Is faster better? Impact of operative time on postoperative outcomes after VATS anatomical pulmonary resection

BackgroundVideo-assisted thoracic surgery (VATS) is now the preferred approach for standard anatomical pulmonary resections. This study evaluates the impact of operative time (OT) on post-operative outcomes after VATS anatomical pulmonary resection for non-small cell lung cancer (NSCLC).MethodsWe retrospectively reviewed all consecutive patients undergoing VATS lobectomy or segmentectomy for NSCLC between November 2010 and December 2019. Postoperative outcomes were compared between short (<150 minutes) and long (≥150 minutes) OT groups. A multivariable analysis was performed to identify predictors of long OT and overall post-operative complications.ResultsA total of 670 patients underwent lobectomy (n=496, 74%) or segmentectomy (n=174, 26%) for NSCLC. Mediastinal lymph node dissection was performed in 621 patients (92.7%). The median OT was 141 minutes (SD: 47 minutes) and 387 patients (57.8%) were operated within 150 minutes. Neoadjuvant chemotherapy was given in 25 patients (3.7%). Conversion thoracotomy was realized in 40 patients (6%). Shorter OT was significantly associated with decreased post-operative overall complication rate (30% vs. 41%; P=0.003), shorter median length of drainage (3 vs. 4 days; P<0.001) and shorter median length of hospital stay (6 vs. 7 days; P<0.001). On multivariable analysis, long OT (≥150 minutes) (OR 1.64, P=0.006), ASA score >2 (OR 1.87, P=0.001), FEV₁ <80% (OR 1.47, P=0.046) and DLCO <80% (OR 1.5, P=0.045) were significantly associated with postoperative complications. Two predictors of long OT were identified: neoadjuvant chemotherapy (OR 3.11, P=0.01) and lobectomy (OR 1.5, P=0.032).ConclusionsA prolonged OT is significantly associated with postoperative complications in our collective of patients undergoing VATS anatomical pulmonary resection.     

High-affinity autoreactive plasma cells disseminate through multiple organs in patients with immune thrombocytopenic purpura

The major therapeutic goal for immune thrombocytopenic purpura (ITP) is to restore normal platelet counts using drugs to promote platelet production or by interfering with mechanisms responsible for platelet destruction. Eighty percent of patients with ITP possess anti–integrin αIIbβ3 IgG autoantibodies that cause platelet opsonization and phagocytosis. The spleen is considered the primary site of autoantibody production by autoreactive B cells and platelet destruction. The immediate failure in approximately 50% of patients to recover a normal platelet count after anti-CD20 rituximab-mediated B cell depletion and splenectomy suggests that autoreactive, rituximab-resistant, IgG-secreting B cells (IgG-SCs) reside in other anatomical compartments. We analyzed more than 3,300 single IgG-SCs from spleen, bone marrow, and/or blood of 27 patients with ITP, revealing high interindividual variability in affinity for αIIbβ3, with variations over 3 logs. IgG-SC dissemination and range of affinities were, however, similar for each patient. Longitudinal analysis of autoreactive IgG-SCs upon treatment with the anti-CD38 mAb daratumumab demonstrated variable outcomes, from complete remission to failure with persistence of high-affinity anti–αIIbβ3 IgG-SCs in the bone marrow. This study demonstrates the existence and dissemination of high-affinity autoreactive plasma cells in multiple anatomical compartments of patients with ITP that may cause the failure of current therapies.     

Improving GWAS discovery and genomic prediction accuracy in biobank data

Genetically informed, deep-phenotyped biobanks are an important research resource and it is imperative that the most powerful, versatile, and efficient analysis approaches are used. Here, we apply our recently developed Bayesian grouped mixture of regressions model (GMRM) in the UK and Estonian Biobanks and obtain the highest genomic prediction accuracy reported to date across 21 heritable traits. When compared to other approaches, GMRM accuracy was greater than annotation prediction models run in the LDAK or LDPred-funct software by 15% (SE 7%) and 14% (SE 2%), respectively, and was 18% (SE 3%) greater than a baseline BayesR model without single-nucleotide polymorphism (SNP) markers grouped into minor allele frequency–linkage disequilibrium (MAF-LD) annotation categories. For height, the prediction accuracy R² was 47% in a UK Biobank holdout sample, which was 76% of the estimated hSNP2. We then extend our GMRM prediction model to provide mixed-linear model association (MLMA) SNP marker estimates for genome-wide association (GWAS) discovery, which increased the independent loci detected to 16,162 in unrelated UK Biobank individuals, compared to 10,550 from BoltLMM and 10,095 from Regenie, a 62 and 65% increase, respectively. The average χ2 value of the leading markers increased by 15.24 (SE 0.41) for every 1% increase in prediction accuracy gained over a baseline BayesR model across the traits. Thus, we show that modeling genetic associations accounting for MAF and LD differences among SNP markers, and incorporating prior knowledge of genomic function, is important for both genomic prediction and discovery in large-scale individual-level studies.

As biobank datasets increase in size, it is important to understand the factors limiting the prediction of phenotype from genotype. Alongside others, we have recently shown that genomic prediction accuracy can be improved through the use of random-effects models that incorporate prior knowledge of genomic annotations and allow for differences in the variance explained by single-nucleotide polymorphism (SNP) markers, depending upon their linkage disequilibrium (LD) and their minor allele frequency (MAF) (1–8). These improvements in prediction accuracy should also translate into greater genome-wide association study (GWAS) discovery power. Mixed-linear models of association (MLMA) are commonly applied in GWASs in a two-step approach, where a random-effects model is first used to estimate leave-one-chromosome-out (LOCO) genetic values, and these are then used in a second marginal regression coefficient estimation step. Theory suggests that the test statistics obtained in the MLMA second step depend upon the accuracy of the LOCO genomic predictors produced from the first step. Current MLMA implementations use a blocked ridge regression model (9), a Restricted Maximum Likelihood (REML) genomic relationship model (10), or a Bayesian spike-and-slab model (11) within the first step.Here, we improve the computational implementation of our recently developed Bayesian grouped mixture of regressions model (GMRM), which estimates genetic marker effects jointly, but with independent marker inclusion probabilities and independent hSNP2 parameters across LD, MAF, and functional annotation groups (Materials and Methods). This allows us to apply the model to 21 traits in the UK Biobank to test for prediction accuracy improvements over existing approaches. We then extend the model to provide MLMA SNP marker association estimates to test whether improved prediction accuracy translates to improved GWAS discovery compared to existing MLMA approaches.     

Comparative evaluation of a heparin‐citrate anticoagulation for LDL‐apheresis in two primary apheresis systems

BACKGROUND: As COBE Spectra has been replaced in many parts of the world, we describe a new protocol for low‐density lipoprotein (LDL)‐apheresis performed on familial hypercholesterolemia patients for the Spectra Optia platform. METHODS: For all procedures, after administering a bolus of heparin of 2,500 U, 10,000 U of heparin added to a 600 ml ACD‐A bag was used as anticoagulant (AC). In a first phase (A), 16 apheresis procedures with COBE Spectra using an inlet:AC ratio of 25:1 were compared to 18 LDL‐apheresis treatments with Spectra Optia at split Inlet:AC ratios of 16:1/18:1 or 20:1/25:1. Platelet activation and coagulation markers were assessed. In a follow‐up phase (B), 20 procedures on Spectra Optia using an inlet:AC ratio of 20:1 were performed. RESULTS: Although coagulation markers and platelet activation analyzed were similar in both apheresis devices used, COBE Spectra procedures did not show any visual clumping in the sets. Visual analysis of clumping was highest in the Spectra Optia's 20:1/25:1 AC regimen (5/8 procedures). For the lowest Spectra Optia, AC regimen and during the follow‐up phase reversible clump formation in the disposable set was similar (1/10 procedures). Clumping was successfully reversed in all cases by temporarily lowering the inlet:AC ratio to 18:1. Blood cell counts (WBC, Plt, Hct) were similar for both COBE Spectra and Spectra Optia procedures. Spectra Optia had a significantly higher plasma removal efficiency versus COBE Spectra (84% vs.75%, P < .05). No serious adverse events were observed. CONCLUSION: Apheresis procedures on the Spectra Optia system with low‐dose heparin‐citrate anticoagulation are feasible and safe.     

DPP4 inhibitor-induced polyarthritis: a report of three cases

Dipeptidyl peptidase-4 (DPP4) inhibitors are a novel therapy widespread used in type 2 diabetes mellitus. We describe 3 cases of polyarthritis which delay of appearance strongly suggests a link with DPP4 inhibitors. Three patients presented with bilateral, symmetrical, seronegative polyarthritis after introduction of DPP4 inhibitors (sitagliptine (n = 2) and vildagliptine (n = 1)). Two patients also developed xerostomia and xerostomia, and laboratory test results showed normal values of CRP and erythrocyte sedimentation rate. Joints X-rays were normal. One patient was diagnosed with primary Sjögren’s syndrome and treated with hydroxychloroquine, methotrexate and prednisone, with a poor efficacy. When sitagliptine was stopped, all symptoms disappeared, leading to methotrexate and prednisone discontinuation within a month. There were no immunological abnormalities in the 2 other patients, but a chronic viral hepatitis B was found in one patient. Eventually, discontinuation of DPP4 inhibitors led to resolution of symptoms in 1 and 3 weeks for both patients. DPP4 inhibitors seemed to trigger bilateral, non-erosive, seronegative polyarthritis in our 3 patients. DPP4, also known as CD26, is expressed on many cells including lymphocytes and fibroblasts, and its inhibition may lead to immunomodulating effect as suggested by clinical and in vitro studies.