Citations

BackgroundPatients with implantable cardioverter defibrillators (ICDs) often have a history of atrial fibrillation (AF) or will develop AF after device implant. Optimal management of ICD patients includes early diagnosis of AF and monitoring of AF burden. We evaluated the performance of an algorithm for monitoring AF in single‐chamber ICDs.MethodsThe RR interval variability‐based detection algorithm determines RR variability by creating a Lorenz plot of the change in RR intervals for the most recent interval pair versus the previous interval pair. A new plot is created every 2 minutes and the AF evidence score of the plot is computed. Patient RR interval data from several Holter databases were pooled to test the performance of the AF detection algorithm.ResultsIn total, 187 recordings from 186 patients were used to assess the performance of the AF detection algorithm integrated into a single‐chamber ICD by comparing the ICD detection results to the Holter annotated truth. Thirty‐five of 186 patients had a total of 94 AF episodes in their Holter recordings lasting a total of 250.5 hours (mean episode duration 7.2 hours). The generalized estimating equations‐adjusted estimate of episode sensitivity was 94.8% with 95% lower confidence limit of 87.2%. Gross duration sensitivity was 95.0% for AF episodes of at least 6 minutes duration with gross duration specificity of 99.6%.ConclusionThis RR interval‐based AF detection algorithm performs well with high sensitivity and specificity. Integration of this algorithm into single‐chamber ICDs will help monitor and detect AF, thus facilitating optimal therapy to prevent AF‐related sequelae.

SummaryObjectivePosttraumatic seizures (PTS) are well‐recognized acute and chronic complications of traumatic brain injury (TBI). Risk factors have been identified, but considerable variability in who develops PTS remains. Existing PTS prognostic models are not widely adopted for clinical use and do not reflect current trends in injury, diagnosis, or care. We aimed to develop and internally validate preliminary prognostic regression models to predict PTS during acute care hospitalization, and at year 1 and year 2 postinjury.MethodsPrognostic models predicting PTS during acute care hospitalization and year 1 and year 2 post‐injury were developed using a recent (2011–2014) cohort from the TBI Model Systems National Database. Potential PTS predictors were selected based on previous literature and biologic plausibility. Bivariable logistic regression identified variables with a p‐value < 0.20 that were used to fit initial prognostic models. Multivariable logistic regression modeling with backward‐stepwise elimination was used to determine reduced prognostic models and to internally validate using 1,000 bootstrap samples. Fit statistics were calculated, correcting for overfitting (optimism).ResultsThe prognostic models identified sex, craniotomy, contusion load, and pre‐injury limitation in learning/remembering/concentrating as significant PTS predictors during acute hospitalization. Significant predictors of PTS at year 1 were subdural hematoma (SDH), contusion load, craniotomy, craniectomy, seizure during acute hospitalization, duration of posttraumatic amnesia, preinjury mental health treatment/psychiatric hospitalization, and preinjury incarceration. Year 2 significant predictors were similar to those of year 1: SDH, intraparenchymal fragment, craniotomy, craniectomy, seizure during acute hospitalization, and preinjury incarceration. Corrected concordance (C) statistics were 0.599, 0.747, and 0.716 for acute hospitalization, year 1, and year 2 models, respectively.SignificanceThe prognostic model for PTS during acute hospitalization did not discriminate well. Year 1 and year 2 models showed fair to good predictive validity for PTS. Cranial surgery, although medically necessary, requires ongoing research regarding potential benefits of increased monitoring for signs of epileptogenesis, PTS prophylaxis, and/or rehabilitation/social support. Future studies should externally validate models and determine clinical utility.

Background Cluster headache (CH), the most common trigeminal autonomic cephalalgia, is an extremely debilitating primary headache disorder that is often not optimally treated. New evidence‐based treatment guidelines for CH will assist clinicians with identifying and choosing among current treatment options. Objectives In this systematic review we appraise the available evidence for the acute and prophylactic treatment of CH, and provide an update of the 2010 American Academy of Neurology (AAN) endorsed systematic review. Methods Medline, PubMed, and EMBASE databases were searched for double‐blind, randomized controlled trials that investigated treatments of CH in adults. Exclusion and inclusion criteria were identical to those utilized in the 2010 AAN systematic review. Results and Recommendations For acute treatment, sumatriptan subcutaneous, zolmitriptan nasal spray, and high flow oxygen remain the treatments with a Level A recommendation. Since the 2010 review, a study of sphenopalatine ganglion stimulation was added to the current guideline and has been administered a Level B recommendation for acute treatment. For prophylactic therapy, previously there were no treatments that were administered a Level A recommendation. For the current guidelines, suboccipital steroid injections have emerged as the only treatment to receive a Level A recommendation with the addition of a second Class I study. Other newly evaluated treatments since the 2010 guidelines have been given a Level B recommendation (negative study: deep brain stimulation), a Level C recommendation (positive study: warfarin; negative studies: cimetidine/chlorpheniramine, candesartan), or a Level U recommendation (frovatriptan). Conclusions This AHS guideline can be utilized for understanding which therapies have superiority to placebo or sham treatment in the management of CH. In clinical practice, these recommendations should be considered in concert with other variables including safety, side effects, patient preferences, clinician experience, cost, and the invasiveness of the intervention. Given the lack of Class I evidence and Level A recommendations, particularly for a number of commonly used preventive therapies, further studies are warranted to demonstrate safety and efficacy for established and emerging therapies.

Abstract Waldenström macroglobulinemia (WM) is a distinct B-cell lymphoproliferative disorder for which clearly defined criteria for the diagnosis, initiation of therapy, and treatment strategy have been proposed as part of the consensus panels of the International Workshop on Waldenström’s Macroglobulinemia (IWWM). At IWWM-8, a task force for treatment recommendations was impanelled to review recently published and ongoing clinical trial data as well as the impact of new mutations (MYD88 and CXCR4) on treatment decisions, indications for B-cell receptor and proteasome inhibitors, and future clinical trial initiatives for WM patients. The panel concluded that therapeutic strategies in WM should be based on individual patient and disease characteristics. Chemoimmunotherapy combinations with rituximab and cyclophosphamide-dexamethasone, bendamustine, or bortezomib-dexamethasone provide durable responses and are still indicated in most patients. Approval of the BTK inhibitor ibrutinib in the United States and Europe represents a novel and effective treatment option for both treatment-naive and relapsing patients. Other B-cell receptor inhibitors, second-generation proteasome inhibitors (eg, carfilzomib), and mammalian target of rapamycin inhibitors are promising and may increase future treatment options. Active enrollment in clinical trials whenever possible was endorsed by the panel for most patients with WM.

Key Points A total of 38% of patients who achieved CR (13 of 34) on brentuximab vedotin have remained in remission for >5 years and may be cured. Nine of the 13 patients (9% of all enrolled patients) have remained in long-term remission without a consolidative allogeneic transplant.

Abstract Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P &lt; 10−8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type–specific expression quantitative trait locus and enhancer–gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P &lt; 10−5 in the three-cancer meta-analysis. Significance: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052–67. ©2016 AACR. This article is highlighted in the In This Issue feature, p. 932