Periprosthetic joint infection (PJI) is a feared complication of arthroplasty surgery. There is controversy as to whether PJI also correlates with increased mortality. Our aim was to investigate in a nationwide cohort if PJI is an independent risk factor for dying. PATIENTS AND METHODS: We performed a retrospective cohort study based on data from the Swedish Hip Arthroplasty Register (SHAR). All patients with a revision THA performed between 1998 and 2017 were included. The outcome is mortality; exposure is PJI according to SHAR. The control group was study participants who underwent aseptic revision. Confounders were age, sex, diagnosis, and comorbidity according to the Elixhauser index. The outcome was analyzed with a Cox proportional hazards model. RESULTS: 4,943 PJI revisions and 12,529 non-infected revisions were included in the analysis. The median follow-up time was 4.1 years. In the PJI group, 1,972 patients died and in the control group, 4,512. The incidence rate ratio was 1.19 (95% confidence interval [CI] 1.13-1.25), the crude hazard ratio (HR) 1.19 (CI 1.13-1.25), and the adjusted HR 1.05 (CI 0.99-1.12) for the exposed versus the unexposed group. The strongest confounder was comorbidity. CONCLUSION: The increased mortality risk after revision due to PJI is mainly caused by the comorbidity of the patient, rather than by the infection itself.

Inference-Based Quantum Sensing.

In a standard quantum sensing (QS) task one aims at estimating an unknown parameter θ, encoded into an n-qubit probe state, via measurements of the system. The success of this task hinges on the ability to correlate changes in the parameter to changes in the system response R(θ) (i.e., changes in the measurement outcomes). For simple cases the form of R(θ) is known, but the same cannot be said for realistic scenarios, as no general closed-form expression exists. In this Letter, we present an inference-based scheme for QS. We show that, for a general class of unitary families of encoding, R(θ) can be fully characterized by only measuring the system response at 2n+1 parameters. This allows us to infer the value of an unknown parameter given the measured response, as well as to determine the sensitivity of the scheme, which characterizes its overall performance. We show that inference error is, with high probability, smaller than δ, if one measures the system response with a number of shots that scales only as Ω(log^{3}(n)/δ^{2}). Furthermore, the framework presented can be broadly applied as it remains valid for arbitrary probe states and measurement schemes, and, even holds in the presence of quantum noise. We also discuss how to extend our results beyond unitary families. Finally, to showcase our method we implement it for a QS task on real quantum hardware, and in numerical simulations.

Mass to voltage ratio index predicts mortality following TAVI.

Transcatheter aortic valve implantation (TAVI) is commonly performed in elderly patients with aortic stenosis. Better methods of risk stratification are needed in this population with high morbidity. There is a relatively high incidence of cardiac amyloidosis in this population and high LV mass index (LVMI) to QRS voltage may help identify patients with worse prognosis following TAVI. This retrospective study enrolled consecutive patients who underwent TAVI in our institution between the years 2008-2019. Mass voltage ratio index (MVRi) was calculated as the ratio of LV mass index on echocardiogram to voltage using the Sokolow-Lyon criteria on 12 lead ECG performed within 3 months before the intervention. Two hundred and fifty-one patients (mean age 80.8 years, 49% men) were enrolled. One hundred and sixty-eight (67%) patients were alive at 3 years follow up. MVRi was a statistically significant predictor of 3 year mortality (p < 0.005). Patients were divided categorically into tertiles based on MVRi score; the "high" group had significantly higher 3-year mortality (p < 0.001). In the multivariate model only Euroscore (p < 0.009) and MVRi (p < 0.011; OR: 2.32; CI: 1.15-4.964) were statistically significant predictors of mortality. The "high" group had a significantly lower survival rate after 3 years follow up on Kaplan-Meier analysis (p < 0.001). Our findings suggest that MVRi is a strong, independent predictor of increased post-TAVI mortality. This may be a simple clinical tool to assist in the assessment of patients prior to before TAVI.

Unusual complications in the management of chronic lymphocytic leukemia.

Chronic lymphocytic leukemia (CLL) is a common, indolent disease that typically presents with a proliferation of mature, immunologically dysfunctional CD5+ B-cells which preferentially occupy the bone marrow, peripheral blood and lymphoid organs. Immune dysfunction leads to an increase in autoimmune diseases which occur in approximately 10% of patients with CLL. Autoimmune cytopenias are the most common, but other organs may be affected as well. The treatment of these conditions typically depends on the extent of CLL and severity of symptoms, but generally consists of CLL-directed therapies, immunosuppression or both. CLL may also infiltrate extranodal sites in the body. Symptomatic extranodal CLL or extranodal disease which threatens normal organ function is an indication for initiation of CLL-directed therapy. The following review summarizes autoimmune and extranodal complications that can occur in patients with CLL and our suggested approach to their treatment.

Similar periprosthetic joint infection rates after and before a national infection control program: a study of 45,438 primary total knee arthroplasties.

Background and purpose - Strenuous efforts to minimize postoperative infection rates have been made, including the Swedish nationwide initiative Prosthesis Related Infections Shall be Stopped (PRISS). This study calculated the incidence rate of periprosthetic joint infection (PJI) following primary total knee arthroplasty (TKA) before and after PRISS. Patients and methods - All 45,438 primary TKAs registered in the Swedish Knee Arthroplasty Register (SKAR) during 2007-2008 and 2012-2013 were included. Matched data on antibiotic prescriptions were obtained from the Swedish Prescribed Drug Register (SPDR). All patients with ≥ 28 days of continuous antibiotic treatment within 2 years of primary surgery had their medical charts reviewed to identify cases of PJI. The incidence rate was calculated by dividing the number of PJIs by the total time at risk during each time period and presented as percentages with 95% confidence interval (CI). Results - 644 PJIs were identified, equaling a 2-year incidence rate of 1.45% (CI 1.34-1.57). The incidence rate was 1.44% (CI 1.27-1.61) before PRISS and 1.46% (CI 1.31-1.61) after. Diagnosis was made within 30 days of primary TKA in 52%, and within 90 days in 73% of cases. 603 cases were reoperated on or revised. Median time from operation to diagnosis was 29 days (1-716), for both time periods. Debridement with exchange of the insert was performed in 32% and 63% of cases before and after PRISS, respectively. Interpretation - We found similar incidence rates before and after the PRISS initiative without any statistically significant difference. Time to diagnosis was similar during both time periods. The project may have contributed to increased compliance with treatment protocols.

Study protocol: The DAICY trial-dual versus single-antibiotic impregnated cement in primary hemiarthroplasty for femoral neck fracture-a register-based cluster-randomized crossover-controlled trial.

BACKGROUND AND PURPOSE: Older patients with a displaced femoral neck fracture (FNF) are often treated with a cemented primary hemiarthroplasty (HA). The DAICY trial investigates whether high-dose dual-impregnated antibioticloaded cement (DIAC) including gentamicin and clindamycin can reduce the risk of periprosthetic joint infection (PJI) in comparison with low-dose single-impregnated gentamicin antibiotic-loaded cement (SIAC), in patients ≥ 60 years treated with a cemented HA for a displaced FNF. STUDY DESIGN: The trial is a national, multicenter, register-based, cluster-randomized, crossover trial. Patients ≥ 60 years with a non-pathological, displaced FNF (Type Garden 3-4/AO 31-B2 or B3) suitable for HA according to local guidelines are eligible for inclusion. Participating orthopedic departments will be randomized to start with either SIAC (control group) or DIAC treatment (intervention group) for 2 years. After 2 years, the study departments will then change to the other treatment arm for the remaining 2 years of the study. Approximately 7,000 patients will be included. The study is pragmatic in that the choice of implant brands, surgical approach and peri- and postoperative protocols follow the local routines of each participating department. All outcome variables will be retrieved after linkage of the study cohort to the following Swedish registers: the Fracture Register, the Arthroplasty Register, the National Patient Register and the Prescribed Drug Registry Outcome: The primary outcome will be periprosthetic joint infection of the index joint within 1 year after surgery. Secondary outcomes will be any reoperation on the index joint, mortality within 90 days and 1 year, resistance patterns of causative bacteria in cases of PJI, and health economics. Potential added value: This trial is designed to support or refute the efficacy of DIAC used in patients with a displaced FNF, potentially reducing PJI and resource allocation. Start of the trial and estimated duration - The DAICY trial started recruiting patients in January 2022 and will continue recruiting for approximately 4 years. Complete follow-up expected in 5 years.

Medical comorbidities in patients with chronic lymphocytic leukaemia treated with idelalisib: analysis of two large randomised clinical trials.

Comorbidities influence survival in patients with chronic lymphocytic leukaemia (CLL) treated with chemo-immunotherapy or ibrutinib. While idelalisib has been studied in patients with comorbidities, their impact has not been investigated. We analysed 481 patients treated with idelalisib on two randomised trials (NCT01659021 and NCT01539512). Comorbidities were assessed using the Cumulative Illness Risk Scale (CIRS). Patients received idelalisib + anti-CD20 (rituximab or ofatumumab; n = 284) or anti-CD20 alone (n = 197). The median age was 69 years. We found that comorbidities did not significantly affect outcomes of idelalisib therapy. The objective response rate (ORR) was 79·3% versus 85·8%, the median progression-free survival (PFS) was 16·3 versus 19·1 months, and the median overall survival (OS) was 39·8 versus 49·8 months in patients treated with idelalisib who had a CIRS score of >6 versus ≤6, correspondingly. Treatment with idelalisib + anti-CD20 was associated with superior PFS and ORR when compared to anti-CD20 monotherapy in patients who had high comorbidities (CIRS score of >6) or at least one severe comorbidity (median PFS 16·3 vs. 6·9 months and 16·6 vs. 6·5 months; odds ratio 20·1 and 33·2; P < 0·0001). Thus, comorbidities do not portend inferior outcomes in patients with CLL treated with idelalisib in combination with anti-CD20 therapy.

Outcomes of Burkitt lymphoma with central nervous system involvement: evidence from a large multicenter cohort study.

Central nervous system (CNS) involvement in Burkitt lymphoma (BL) poses a major therapeutic challenge, and the relative ability of contemporary regimens to treat CNS involvement remains uncertain. We described prognostic significance of CNS involvement and incidence of CNS recurrence/progression after contemporary immunochemotherapy using real-world clinicopathologic data on adults with BL diagnosed between 2009 and 2018 across 30 US institutions. We examined associations between baseline CNS involvement, patient characteristics, complete response (CR) rates, and survival. We also examined risk factors for CNS recurrence. Nineteen percent (120/641) of patients (age 18-88 years) had CNS involvement. It was independently associated with HIV infection, poor performance status, involvement of ≥2 extranodal sites, or bone marrow involvement. First-line regimen selection was unaffected by CNS involvement (P=0.93). Patients with CNS disease had significantly lower rates of CR (59% versus 77% without; P<0.001), worse 3-year progression-free survival (adjusted hazard ratio [aHR], 1.53, 95% confidence interval [CI], 1.14-2.06, P=0.004) and overall survival (aHR, 1.62, 95%CI, 1.18-2.22, P=0.003). The 3-year cumulative incidence of CNS recurrence was 6% (95%CI, 4-8%). It was significantly lower among patients receiving other regimens (CODOX-M/IVAC, 4%, or hyperCVAD/MA, 3%) compared with DA-EPOCH-R (13%; adjusted sub-HR, 4.38, 95%CI, 2.16-8.87, P<0.001). Baseline CNS involvement in BL is relatively common and portends inferior prognosis independent of first-line regimen selection. In real-world practice, regimens with highly CNS-penetrant intravenous systemic agents were associated with a lower risk of CNS recurrence. This finding may be influenced by observed suboptimal adherence to the strict CNS staging and intrathecal therapy procedures incorporated in DA-EPOCH-R.

Intensive induction regimens after deferring initial therapy for mantle cell lymphoma are not associated with improved survival.

INTRODUCTION: While most patients with mantle cell lymphoma (MCL) receive therapy shortly after diagnosis, a subset of patients with indolent-behaving disease can safely defer treatment. In this subgroup, we evaluated the importance of treatment intensity in patients with MCL who defer initial therapy. METHODS: Out of 1134 patients with MCL from 12 academic centers, we analyzed 219 patients who initiated therapy at least 90 days after diagnosis. Patients who received induction with high-dose cytarabine and/or autologous stem cell transplantation (ASCT) in first remission were considered to have received intensive therapy (n = 88) while all other approaches were non-intensive (n = 131). RESULTS: There was no difference in progression-free (PFS; P = .224) or overall survival (OS; P = .167) in deferred patients who received non-intensive vs. intensive therapy. Additionally, univariate and multivariate Cox proportional hazards models were performed for PFS and OS. Treatment at an academic center (HR 0.43, P = .015) was associated with improved OS in both univariate and multivariate models, while intensity of treatment was not associated with improved OS in either model. CONCLUSIONS: These results indicate that intensified initial treatment is not associated with improved survival after deferring initial therapy, although prospective studies are needed to determine which of these patients with MCL may benefit from intensive therapy.

Multi-center analysis of practice patterns and outcomes of younger and older patients with mantle cell lymphoma in the rituximab era.

Clinical outcomes and predictors of survival in patients with newly diagnosed mantle cell lymphoma (MCL) treated in the rituximab era (2000-2015) at 12 US academic centers were assessed to identify determinants of survival across age groups. Objectives were to characterize and compare practice patterns, outcomes and prognostic factors for survival in younger patients (age < 65) and older patients (age ≥ 65 years). Among 1162 patients included, 697 were younger and 465 were older. In younger patients, 2-year progression free survival (PFS) and overall survival (OS) rates were 79% and 92% respectively; blastoid histology, ECOG ≥ 2, and lack of maintenance rituximab (MR) remained statistically relevant to poor OS on univariate analysis (UVA) and multivariate analysis (MVA). In older patients, 2-year PFS and OS rates were 67% and 86% respectively; lack of maintenance rituximab remained significantly associated with inferior PFS and OS on UVA and MVA (p < 0.001). Two-year PFS rates were 79%, and 67% and 2-year OS rates were 92% and 86% for ages < 65 and ≥ 65 respectively (p < 0.001). First-line high-dose cytarabine exposure and/or MR lessened the negative impact of age on survival. Taken collectively, survival outcomes for older patients remain inferior to those of younger patients in the rituximab era. However, maintenance rituximab and potentially high-dose cytarabine-based induction can mitigate the negative impact of age on survival.

Automating classification of osteoarthritis according to Kellgren-Lawrence in the knee using deep learning in an unfiltered adult population.

BACKGROUND: Prevalence for knee osteoarthritis is rising in both Sweden and globally due to increased age and obesity in the population. This has subsequently led to an increasing demand for knee arthroplasties. Correct diagnosis and classification of a knee osteoarthritis (OA) are therefore of a great interest in following-up and planning for either conservative or operative management. Most orthopedic surgeons rely on standard weight bearing radiographs of the knee. Improving the reliability and reproducibility of these interpretations could thus be hugely beneficial. Recently, deep learning which is a form of artificial intelligence (AI), has been showing promising results in interpreting radiographic images. In this study, we aim to evaluate how well an AI can classify the severity of knee OA, using entire image series and not excluding common visual disturbances such as an implant, cast and non-degenerative pathologies. METHODS: We selected 6103 radiographic exams of the knee taken at Danderyd University Hospital between the years 2002-2016 and manually categorized them according to the Kellgren & Lawrence grading scale (KL). We then trained a convolutional neural network (CNN) of ResNet architecture using PyTorch. We evaluated the results against a test set of 300 exams that had been reviewed independently by two senior orthopedic surgeons who settled eventual interobserver disagreements through consensus sessions. RESULTS: The CNN yielded an overall AUC of more than 0.87 for all KL grades except KL grade 2, which yielded an AUC of 0.8 and a mean AUC of 0.92. When merging adjacent KL grades, all but one group showed near perfect results with AUC > 0.95 indicating excellent performance. CONCLUSION: We have found that we could teach a CNN to correctly diagnose and classify the severity of knee OA using the KL grading system without cleaning the input data from major visual disturbances such as implants and other pathologies.

Ankle fracture classification using deep learning: automating detailed AO Foundation/Orthopedic Trauma Association (AO/OTA) 2018 malleolar fracture identification reaches a high degree of correct classification.

Background and purpose - Classification of ankle fractures is crucial for guiding treatment but advanced classifications such as the AO Foundation/Orthopedic Trauma Association (AO/OTA) are often too complex for human observers to learn and use. We have therefore investigated whether an automated algorithm that uses deep learning can learn to classify radiographs according to the new AO/OTA 2018 standards.Method - We trained a neural network based on the ResNet architecture on 4,941 radiographic ankle examinations. All images were classified according to the AO/OTA 2018 classification. A senior orthopedic surgeon (MG) then re-evaluated all images with fractures. We evaluated the network against a test set of 400 patients reviewed by 2 expert observers (MG, AS) independently.Results - In the training dataset, about half of the examinations contained fractures. The majority of the fractures were malleolar, of which the type B injuries represented almost 60% of the cases. Average area under the area under the receiver operating characteristic curve (AUC) was 0.90 (95% CI 0.82-0.94) for correctly classifying AO/OTA class where the most common major fractures, the malleolar type B fractures, reached an AUC of 0.93 (CI 0.90-0.95). The poorest performing type was malleolar A fractures, which included avulsions of the fibular tip.Interpretation - We found that a neural network could attain the required performance to aid with a detailed ankle fracture classification. This approach could be scaled up to other body parts. As the type of fracture is an important part of orthopedic decision-making, this is an important step toward computer-assisted decision-making.