Large-scale analysis of interindividual variability in single and paired-pulse TMS data

ObjectiveThis study brought together over 60 transcranial magnetic stimulation (TMS) researchers to create the largest known sample of individual participant single and paired-pulse TMS data to date, enabling a more comprehensive evaluation of factors driving response variability.MethodsAuthors of previously published studies were contacted and asked to share deidentified individual TMS data. Mixed-effects regression investigated a range of individual and study level variables for their contribution to variability in response to single and paired-pulse TMS data.Results687 healthy participant’s data were pooled across 35 studies. Target muscle, pulse waveform, neuronavigation use, and TMS machine significantly predicted an individual’s single-pulse TMS amplitude. Baseline motor evoked potential amplitude, motor cortex hemisphere, and motor threshold (MT) significantly predicted short-interval intracortical inhibition response. Baseline motor evoked potential amplitude, test stimulus intensity, interstimulus interval, and MT significantly predicted intracortical facilitation response. Age, hemisphere, and TMS machine significantly predicted MT.ConclusionsThis large-scale analysis has identified a number of factors influencing participants’ responses to single and paired-pulse TMS. We provide specific recommendations to minimise interindividual variability in single and paired-pulse TMS data.SignificanceThis study has used large-scale analyses to give clarity to factors driving variance in TMS data. We hope that this ongoing collaborative approach will increase standardisation of methods and thus the utility of single and paired-pulse TMS.     

Radiologically Placed Peritoneovenous Shunt is an Acceptable Treatment Alternative for Refractory Ascites Due to End-Stage Liver Disease

PurposeTo compare patients treated with large-volume paracentesis (LVP), transjugular intrahepatic portosystemic shunt (TIPS), and peritoneovenous shunt (PVS) for ascites.Materials and MethodsA retrospective study of 192 patients treated with LVP (94), TIPS (75), or PVS (23) was performed. Records were reviewed for patient characteristics and outcomes. The patients’ age differed (LVP, 59.5 years; TIPS, 58.8 years; and PVS, 65.6 years; P = .003). Nonalcoholic steatohepatitis was the most common etiology in the PVS cohort (11/23, 47%), and hepatitis C in the TIPS (27/75, 36%), and LVP cohorts (43/94, 46%) (P = .032). The model for end-stage liver disease score was significantly different (LVP, 14; TIPS, 13; and PVS, 8; P = .035). Hepatocellular carcinoma was higher in the PVS cohort (6/23 patients, 25%) than in the TIPS (4/75, 5%), and LVP (12/94, 12%) cohorts (P = .03).ResultsEmergency department visits and hospital readmissions were the highest in the LVP cohort (40%, ≥2 readmissions, P < .001). Patients required fewer LVPs after TIPS (1.5 to 0.14, P < .001) or PVS (2.1 to 0.5, P = .019). In an unadjusted Cox model, patients in the TIPS cohort were found to have a 58% reduction in the risk of death compared with patients in the LVP cohort (P = .003). Transplant-free survival (PVS, 44 days; TIPS, 155 days; and LVP, 213 days) differed (log rank = 0.001).ConclusionsThe survival in the PVS and TIPS cohorts was similar, with less healthcare utilization than the LVP cohort. PVS is a satisfactory alternative to LVP.     

Renal Effects of Crizotinib in Patients With ALK-Positive Advanced NSCLC

IntroductionWe retrospectively analyzed the effects of crizotinib on serum creatinine and creatinine-based estimated glomerular filtration rate (eGFR) in patients with anaplastic lymphoma kinase–positive advanced NSCLC across four trials (NCT00585195, NCT00932451, NCT00932893, and NCT01154140).MethodsChanges from baseline data in serum creatinine and eGFR, calculated using the Chronic Kidney Disease Epidemiology Collaboration creatinine-based equation, were assessed over time. eGFR was graded using standard chronic kidney disease criteria.ResultsMedian serum creatinine increased from 0.79 mg/dL at baseline to 0.93 mg/dL after 2 weeks of treatment (median percentage increase from baseline, 21.2%), was stable from week 12 (0.96 mg/dL) to week 104 (1.00 mg/dL), and decreased to 0.90 mg/dL at 28 days after last dose (median percentage increase from baseline, 13.1%). Median eGFR decreased over time (96.42, 80.23, 78.06 and 75.45 mL/min/1.73 m² at baseline, week 2, week 12, and week 104, respectively) and increased to 83.02 mL/min/1.73 m² at 28 days after the last dose. Median percentage decrease from baseline was 14.9%, 17.0%, and 10.4% at week 2, week 12, and 28 days after last dose of crizotinib, respectively. Overall, 12.6% of patients had a shift from eGFR grade less than or equal to 3a (≥45 mL/min/1.73 m²) at baseline to greater than or equal to 3b (<45 mL/min/1.73 m²) post-baseline.ConclusionsCrizotinib resulted in a decline in creatinine-based estimates of renal function mostly over the first 2 weeks of treatment. However, there was minimal evidence of cumulative effects with prolonged treatment and these changes were largely reversible following treatment discontinuation, consistent with previous reports suggesting this may be predominantly an effect on creatinine secretion as opposed to true nephrotoxicity.