Arguments for the biological and predictive relevance of the proportional recovery rule

The proportional recovery rule (PRR) posits that most stroke survivors can expect to reduce a fixed proportion of their motor impairment. As a statistical model, the PRR explicitly relates change scores to baseline values - an approach that arises in many scientific domains but has the potential to introduce artifacts and flawed conclusions. We describe approaches that can assess associations between baseline and changes from baseline while avoiding artifacts due either to mathematical coupling or to regression to the mean. We also describe methods that can compare different biological models of recovery. Across several real datasets in stroke recovery, we find evidence for non-artifactual associations between baseline and change, and support for the PRR compared to alternative models. We also introduce a statistical perspective that can be used to assess future models. We conclude that the PRR remains a biologically relevant model of stroke recovery

Association between convalescent plasma treatment and mortality in COVID-19: a collaborative systematic review and meta-analysis of randomized clinical trials.

Funder: laura and john arnold foundationBACKGROUND: Convalescent plasma has been widely used to treat COVID-19 and is under investigation in numerous randomized clinical trials, but results are publicly available only for a small number of trials. The objective of this study was to assess the benefits of convalescent plasma treatment compared to placebo or no treatment and all-cause mortality in patients with COVID-19, using data from all available randomized clinical trials, including unpublished and ongoing trials (Open Science Framework, https://doi.org/10.17605/OSF.IO/GEHFX ). METHODS: In this collaborative systematic review and meta-analysis, clinical trial registries (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform), the Cochrane COVID-19 register, the LOVE database, and PubMed were searched until April 8, 2021. Investigators of trials registered by March 1, 2021, without published results were contacted via email. Eligible were ongoing, discontinued and completed randomized clinical trials that compared convalescent plasma with placebo or no treatment in COVID-19 patients, regardless of setting or treatment schedule. Aggregated mortality data were extracted from publications or provided by investigators of unpublished trials and combined using the Hartung-Knapp-Sidik-Jonkman random effects model. We investigated the contribution of unpublished trials to the overall evidence. RESULTS: A total of 16,477 patients were included in 33 trials (20 unpublished with 3190 patients, 13 published with 13,287 patients). 32 trials enrolled only hospitalized patients (including 3 with only intensive care unit patients). Risk of bias was low for 29/33 trials. Of 8495 patients who received convalescent plasma, 1997 died (23%), and of 7982 control patients, 1952 died (24%). The combined risk ratio for all-cause mortality was 0.97 (95% confidence interval: 0.92; 1.02) with between-study heterogeneity not beyond chance (I2 = 0%). The RECOVERY trial had 69.8% and the unpublished evidence 25.3% of the weight in the meta-analysis. CONCLUSIONS: Convalescent plasma treatment of patients with COVID-19 did not reduce all-cause mortality. These results provide strong evidence that convalescent plasma treatment for patients with COVID-19 should not be used outside of randomized trials. Evidence synthesis from collaborations among trial investigators can inform both evidence generation and evidence application in patient care

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Effects of alirocumab on types of myocardial infarction: insights from the ODYSSEY OUTCOMES trial

Aims  The third Universal Definition of Myocardial Infarction (MI) Task Force classified MIs into five types: Type 1, spontaneous; Type 2, related to oxygen supply/demand imbalance; Type 3, fatal without ascertainment of cardiac biomarkers; Type 4, related to percutaneous coronary intervention; and Type 5, related to coronary artery bypass surgery. Low-density lipoprotein cholesterol (LDL-C) reduction with statins and proprotein convertase subtilisin–kexin Type 9 (PCSK9) inhibitors reduces risk of MI, but less is known about effects on types of MI. ODYSSEY OUTCOMES compared the PCSK9 inhibitor alirocumab with placebo in 18 924 patients with recent acute coronary syndrome (ACS) and elevated LDL-C (≥1.8 mmol/L) despite intensive statin therapy. In a pre-specified analysis, we assessed the effects of alirocumab on types of MI. Methods and results  Median follow-up was 2.8 years. Myocardial infarction types were prospectively adjudicated and classified. Of 1860 total MIs, 1223 (65.8%) were adjudicated as Type 1, 386 (20.8%) as Type 2, and 244 (13.1%) as Type 4. Few events were Type 3 (n = 2) or Type 5 (n = 5). Alirocumab reduced first MIs [hazard ratio (HR) 0.85, 95% confidence interval (CI) 0.77–0.95; P = 0.003], with reductions in both Type 1 (HR 0.87, 95% CI 0.77–0.99; P = 0.032) and Type 2 (0.77, 0.61–0.97; P = 0.025), but not Type 4 MI. Conclusion  After ACS, alirocumab added to intensive statin therapy favourably impacted on Type 1 and 2 MIs. The data indicate for the first time that a lipid-lowering therapy can attenuate the risk of Type 2 MI. Low-density lipoprotein cholesterol reduction below levels achievable with statins is an effective preventive strategy for both MI types.For complete list of authors see http://dx.doi.org/10.1093/eurheartj/ehz299</p

Effect of alirocumab on mortality after acute coronary syndromes. An analysis of the ODYSSEY OUTCOMES randomized clinical trial

Background: Previous trials of PCSK9 (proprotein convertase subtilisin-kexin type 9) inhibitors demonstrated reductions in major adverse cardiovascular events, but not death. We assessed the effects of alirocumab on death after index acute coronary syndrome. Methods: ODYSSEY OUTCOMES (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab) was a double-blind, randomized comparison of alirocumab or placebo in 18 924 patients who had an ACS 1 to 12 months previously and elevated atherogenic lipoproteins despite intensive statin therapy. Alirocumab dose was blindly titrated to target achieved low-density lipoprotein cholesterol (LDL-C) between 25 and 50 mg/dL. We examined the effects of treatment on all-cause death and its components, cardiovascular and noncardiovascular death, with log-rank testing. Joint semiparametric models tested associations between nonfatal cardiovascular events and cardiovascular or noncardiovascular death. Results: Median follow-up was 2.8 years. Death occurred in 334 (3.5%) and 392 (4.1%) patients, respectively, in the alirocumab and placebo groups (hazard ratio [HR], 0.85; 95% CI, 0.73 to 0.98; P=0.03, nominal P value). This resulted from nonsignificantly fewer cardiovascular (240 [2.5%] vs 271 [2.9%]; HR, 0.88; 95% CI, 0.74 to 1.05; P=0.15) and noncardiovascular (94 [1.0%] vs 121 [1.3%]; HR, 0.77; 95% CI, 0.59 to 1.01; P=0.06) deaths with alirocumab. In a prespecified analysis of 8242 patients eligible for ≥3 years follow-up, alirocumab reduced death (HR, 0.78; 95% CI, 0.65 to 0.94; P=0.01). Patients with nonfatal cardiovascular events were at increased risk for cardiovascular and noncardiovascular deaths (P<0.0001 for the associations). Alirocumab reduced total nonfatal cardiovascular events (P<0.001) and thereby may have attenuated the number of cardiovascular and noncardiovascular deaths. A post hoc analysis found that, compared to patients with lower LDL-C, patients with baseline LDL-C ≥100 mg/dL (2.59 mmol/L) had a greater absolute risk of death and a larger mortality benefit from alirocumab (HR, 0.71; 95% CI, 0.56 to 0.90; Pinteraction=0.007). In the alirocumab group, all-cause death declined wit h achieved LDL-C at 4 months of treatment, to a level of approximately 30 mg/dL (adjusted P=0.017 for linear trend). Conclusions: Alirocumab added to intensive statin therapy has the potential to reduce death after acute coronary syndrome, particularly if treatment is maintained for ≥3 years, if baseline LDL-C is ≥100 mg/dL, or if achieved LDL-C is low. Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01663402

Functional Data Analysis and Machine Learning for High-Dimensional Structured Data

This thesis pertains to the uses of Functional Data Analysis and Machine Learning when analyzing high-dimensional structured datasets. The theme that motivates the first two chapters is the development of dimension-reduction methods in the context of functional data to advance the understanding of in-vivo measurements of neural-spike data. The last chapter addresses the analysis of survey data using machine learning techniques to identify novel risk factors for suicide in the general population. The first chapter of this thesis, "Adaptive Functional Principal Component Analysis," provides a novel method for adequately capturing modes of variation in data exhibiting sharp changes in smoothness. Our work integrates a novel scatterplot technique that adaptively smooths latent functions estimated in an FPCA framework. We are motivated to identify coordinated patterns of brain activity across multiple simultaneously-recorded neurons during motor behavior to understand the dynamics between the brain and dexterous movement. Our proposed method adequately captures the underlying biological mechanisms in our experiment, offering interpretable activation patterns when compared to standard approaches. The second chapter of our dissertation develops statistical procedures to compare the eigendecomposition from two samples of functional data. We first introduce appropriate tests for both independent and paired functions. We are motivated to test whether activation patterns in the motor cortex hold constant when a mouse performs a reaching movement repeatedly. We test all pairwise comparisons across trials and compare the distribution of the p-values against the distribution under the null. Our results suggest trial-to-trial variation in the latent activation patterns that can't be attributed to sampling noise. Our results can inform future methodology for deriving activation patterns from noisy neural spikes. The last chapter of this dissertation dives into applying Machine Learning Techniques to analyze survey data. We use the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) survey to identify novel risk factors for suicide attempts in the general population. Our analysis uses a Balanced Random Forest (BRF) approach and incorporates extreme class imbalance and survey architecture into the algorithm. We extend prior research focusing on high-risk clinical samples by identifying risk factors for suicide attempts in the general population. Our work identifies risk variables that can help guide clinical assessment and the development of suicide risk scales

Arguments for the biological and predictive relevance of the proportional recovery rule

The proportional recovery rule (PRR) posits that most stroke survivors can expect to reduce a fixed proportion of their motor impairment. As a statistical model, the PRR explic-itly relates change scores to baseline values – an approach that arises in many scientific domains but has the potential to introduce artifacts and flawed conclusions. We describe approaches that can assess associations between baseline and changes from baseline while avoiding artifacts due either to mathematical coupling or to regression to the mean. We also describe methods that can compare different biological models of recovery. Across several real datasets in stroke recovery, we find evidence for non-artifactual associations between baseline and change, and support for the PRR compared to alternative models. We also introduce a statistical perspective that can be used to assess future models. We conclude that the PRR remains a biologically relevant model of stroke recovery

Changes in typical beliefs in response to complicated grief treatment

BackgroundProlonged grief disorder (PGD) is a new diagnosis in the 11th edition of the International Classification of Diseases, estimated to affect 1 in 10 bereaved people and causing significant distress and impairment. Maladaptive thoughts play an important role in PGD. We have previously validated the typical beliefs questionnaire (TBQ), which contains five kinds of thinking commonly seen in PGD: protesting the death, negative thoughts about the world, needing the person, less grief is wrong, and grieving too much. The current paper examines the role of maladaptive cognition as measured by the TBQ in PGD and its change with treatment.MethodsAmong participants in a multisite clinical trial including 394 adults, we examined (a) the relationship between maladaptive thoughts at baseline and treatment outcomes, (b) the relationship between maladaptive thoughts and suicidality at baseline and posttreatment, and (c) the effect of treatment with and without complicated grief therapy (CGT) on maladaptive thinking.ResultsTBQ scores were associated with treatment outcomes and were strongly related to suicidal thinking before and after treatment. TBQ scores showed significantly greater reduction in participants who received CGT with citalopram versus citalopram alone (adjusted mean standard error [SE] difference, -2.45 [0.85]; p = .004) and those who received CGT with placebo versus placebo alone (adjusted mean [SE] difference, -3.44 [0.90]; p &lt; .001).ConclusionsMaladaptive thoughts, as measured by the TBQ, have clinical and research significance for PGD and its treatment

Impact of sleep on complicated grief severity and outcomes

BackgroundComplicated grief (CG) is characterized by persistent, impairing grief after losing a loved one. Little is known about sleep disturbance in CG. Baseline prevalence of subjective sleep disturbance, impact of treatment on sleep, and impact of mid-treatment sleep on CG and quality of life outcomes were examined in adults with CG in secondary analyses of a clinical trial.MethodsPatients with CG (n = 395, mean age =53.0; 78% female) were randomized to CGT+placebo, CGT+citalopram (CIT), CIT, or placebo. Subjective sleep disturbance was assessed by a grief-anchored sleep item (Pittsburgh Sleep Quality Index: PSQI-1) and a four-item sleep subscale of the Quick Inventory of Depressive Symptomatology (QIDS-4). Sleep disturbance was quantified as at least one QIDS-4 item with severity ≥2 or grief-related sleep disturbance ≥3 days a week for PSQI-1. Outcomes included the Inventory of Complicated Grief (ICG), Work and Social Adjustment Scale (WSAS), and Clinical Global Impressions Scale.ResultsBaseline sleep disturbance prevalence was 91% on the QIDS-4 and 46% for the grief-anchored PSQI-1. Baseline CG severity was significantly associated with sleep disturbance (QIDS-4: p = .015; PSQI-1: p = .001) after controlling for comorbid depression and PTSD. Sleep improved with treatment; those receiving CGT+CIT versus CIT evidenced better endpoint sleep (p = .027). Mid-treatment QIDS-4 significantly predicted improvement on outcome measures (all p &lt; .01), though only WSAS remained significant after adjustment for mid-treatment ICG (p = .02).ConclusionsGreater CG severity is associated with poorer sleep beyond PTSD and depression comorbidity. Additional research including objective sleep measurement is needed to optimally elucidate and address sleep impairment associated with CG

Frequency of BRAF V600E Mutation in the Mexican Population of Patients With Metastatic Melanoma

Purpose: The BRAF V600E mutation has been described in melanomas occurring in the Caucasian, European, and Asian populations. However, in the Mexican population, the status and clinical significance of BRAF mutation has not been researched on a large scale. Methods: Consecutive BRAF-tested Mexican patients with metastatic melanoma (n = 127) were analyzed for mutations in exon 15 of the BRAF gene in genomic DNA by real-time polymerase chain reaction technology for amplification and detection. The results were correlated with the clinical-pathologic features and the prognosis of the patients. Results: The frequency of somatic mutation V600E within the BRAF gene was 54.6% (43 of 127 patients). Nodular melanoma was the most prevalent subtype in our population, with BRAF mutations in 37.2% (16 of 55 patients). In contrast, superficial spread had a frequency of 18.6% BRAF mutation (eight of 24). Other clinicopathologic features were assessed to correlate with the mutation status. Conclusion: This study searched for the most prevalent BRAF V600E mutation type in melanoma in a heterogeneous population from Mexico. Nodular melanoma was found to be the most prevalent in metastatic presentation and the presence of BRAF V600E mutation, perhaps related to the mixed ancestry; in the north, ancestry is predominantly European and in the south, it is predominantly Asian. The outcomes of the mutation correlations were similar to those found in other populations