Quantifying how single dose Ad26.COV2.S vaccine efficacy depends on Spike sequence features

In the ENSEMBLE randomized, placebo-controlled phase 3 trial (NCT04505722), estimated single-dose Ad26.COV2.S vaccine efficacy (VE) was 56% against moderate to severe-critical COVID-19. SARS-CoV-2 Spike sequences were determined from 484 vaccine and 1,067 placebo recipients who acquired COVID-19. In this set of prespecified analyses, we show that in Latin America, VE was significantly lower against Lambda vs. Reference and against Lambda vs. non-Lambda [family-wise error rate (FWER) p < 0.05]. VE differed by residue match vs. mismatch to the vaccine-insert at 16 amino acid positions (4 FWER p < 0.05; 12 q-value ≤ 0.20); significantly decreased with physicochemical-weighted Hamming distance to the vaccine-strain sequence for Spike, receptor-binding domain, N-terminal domain, and S1 (FWER p < 0.001); differed (FWER ≤ 0.05) by distance to the vaccine strain measured by 9 antibody-epitope escape scores and 4 NTD neutralization-impacting features; and decreased (p = 0.011) with neutralization resistance level to vaccinee sera. VE against severe-critical COVID-19 was stable across most sequence features but lower against the most distant viruses.

Data-driven automated classification algorithms for acute health conditions: applying PheNorm to COVID-19 disease

OBJECTIVES

Automated phenotyping algorithms can reduce development time and operator dependence compared to manually developed algorithms. One such approach, PheNorm, has performed well for identifying chronic health conditions, but its performance for acute conditions is largely unknown. Herein, we implement and evaluate PheNorm applied to symptomatic COVID-19 disease to investigate its potential feasibility for rapid phenotyping of acute health conditions.

MATERIALS AND METHODS

PheNorm is a general-purpose automated approach to creating computable phenotype algorithms based on natural language processing, machine learning, and (low cost) silver-standard training labels. We applied PheNorm to cohorts of potential COVID-19 patients from 2 institutions and used gold-standard manual chart review data to investigate the impact on performance of alternative feature engineering options and implementing externally trained models without local retraining.

RESULTS

Models at each institution achieved AUC, sensitivity, and positive predictive value of 0.853, 0.879, 0.851 and 0.804, 0.976, and 0.885, respectively, at quantiles of model-predicted risk that maximize F1. We report performance metrics for all combinations of silver labels, feature engineering options, and models trained internally versus externally.

DISCUSSION

Phenotyping algorithms developed using PheNorm performed well at both institutions. Performance varied with different silver-standard labels and feature engineering options. Models developed locally at one site also worked well when implemented externally at the other site.

CONCLUSION

PheNorm models successfully identified an acute health condition, symptomatic COVID-19. The simplicity of the PheNorm approach allows it to be applied at multiple study sites with substantially reduced overhead compared to traditional approaches.

Prevention efficacy of the broadly neutralizing antibody VRC01 depends on HIV-1 envelope sequence features

In the Antibody Mediated Prevention (AMP) trials (HVTN 704/HPTN 085 and HVTN 703/HPTN 081), prevention efficacy (PE) of the monoclonal broadly neutralizing antibody (bnAb) VRC01 (vs. placebo) against HIV-1 acquisition diagnosis varied according to the HIV-1 Envelope (Env) neutralization sensitivity to VRC01, as measured by 80% inhibitory concentration (IC80). Here, we performed a genotypic sieve analysis, a complementary approach to gaining insight into correlates of protection that assesses how PE varies with HIV-1 sequence features. We analyzed HIV-1 Env amino acid (AA) sequences from the earliest available HIV-1 RNA-positive plasma samples from AMP participants diagnosed with HIV-1 and identified Env sequence features that associated with PE. The strongest Env AA sequence correlate in both trials was VRC01 epitope distance that quantifies the divergence of the VRC01 epitope in an acquired HIV-1 isolate from the VRC01 epitope of reference HIV-1 strains that were most sensitive to VRC01-mediated neutralization. In HVTN 704/HPTN 085, the Env sequence-based predicted probability that VRC01 IC80 against the acquired isolate exceeded 1 µg/mL also significantly associated with PE. In HVTN 703/HPTN 081, a physicochemical-weighted Hamming distance across 50 VRC01 binding-associated Env AA positions of the acquired isolate from the most VRC01-sensitive HIV-1 strain significantly associated with PE. These results suggest that incorporating mutation scoring by BLOSUM62 and weighting by the strength of interactions at AA positions in the epitope:VRC01 interface can optimize performance of an Env sequence-based biomarker of VRC01 prevention efficacy. Future work could determine whether these results extend to other bnAbs and bnAb combinations.

Engaging staff to improve COVID-19 vaccination response at long-term care facilities (ENSPIRE): A cluster randomized trial of co-designed, tailored vaccine promotion materials

BACKGROUND

COVID-19 vaccination rates among long-term care center (LTCC) workers are among the lowest of all frontline health care workers. Current efforts to increase COVID-19 vaccine uptake generally focus on strategies that have proven effective for increasing influenza vaccine uptake among health care workers including educational and communication strategies. Experimental evidence is lacking on the comparative advantage of educational strategies to improve vaccine acceptance and uptake, especially in the context of COVID-19. Despite the lack of evidence, education and communication strategies are recommended to improve COVID-19 vaccination rates and decrease vaccine hesitancy (VH), especially strategies using tailored messaging for disproportionately affected populations.

METHODS

We describe a cluster-randomized comparative effectiveness trial with 40 LTCCs and approximately 4000 LTCC workers in 2 geographically, culturally, and ethnically distinct states. We compare the effectiveness of two strategies for increasing COVID-19 booster vaccination rates and willingness to promote COVID-19 booster vaccination: co-design processes for tailoring educational messages vs. an enhanced usual care comparator. Our study focuses on the language and/or cultural groups that are most disproportionately affected by VH and low COVID-19 vaccine uptake in these LTCCs.

CONCLUSION

Finding effective methods to increase COVID-19 vaccine uptake and decrease VH among LTCC staff is critical. Beyond COVID-19, better approaches are needed to improve vaccine uptake and decrease VH for a variety of existing vaccines as well as vaccines created to address novel viruses as they emerge.

Predicting neutralization susceptibility to combination HIV-1 monoclonal broadly neutralizing antibody regimens

Combination monoclonal broadly neutralizing antibodies (bnAbs) are currently being developed for preventing HIV-1 infection. Recent work has focused on predicting in vitro neutralization potency of both individual bnAbs and combination regimens against HIV-1 pseudoviruses using Env sequence features. To predict in vitro combination regimen neutralization potency against a given HIV-1 pseudovirus, previous approaches have applied mathematical models to combine individual-bnAb neutralization and have predicted this combined neutralization value; we call this the combine-then-predict (CP) approach. However, prediction performance for some individual bnAbs has exceeded that for the combination, leading to another possibility: combining the individual-bnAb predicted values and using these to predict combination regimen neutralization; we call this the predict-then-combine (PC) approach. We explore both approaches in both simulated data and data from the Los Alamos National Laboratory's Compile, Neutralize, and Tally NAb Panels repository. The CP approach is superior to the PC approach when the neutralization outcome of interest is binary (e.g., neutralization susceptibility, defined as inhibitory concentration < 1 μg/mL. For continuous outcomes, the CP approach performs at least as well as the PC approach, and is superior to the PC approach when the individual-bnAb prediction algorithms have poor performance. This knowledge may be used when building prediction models for novel antibody combinations in the absence of in vitro neutralization data for the antibody combination; this, in turn, will aid in the evaluation and down-selection of these antibody combinations into prevention efficacy trials.

Considerations for Subgroup Analyses in Cluster-Randomized Trials Based on Aggregated Individual-Level Predictors

In research assessing the effect of an intervention or exposure, a key secondary objective often involves assessing differential effects of this intervention or exposure in subgroups of interest; this is often referred to as assessing effect modification or heterogeneity of treatment effects (HTE). Observed HTE can have important implications for policy, including intervention strategies (e.g., will some patients benefit more from intervention than others?) and prioritizing resources (e.g., to reduce observed health disparities). Analysis of HTE is well understood in studies where the independent unit is an individual. In contrast, in studies where the independent unit is a cluster (e.g., a hospital or school) and a cluster-level outcome is used in the analysis, it is less well understood how to proceed if the HTE analysis of interest involves an individual-level characteristic (e.g., self-reported race) that must be aggregated at the cluster level. Through simulations, we show that only individual-level models have power to detect HTE by individual-level variables; if outcomes must be defined at the cluster level, then there is often low power to detect HTE by the corresponding aggregated variables. We illustrate the challenges inherent to this type of analysis in a study assessing the effect of an intervention on increasing COVID-19 booster vaccination rates at long-term care centers.

A causal roadmap for generating high-quality real-world evidence

Increasing emphasis on the use of real-world evidence (RWE) to support clinical policy and regulatory decision-making has led to a proliferation of guidance, advice, and frameworks from regulatory agencies, academia, professional societies, and industry. A broad spectrum of studies use real-world data (RWD) to produce RWE, ranging from randomized trials with outcomes assessed using RWD to fully observational studies. Yet, many proposals for generating RWE lack sufficient detail, and many analyses of RWD suffer from implausible assumptions, other methodological flaws, or inappropriate interpretations. The Causal Roadmap is an explicit, itemized, iterative process that guides investigators to prespecify study design and analysis plans; it addresses a wide range of guidance within a single framework. By supporting the transparent evaluation of causal assumptions and facilitating objective comparisons of design and analysis choices based on prespecified criteria, the Roadmap can help investigators to evaluate the quality of evidence that a given study is likely to produce, specify a study to generate high-quality RWE, and communicate effectively with regulatory agencies and other stakeholders. This paper aims to disseminate and extend the Causal Roadmap framework for use by clinical and translational researchers; three companion papers demonstrate applications of the Causal Roadmap for specific use cases.

An application of the Causal Roadmap in two safety monitoring case studies: Causal inference and outcome prediction using electronic health record data

Background

Real-world data, such as administrative claims and electronic health records, are increasingly used for safety monitoring and to help guide regulatory decision-making. In these settings, it is important to document analytic decisions transparently and objectively to assess and ensure that analyses meet their intended goals.

Methods

The Causal Roadmap is an established framework that can guide and document analytic decisions through each step of the analytic pipeline, which will help investigators generate high-quality real-world evidence.

Results

In this paper, we illustrate the utility of the Causal Roadmap using two case studies previously led by workgroups sponsored by the Sentinel Initiative - a program for actively monitoring the safety of regulated medical products. Each case example focuses on different aspects of the analytic pipeline for drug safety monitoring. The first case study shows how the Causal Roadmap encourages transparency, reproducibility, and objective decision-making for causal analyses. The second case study highlights how this framework can guide analytic decisions beyond inference on causal parameters, improving outcome ascertainment in clinical phenotyping.

Conclusion

These examples provide a structured framework for implementing the Causal Roadmap in safety surveillance and guide transparent, reproducible, and objective analysis.

Application of the SLAPNAP statistical learning tool to broadly neutralizing antibody HIV prevention research

Combination monoclonal broadly neutralizing antibody (bnAb) regimens are in clinical development for HIV prevention, necessitating additional knowledge of bnAb neutralization potency/breadth against circulating viruses. Williamson et al. (2021) described a software tool, Super LeArner Prediction of NAb Panels (SLAPNAP), with application to any HIV bnAb regimen with sufficient neutralization data against a set of viruses in the Los Alamos National Laboratory's Compile, Neutralize, and Tally Nab Panels repository. SLAPNAP produces a proteomic antibody resistance (PAR) score for Env sequences based on predicted neutralization resistance and estimates variable importance of Env amino acid features. We apply SLAPNAP to compare HIV bnAb regimens undergoing clinical testing, finding improved power for downstream sieve analyses and increased precision for comparing neutralization potency/breadth of bnAb regimens due to the inclusion of PAR scores of Env sequences with much larger sample sizes available than for neutralization outcomes. SLAPNAP substantially improves bnAb regimen characterization, ranking, and down-selection.

A health-system-embedded deprescribing intervention targeting patients and providers to prevent falls in older adults (STOP-FALLS trial): study protocol for a pragmatic cluster-randomized controlled trial

BACKGROUND

Central nervous system (CNS) active medications have been consistently linked to falls in older people. However, few randomized trials have evaluated whether CNS-active medication reduction reduces falls and fall-related injuries. The objective of the Reducing CNS-active Medications to Prevent Falls and Injuries in Older Adults (STOP-FALLS) trial is to test the effectiveness of a health-system-embedded deprescribing intervention focused on CNS-active medications on the incidence of medically treated falls among community-dwelling older adults.

METHODS

We will conduct a pragmatic, cluster-randomized, parallel-group, controlled clinical trial within Kaiser Permanente Washington to test the effectiveness of a 12-month deprescribing intervention consisting of (1) an educational brochure and self-care handouts mailed to older adults prescribed one or more CNS-active medications (aged 60 + : opioids, benzodiazepines and Z-drugs; aged 65 + : skeletal muscle relaxants, tricyclic antidepressants, and antihistamines) and (2) decision support for their primary health care providers. Outcomes are examined over 18-26 months post-intervention. The primary outcome is first incident (post-baseline) medically treated fall as determined from health plan data. Our sample size calculations ensure at least 80% power to detect a 20% reduction in the rate of medically treated falls for participants receiving care within the intervention (n = 9) versus usual care clinics (n = 9) assuming 18 months of follow-up. Secondary outcomes include medication discontinuation or dose reduction of any target medications. Safety outcomes include serious adverse drug withdrawal events, unintentional overdose, and death. We will also examine medication signetur fields for attempts to decrease medications. We will report factors affecting implementation of the intervention.

DISCUSSION

The STOP-FALLS trial will provide new information about whether a health-system-embedded deprescribing intervention that targets older participants and their primary care providers reduces medically treated falls and CNS-active medication use. Insights into factors affecting implementation will inform future research and healthcare organizations that may be interested in replicating the intervention.

TRIAL REGISTRATION

ClinicalTrial.gov NCT05689554. Registered on 18 January 2023, retrospectively registered.

Comparing antibody assays as correlates of protection against COVID-19 in the COVE mRNA-1273 vaccine efficacy trial

The best assay or marker to define mRNA-1273 vaccine-induced antibodies as a correlate of protection (CoP) is unclear. In the COVE trial, participants received two doses of the mRNA-1273 COVID-19 vaccine or placebo. We previously assessed IgG binding antibodies to the spike protein (spike IgG) or receptor binding domain (RBD IgG) and pseudovirus neutralizing antibody 50 or 80% inhibitory dilution titer measured on day 29 or day 57, as correlates of risk (CoRs) and CoPs against symptomatic COVID-19 over 4 months after dose. Here, we assessed a new marker, live virus 50% microneutralization titer (LV-MN50), and compared and combined markers in multivariable analyses. LV-MN50 was an inverse CoR, with a hazard ratio of 0.39 (95% confidence interval, 0.19 to 0.83) at day 29 and 0.51 (95% confidence interval, 0.25 to 1.04) at day 57 per 10-fold increase. In multivariable analyses, pseudovirus neutralization titers and anti-spike binding antibodies performed best as CoRs; combining antibody markers did not improve correlates. Pseudovirus neutralization titer was the strongest independent correlate in a multivariable model. Overall, these results supported pseudovirus neutralizing and binding antibody assays as CoRs and CoPs, with the live virus assay as a weaker correlate in this sample set. Day 29 markers performed as well as day 57 markers as CoPs, which could accelerate immunogenicity and immunobridging studies.

Baseline host determinants of robust human HIV-1 vaccine-induced immune responses: A meta-analysis of 26 vaccine regimens

BACKGROUND

The identification of baseline host determinants that associate with robust HIV-1 vaccine-induced immune responses could aid HIV-1 vaccine development. We aimed to assess both the collective and relative performance of baseline characteristics in classifying individual participants in nine different Phase 1-2 HIV-1 vaccine clinical trials (26 vaccine regimens, conducted in Africa and in the Americas) as High HIV-1 vaccine responders.

METHODS

This was a meta-analysis of individual participant data, with studies chosen based on participant-level (vs. study-level summary) data availability within the HIV-1 Vaccine Trials Network. We assessed the performance of 25 baseline characteristics (demographics, safety haematological measurements, vital signs, assay background measurements) and estimated the relative importance of each characteristic in classifying 831 participants as High (defined as within the top 25th percentile among positive responders or above the assay upper limit of quantification) versus Non-High responders. Immune response outcomes included HIV-1-specific serum IgG binding antibodies and Env-specific CD4+ T-cell responses assessed two weeks post-last dose, all measured at central HVTN laboratories. Three variable importance approaches based on SuperLearner ensemble machine learning were considered.

FINDINGS

Overall, 30.1%, 50.5%, 36.2%, and 13.9% of participants were categorized as High responders for gp120 IgG, gp140 IgG, gp41 IgG, and Env-specific CD4+ T-cell vaccine-induced responses, respectively. When including all baseline characteristics, moderate performance was achieved for the classification of High responder status for the binding antibody responses, with cross-validated areas under the ROC curve (CV-AUC) of 0.72 (95% CI: 0.68, 0.76) for gp120 IgG, 0.73 (0.69, 0.76) for gp140 IgG, and 0.67 (95% CI: 0.63, 0.72) for gp41 IgG. In contrast, the collection of all baseline characteristics yielded little improvement over chance for predicting High Env-specific CD4+ T-cell responses [CV-AUC: 0.53 (0.48, 0.58)]. While estimated variable importance patterns differed across the three approaches, female sex assigned at birth, lower height, and higher total white blood cell count emerged as significant predictors of High responder status across multiple immune response outcomes using Approach 1. Of these three baseline variables, total white blood cell count ranked highly across all three approaches for predicting vaccine-induced gp41 and gp140 High responder status.

INTERPRETATION

The identified features should be studied further in pursuit of intervention strategies to improve vaccine responses and may be adjusted for in analyses of immune response data to enhance statistical power.

FUNDING

National Institute of Allergy and Infectious Diseases (UM1AI068635 to YH, UM1AI068614 to GDT, UM1AI068618 to MJM, and UM1 AI069511 to MCK), the Duke CFAR P30 AI064518 to GDT, and National Institute of Dental and Craniofacial Research (R01DE027245 to JJK). This work was also supported by the Bill and Melinda Gates Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of any of the funding sources.

A multiview model for relative and absolute microbial abundances

The absolute abundance of bacterial taxa in human host-associated environments plays a critical role in reproductive and gastrointestinal health. However, obtaining the absolute abundance of many bacterial species is typically prohibitively expensive. In contrast, relative abundance data for many species are comparatively cheap and easy to collect (e.g., with universal primers for the 16S rRNA gene). In this paper, we propose a method to jointly model relative abundance data for many taxa and absolute abundance data for a subset of taxa. Our method provides point and interval estimates for the absolute abundance of all taxa. Crucially, our proposal accounts for differences in the efficiency of taxon detection in the relative and absolute abundance data. We show that modeling taxon-specific efficiencies substantially reduces the estimation error for absolute abundance, and controls the coverage of interval estimators. We demonstrate the performance of our proposed method via a simulation study, a study of the effect of HIV acquisition on microbial abundances, and a sensitivity study where we jackknife the taxa with observed absolute abundances.

Diaphragmatic Pacing as an Initial Presentation of Delayed Ventricular Lead Perforation

Ventricular lead perforation is an infrequent and potentially fatal complication of pacemakers and implantable cardioverter-defibrillators that typically presents shortly following device implantation. Delayed lead perforations occurring 1 month after implantation are not widely reported and can have a wide range of presentations ranging from asymptomatic to potentially fatal cardiac tamponade. We describe a case of successful percutaneous lead extraction and revision in a patient who presented 9 months following implantation with an active fixation right ventricular pacing lead with apical perforation. Perforation was suspected when device interrogation showed ventricular sensing without ventricular capture, but with diaphragm stimulation. After an initial X-ray and transthoracic echocardiogram failed to detect it, computed tomography angiography confirmed the myocardial perforation. This case demonstrates the importance of recognizing such a complication following cardiac implantable electronic device implantation regardless of the timeline of presentation. It also serves to highlight the importance of clinical suspicion and awareness of the limitations of imaging for perforation. Transvenous percutaneous lead extraction and revision remains a favored approach due to reduced patient trauma when compared to the open surgical approach.

Conduction system pacing in prosthetic heart valves

BACKGROUND

There has been increasing interest in physiologic pacing techniques that directly activate the specialized conduction system. We aimed to assess outcomes of conduction system pacing (CSP) in patients with prosthetic heart valves.

METHODS

This systematic review was performed according to PRISMA guidelines. Freeman-Tukey double arcsine transformation with the random-effect model was used to summarize the data. Outcomes studied were 1) implant success (defined as ability to recruit the His-Purkinje system or the distal Purkinje system); (2) lead parameters at implant and follow-up; and (3) procedure-related complications.

RESULTS

This systematic review of 7 studies included 267 unique patients in whom CSP was attempted with either HBP or LBBAP for pacing indications after a prosthetic valve. HBP was attempted in 38% (n = 108), while LBBAP in 62% (n = 175) patients. The overall success rate of CSP was 87%, while in patients post-TAVR, the overall success rate was 83.2%. In the subgroup analysis, LBBAP had a significant higher overall success rate compared to HBP (94.3% vs. 76.5%, p _interaction = 0.02) and post-TAVR patients (94.3 vs. 66.9%, p _interaction < 0.01), respectively. The LBBAP thresholds were significantly lower compared to HBP both at implant (0.67 ± 0.4 @ 0.44 ms vs. 1.35 ± 1 @ 0.85 ms, p _interaction < 0.01) and at a mean follow-up of 12.4 ± 8 months (0.73 ± 0.1 @ 0.44 ms vs. 1.39 ± 1 @ 0.85 ms, p _interaction < 0.01), respectively.

CONCLUSION

CSP is safe and feasible in patients with a prosthetic valve, with a significantly higher success rate and superior lead parameters with LBBAP than HBP, especially in patients post-TAVR.

Combining information to estimate adherence in studies of pre-exposure prophylaxis for HIV prevention: Application to HPTN 067

In trials of oral HIV pre-exposure prophylaxis (PrEP), multiple approaches have been used to measure adherence, including self-report, pill counts, electronic dose monitoring devices, and biological measures such as drug levels in plasma, peripheral blood mononuclear cells, hair, and/or dried blood spots. No one of these measures is ideal and each has strengths and weaknesses. However, accurate estimates of adherence to oral PrEP are important as drug efficacy is closely tied to adherence, and secondary analyses of trial data within identified adherent/non-adherent subgroups may yield important insights into real-world drug effectiveness. We develop a statistical approach to combining multiple measures of adherence and show in simulated data that the proposed method provides a more accurate measure of true adherence than self-report. We then apply the method to estimate adherence in the ADAPT study (HPTN 067) in South African women.

A general framework for inference on algorithm-agnostic variable importance

In many applications, it is of interest to assess the relative contribution of features (or subsets of features) toward the goal of predicting a response - in other words, to gauge the variable importance of features. Most recent work on variable importance assessment has focused on describing the importance of features within the confines of a given prediction algorithm. However, such assessment does not necessarily characterize the prediction potential of features, and may provide a misleading reflection of the intrinsic value of these features. To address this limitation, we propose a general framework for nonparametric inference on interpretable algorithm-agnostic variable importance. We define variable importance as a population-level contrast between the oracle predictiveness of all available features versus all features except those under consideration. We propose a nonparametric efficient estimation procedure that allows the construction of valid confidence intervals, even when machine learning techniques are used. We also outline a valid strategy for testing the null importance hypothesis. Through simulations, we show that our proposal has good operating characteristics, and we illustrate its use with data from a study of an antibody against HIV-1 infection.

Improving random forest predictions in small datasets from two-phase sampling designs

BACKGROUND

While random forests are one of the most successful machine learning methods, it is necessary to optimize their performance for use with datasets resulting from a two-phase sampling design with a small number of cases-a common situation in biomedical studies, which often have rare outcomes and covariates whose measurement is resource-intensive.

METHODS

Using an immunologic marker dataset from a phase III HIV vaccine efficacy trial, we seek to optimize random forest prediction performance using combinations of variable screening, class balancing, weighting, and hyperparameter tuning.

RESULTS

Our experiments show that while class balancing helps improve random forest prediction performance when variable screening is not applied, class balancing has a negative impact on performance in the presence of variable screening. The impact of the weighting similarly depends on whether variable screening is applied. Hyperparameter tuning is ineffective in situations with small sample sizes. We further show that random forests under-perform generalized linear models for some subsets of markers, and prediction performance on this dataset can be improved by stacking random forests and generalized linear models trained on different subsets of predictors, and that the extent of improvement depends critically on the dissimilarities between candidate learner predictions.

CONCLUSION

In small datasets from two-phase sampling design, variable screening and inverse sampling probability weighting are important for achieving good prediction performance of random forests. In addition, stacking random forests and simple linear models can offer improvements over random forests.

CMV viral load kinetics as surrogate endpoints after allogeneic transplantation

BACKGROUNDViral load (VL) surrogate endpoints transformed development of HIV and hepatitis C therapeutics. Surrogate endpoints for CMV-related morbidity and mortality could advance development of antiviral treatments. Although observational data support using CMV VL as a trial endpoint, randomized controlled trials (RCTs) demonstrating direct associations between virological markers and clinical endpoints are lacking.METHODSWe performed CMV DNA PCR on frozen serum samples from the only placebo-controlled RCT of ganciclovir for early treatment of CMV after hematopoietic cell transplantation (HCT). We used established criteria to assess VL kinetics as surrogates for CMV disease or death by weeks 8, 24, and 48 after randomization and quantified antiviral effects captured by each marker. We used ensemble-based machine learning to assess the predictive ability of VL kinetics and performed this analysis on a ganciclovir prophylaxis RCT for validation.RESULTSVL suppression with ganciclovir reduced cumulative incidence of CMV disease and death for 20 years after HCT. Mean VL, peak VL, and change in VL during the first 5 weeks of treatment fulfilled the Prentice definition for surrogacy, capturing more than 95% of ganciclovir's effect, and yielded highly sensitive and specific predictions by week 48. In the prophylaxis trial, the viral shedding rate satisfied the Prentice definition for CMV disease by week 24.CONCLUSIONSOur results support using CMV VL kinetics as surrogates for CMV disease, provide a framework for developing CMV preventative and therapeutic agents, and support reductions in VL as the mechanism through which antivirals reduce CMV disease.FUNDINGMerck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc.

Analysis of Neutralizing Antibodies as a Correlate of Instantaneous Risk of Hospitalized Dengue in Placebo Recipients of Dengue Vaccine Efficacy Trials

BACKGROUND

In the CYD14 (NCT01373281) and CYD15 (NCT01374516) dengue vaccine efficacy trials, Month 13 neutralizing antibody (nAb) titers correlated inversely with risk of symptomatic, virologically confirmed dengue (VCD) between Month 13 (one month post-final-dose) and Month 25. We assessed nAb titer as a correlate of instantaneous risk of hospitalized VCD (HVCD), for which participants were continually surveilled for 72 months.

METHODS

Using longitudinal nAb titers from the per-protocol immunogenicity subsets, we estimated hazard ratios (HRs) of HVCD by current nAb titer value for three correlate/endpoint pairs: average titer across all four serotypes/HVCD of any serotype (HVCD-Any), serotype-specific titer/homologous HVCD, and serotype-specific titer/heterologous HVCD.

RESULTS

Baseline-seropositive placebo recipients with higher average titer had lower instantaneous risk of HVCD-Any in 2-16-year-olds and in 9-16-year-olds (HR 0.26 or 0.15 per 10-fold increase in average titer by two methods, 95% CIs 0.14 to 0.45 and 0.07 to 0.34, respectively) pooled across both trials. Results were similar for homologous HVCD. There was evidence suggesting increased HVCD-Any risk in participants with low average titer (1:10 to 1:100) compared to seronegative participants (HR 1.85, 95% CI 0.93 to 3.68).

CONCLUSIONS

Natural infection-induced nAbs were inversely associated with hospitalized dengue, upon exceeding a relatively low threshold.

Super LeArner Prediction of NAb Panels (SLAPNAP): A Contain-erized Tool for Predicting Combination Monoclonal Broadly Neu-tralizing Antibody Sensitivity

MOTIVATION

A single monoclonal broadly neutralizing antibody (bnAb) regimen was recently evaluated in two randomized trials for prevention efficacy against HIV-1 infection. Subsequent trials will evaluate combination bnAb regimens (e.g., cocktails, multi-specific antibodies), which demonstrate higher potency and breadth in vitro compared to single bnAbs. Given the large number of potential regimens, methods for down-selecting these regimens into efficacy trials are of great interest.

RESULTS

We developed Super LeArner Prediction of NAb Panels (SLAPNAP), a software tool for training and evaluating machine learning models that predict in vitro neutralization sensitivity of HIV Envelope (Env) pseudoviruses to a given single or combination bnAb regimen, based on Env amino acid sequence features. SLAPNAP also provides measures of variable importance of sequence features. By predicting bnAb coverage of circulating sequences, SLAPNAP can improve ranking of bnAb regimens by their potential prevention efficacy. In addition, SLAPNAP can improve sieve analysis by defining sequence features that impact bnAb prevention efficacy.

AVAILABILITY

SLAPNAP is a freely available docker image that can be downloaded from DockerHub (https://hub.docker.com/r/slapnap/slapnap). Source code and documentation are available at GitHub (respectively, https://github.com/benkeser/slapnap and https://benkeser.github.io/slapnap/).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Nonparametric variable importance assessment using machine learning techniques

In a regression setting, it is often of interest to quantify the importance of various features in predicting the response. Commonly, the variable importance measure used is determined by the regression technique employed. For this reason, practitioners often only resort to one of a few regression techniques for which a variable importance measure is naturally defined. Unfortunately, these regression techniques are often suboptimal for predicting the response. Additionally, because the variable importance measures native to different regression techniques generally have a different interpretation, comparisons across techniques can be difficult. In this work, we study a variable importance measure that can be used with any regression technique, and whose interpretation is agnostic to the technique used. This measure is a property of the true data-generating mechanism. Specifically, we discuss a generalization of the analysis of variance variable importance measure and discuss how it facilitates the use of machine learning techniques to flexibly estimate the variable importance of a single feature or group of features. The importance of each feature or group of features in the data can then be described individually, using this measure. We describe how to construct an efficient estimator of this measure as well as a valid confidence interval. Through simulations, we show that our proposal has good practical operating characteristics, and we illustrate its use with data from a study of risk factors for cardiovascular disease in South Africa.

Protocol driven periprocedural anticoagulation for left atrial ablation

INTRODUCTION

A weight-based heparin dosing policy adjusted for preprocedural oral anticoagulation was implemented to reduce the likelihood of subtherapeutic dosing during left atrial catheter ablation procedures. We hypothesized that initiation of the protocol would result in a greater prevalence of therapeutic activated clotting time (ACT) values and decreased time to therapeutic ACT during left atrial ablation procedures.

METHODS

A departmental protocol was initiated for which subjects received intravenous unfractionated heparin (UFH) to achieve and maintain a goal of ACT >300 s. Initial bolus dose was adjusted for pre-procedure oral anticoagulation and weight as follows: 50 units/kg for those receiving warfarin, 75 units/kg for those not anticoagulated, and 120 units/kg for those on direct oral anticoagulants (DOACs). A UFH infusion was initiated at 10% of the bolus per hour. One hundred consecutive left atrial ablation procedures treated with Protocol Guided heparin dosing were compared with a retrospective consecutive cohort of Usual Care heparin dosing.

RESULTS

When the Usual Care and Protocol Guided cohorts were compared, significant findings were limited to those on pre-procedure DOAC. The initial UFH bolus increased from 99.3 ± 24.8 to 118.2 ± 22.8 units/kg (p < .001), the proportion of therapeutic ACT on the first draw after heparin administration increased from 57.7% to 76.6% (p = .010), and the time to therapeutic ACT after UFH administration decreased from 37.8 ± 19.8 to 30.2 ± 16.4 min (p = .032).

CONCLUSION

A weight-based protocol for periprocedural UFH administration resulted in a higher proportion of therapeutic ACT values and decreased the time to therapeutic ACT for those on pre-procedure DOAC.

Hydroxychloroquine/Azithromycin Therapy and QT Prolongation in Hospitalized Patients With COVID-19

Objectives

This study aimed to characterize corrected QT (QTc) prolongation in a cohort of hospitalized patients with coronavirus disease-2019 (COVID-19) who were treated with hydroxychloroquine and azithromycin (HCQ/AZM).

Background

HCQ/AZM is being widely used to treat COVID-19 despite the known risk of QT interval prolongation and the unknown risk of arrhythmogenesis in this population.

Methods

A retrospective cohort of COVID-19 hospitalized patients treated with HCQ/AZM was reviewed. The QTc interval was calculated before drug administration and for the first 5 days following initiation. The primary endpoint was the magnitude of QTc prolongation, and factors associated with QTc prolongation. Secondary endpoints were incidences of sustained ventricular tachycardia or ventricular fibrillation and all-cause mortality.

Results

Among 415 patients who received concomitant HCQ/AZM, the mean QTc increased from 443 ± 25 ms to a maximum of 473 ± 40 ms (87 [21%] patients had a QTc ≥500 ms). Factors associated with QTc prolongation ≥500 ms were age (p < 0.001), body mass index <30 kg/m² (p = 0.005), heart failure (p < 0.001), elevated creatinine (p = 0.005), and peak troponin (p < 0.001). The change in QTc was not associated with death over the short period of the study in a population in which mortality was already high (hazard ratio: 0.998; p = 0.607). No primary high-grade ventricular arrhythmias were observed.

Conclusions

An increase in QTc was seen in hospitalized patients with COVID-19 treated with HCQ/AZM. Several clinical factors were associated with greater QTc prolongation. Changes in QTc were not associated with increased risk of death.

Strategic Deployment of Cardiology Fellows in Training Using the Accreditation Council for Graduate Medical Education Coronavirus Disease 2019 Framework

Coronavirus disease 2019 is a global pandemic affecting >3 million people in >170 countries, resulting in >200 000 deaths; 35% to 40% of patients and deaths are in the United States. The coronavirus disease 2019 crisis is placing an enormous burden on health care in the United States, including residency and fellowship training programs. The balance between mitigation, training and education, and patient care is the ultimate determinant of the role of cardiology fellows in training during the coronavirus disease 2019 crisis. On March 24, 2020, the Accreditation Council for Graduate Medical Education issued a formal response to the pandemic crisis and described a framework for operation of graduate medical education programs. Guidance for deployment of cardiology fellows in training during the coronavirus disease 2019 crisis is based on the principles of a medical mission, and adherence to preparation, protection, and support of our fellows in training. The purpose of this review is to describe our departmental strategic deployment of cardiology fellows in training using the Accreditation Council for Graduate Medical Education framework for pandemic preparedness.

Efficient nonparametric statistical inference on population feature importance using Shapley values

The true population-level importance of a variable in a prediction task provides useful knowledge about the underlying data-generating mechanism and can help in deciding which measurements to collect in subsequent experiments. Valid statistical inference on this importance is a key component in understanding the population of interest. We present a computationally efficient procedure for estimating and obtaining valid statistical inference on the Shapley Population Variable Importance Measure (SPVIM). Although the computational complexity of the true SPVIM scales exponentially with the number of variables, we propose an estimator based on randomly sampling only Θ(n) feature subsets given n observations. We prove that our estimator converges at an asymptotically optimal rate. Moreover, by deriving the asymptotic distribution of our estimator, we construct valid confidence intervals and hypothesis tests. Our procedure has good finite-sample performance in simulations, and for an in-hospital mortality prediction task produces similar variable importance estimates when different machine learning algorithms are applied.

Antibody Fc effector functions and IgG3 associate with decreased HIV-1 risk

HVTN 505 is a preventative vaccine efficacy trial testing DNA followed by recombinant adenovirus serotype 5 (rAd5) in circumcised, Ad5-seronegative men and transgendered persons who have sex with men in the United States. Identified immune correlates of lower HIV-1 risk and a virus sieve analysis revealed that, despite lacking overall efficacy, vaccine-elicited responses exerted pressure on infecting HIV-1 viruses. To interrogate the mechanism of the antibody correlate of HIV-1 risk, we examined antigen-specific antibody recruitment of Fcγ receptors (FcγRs), antibody-dependent cellular phagocytosis (ADCP), and the role of anti-envelope (anti-Env) IgG3. In a prespecified immune correlates analysis, antibody-dependent monocyte phagocytosis and antibody binding to FcγRIIa correlated with decreased HIV-1 risk. Follow-up analyses revealed that anti-Env IgG3 breadth correlated with reduced HIV-1 risk, anti-Env IgA negatively modified infection risk by Fc effector functions, and that vaccine recipients with a specific FcγRIIa single-nucleotide polymorphism locus had a stronger correlation with decreased HIV-1 risk when ADCP, Env-FcγRIIa, and IgG3 binding were high. Additionally, FcγRIIa engagement correlated with decreased viral load setpoint in vaccine recipients who acquired HIV-1. These data support a role for vaccine-elicited anti-HIV-1 Env IgG3, antibody engagement of FcRs, and phagocytosis as potential mechanisms for HIV-1 prevention.

Prediction of VRC01 neutralization sensitivity by HIV-1 gp160 sequence features

The broadly neutralizing antibody (bnAb) VRC01 is being evaluated for its efficacy to prevent HIV-1 infection in the Antibody Mediated Prevention (AMP) trials. A secondary objective of AMP utilizes sieve analysis to investigate how VRC01 prevention efficacy (PE) varies with HIV-1 envelope (Env) amino acid (AA) sequence features. An exhaustive analysis that tests how PE depends on every AA feature with sufficient variation would have low statistical power. To design an adequately powered primary sieve analysis for AMP, we modeled VRC01 neutralization as a function of Env AA sequence features of 611 HIV-1 gp160 pseudoviruses from the CATNAP database, with objectives: (1) to develop models that best predict the neutralization readouts; and (2) to rank AA features by their predictive importance with classification and regression methods. The dataset was split in half, and machine learning algorithms were applied to each half, each analyzed separately using cross-validation and hold-out validation. We selected Super Learner, a nonparametric ensemble-based cross-validated learning method, for advancement to the primary sieve analysis. This method predicted the dichotomous resistance outcome of whether the IC50 neutralization titer of VRC01 for a given Env pseudovirus is right-censored (indicating resistance) with an average validated AUC of 0.868 across the two hold-out datasets. Quantitative log IC50 was predicted with an average validated R2 of 0.355. Features predicting neutralization sensitivity or resistance included 26 surface-accessible residues in the VRC01 and CD4 binding footprints, the length of gp120, the length of Env, the number of cysteines in gp120, the number of cysteines in Env, and 4 potential N-linked glycosylation sites; the top features will be advanced to the primary sieve analysis. This modeling framework may also inform the study of VRC01 in the treatment of HIV-infected persons.

Adaptive non-inferiority margins under observable non-constancy

A central assumption in the design and conduct of non-inferiority trials is that the active-control therapy will have the same degree of effectiveness in the planned non-inferiority trial as in the prior placebo-controlled trials used to define the non-inferiority margin. This is referred to as the 'constancy' assumption. If the constancy assumption fails, decisions based on the chosen non-inferiority margin may be incorrect, and the study runs the risk of approving an inferior product or failing to approve a beneficial product. The constancy assumption cannot be validated in a trial without a placebo arm, and it is unlikely ever to be met completely. When there are strong, observable predictors of constancy, such as dosing and adherence to the active-control product, we can specify conditions where the constancy assumption will likely fail. We propose a method for using measurable predictors of active-control effectiveness to specify non-inferiority margins targeted to the planned study population characteristics. We describe a pre-specified method, using baseline characteristics or post-baseline predictors in the active-control arm, to adapt the non-inferiority margin at the end of the study if constancy is violated. Adaptive margins can help adjust for constancy violations that will inevitably occur in real clinical trials, while maintaining pre-specified levels of Type I error and power.

Isolation and characterization of glycogen synthase in Dictyostelium discoideum

We have partially purified the protein and isolated the glcS gene for glycogen synthase in Dictyostelium. glcS mRNA is present throughout development and is the product of a single gene coding for 775 amino acids, with a predicted molecular mass of 87 kD. The sequence is highly similar to glycogen synthase from human muscle, yeast, and rat liver, diverging significantly only at the amino and carboxy termini. Phosphorylation and UDPG binding sites are conserved, with K(m) values for UDPG being comparable to those determined for other organisms, but in vitro phosphorylation failing to convert between the G6P-dependent (D) and -independent (I) forms. Enzyme activity is relatively constant throughout the life cycle: the I form of the enzyme isolates with the soluble fraction in amoebae, switches to the D form, becomes pellet-associated during early development, and finally reverts during late development to the I form, which again localizes to the soluble fraction. Deletion analysis of the promoter reveals a GC-rich element which, when deleted, abolishes expression of glcS.

A novel system for the rapid generation of precise DNA deletions

To generate DNA deletions, a tandem array of class IIS restriction enzyme recognition sites was cloned into a plasmid. The recognition sites were arranged so that each enzyme cleaves at a different site within an adjacent target sequence. Digestion with both enzymes followed by end repair and ligation resulted in the deletion of DNA between the two sites of cleavage. Because both recognition sites are preserved following deletion, it was found that sequential deletions could be generated using cycles of restriction enzyme digestion, end repair and ligation. Therefore, this system represents a valuable tool in the definition of functional DNA sequences.

Success of surf lifesaving resuscitations in Queensland, 1973-1992

OBJECTIVE

To determine the success of resuscitations performed by Queensland surf lifesavers and the factors associated with successful resuscitation.

DESIGN

Retrospective case survey, using data from Surf Life Saving Association of Australia resuscitation report forms.

SETTING

54 Queensland beaches patrolled by surf lifesavers, and nearby areas, between 1973 and 1992.

OUTCOME MEASURES

Reasons and success rates for resuscitation, distance from surf clubhouse, whether inside patrolled area, victim's age, sex, facial colour on presentation, occurrence of vomiting, airway difficulties and involvement of alcohol.

RESULTS

171 resuscitations were reported (80% involving males and 20% females), with a success rate of 67%. Seventy-two per cent were performed during patrol hours, 17% within patrolled areas (95% successful) and 55% outside patrolled areas (only 62% successful) (P = 0.004 for difference in success rates); resuscitation success rates fell with increasing distance from the surf clubhouse (P = 0.009). Reasons for resuscitation were: immersion, 70% (success rate, 68%); collapse, 22% (success rate, 47%); and surf or beach injury, 7% and 1%, respectively (success rate, 100% for each). Resuscitation was more likely to be successful if the victim's facial colour on presentation was normal, pale or blue, but not if grey, and if the victim did not vomit or regurgitate.

CONCLUSIONS

Resuscitation by surf lifesavers was highly successful when the victim was close to the surf patrol, indicating a need for funding to expand patrol areas. Public awareness of the greater safety of "bathing between the flags" (in the delineated patrol area) should be increased.

Comparison of atrial-His intervals during tachycardia and atrial pacing in patients with long RP tachycardia

INTRODUCTION

The purpose of this study is to describe a simple and reliable diagnostic maneuver that allows for the rapid differentiation of atypical AV nodal reentrant tachycardia (AVNRT) from other causes of long RP tachycardia. Long RP tachycardias may be caused by atypical AVNRT, orthodromic reciprocating tachycardia (ORT) involving a slowly conducting retrograde accessory pathway, or atrial tachycardia. The differentiation of atypical AVNRT from ORT or atrial tachycardia may be difficult, especially when the differential diagnosis includes a posteroseptal accessory pathway or an atrial tachycardia arising in the posteroseptal right atrium.

METHODS AND RESULTS

Twelve patients with atypical AVNRT, 21 with ORT, and 12 with an atrial tachycardia diagnosed using conventional criteria were enrolled in this study. The atrial-His (AH) interval was measured at the His-bundle position during the tachycardia and during atrial pacing from the high right atrium at the tachycardia cycle length in the setting of sinus rhythm. In patients with atypical AVNRT, the mean AH interval was 69 69 msec +/- 50 msec (+/- SD) longer during high right atrial pacing than during the tachycardia (P < 0.001). In 10 of 12 patients with atypical AVNRT, the AH interval during atrial pacing was more than 40 msec longer than the AH interval measured during the tachycardia. In contrast, in patients with ORT or atrial tachycardia, the differences in AH interval between atrial pacing and tachycardia were never more than 20 and 10 msec, respectively.

CONCLUSION

The difference in the AH interval between atrial pacing and the tachycardia allows a simple and rapid means of differentiating atypical AVNRT from other types of long RP tachycardias.

Comparison of implantation of nonthoracotomy defibrillators in the operating room versus the electrophysiology laboratory

Implantable cardioverter-defibrillators (ICDs) with nonthoracotomy lead systems are widely available, and are implanted either in the electrophysiology laboratory or the operating room. The purpose of this study was to prospectively evaluate the safety and efficacy of nonthoracotomy ICD implantation in an electrophysiology laboratory versus an operating room. During a 7-month period, 62 consecutive ICDs with nonthoracotomy lead systems were implanted in patients in an electrophysiology laboratory. During the next 10 months, 110 consecutive ICDs were implanted in patients in a surgical operating room. All ICD implantations were performed under general anesthesia by electrophysiologists. There were no differences in age (58 +/- 14 vs 62 +/- 12 years, p = 0.06), gender distribution (p = 0.3), frequency of structural heart disease (97% vs 97%, p = 0.9), ejection fraction (0.31 +/- 0.15 vs 0.29 +/- 0.13, p = 0.3), or presentation with cardiac arrest (65% vs 53%, p = 0.2) between patients undergoing ICD implantation in the electrophysiology laboratory and operating room, respectively. The rate of successful implantation and of complications for systems implanted in the electrophysiology laboratory (95% and 13%, respectively) and in the operating room (98% and 14%, respectively) were similar (p = 0.4 and p = 0.8, respectively). Specifically, the rate of infection (0% vs 4%, p = 0.3) and hematoma formation (2% vs 4%, p = 0.8) were not statistically significantly different. Three patients who had undergone ICD implantation in an operating room died within 30 days. ICDs with nonthoracotomy lead systems can be implanted with a similarly high rate of success and acceptable complication rate in the electrophysiology laboratory and in the operating room.

An autonomously propagating luciferase-encoding vector for Dictyostelium discoideum

We have constructed a luc reporter vector for Dictyostelium discoideum using a 626-bp fragment from the nuclear-associated plasmid Ddp2. The ori from Ddp2 is localized within this fragment and was used to provide an autonomous replication sequence for the reporter vector. This reporter vector was stably retained in D. discoideum AX3K cells without alteration. The vector molecule was also found to exist in relatively low copy number compared to other Dictyostelium vectors in the transformed cells. We demonstrated the utility of this vector as a reporter vector with glycogen synthase promoter/luc fusions of varying sizes.

Analysis of junctional ectopy during radiofrequency ablation of the slow pathway in patients with atrioventricular nodal reentrant tachycardia

BACKGROUND

Junctional ectopy may occur during radiofrequency (RF) catheter ablation of the slow pathway in patients with atrioventricular nodal reentrant tachycardia (AVNRT). The purpose of the present study was to characterize this junctional ectopy quantitatively.

METHODS AND RESULTS

The subjects of this study were 52 consecutive patients with AVNRT who underwent slow pathway ablation and 5 additional patients included retrospectively because they had developed high-degree atrioventricular (AV) block during the procedure. A combined anatomic and electrogram mapping approach was used for slow pathway ablation, and AVNRT was successfully eliminated in all patients. In the group of 52 consecutive patients, the incidence of junctional ectopy was significantly higher during 52 effective applications of RF energy than during 366 ineffective applications (100% versus 65%, P < .001). Compared with ineffective RF energy applications, successful RF energy applications had a significantly longer duration of individual bursts of junctional ectopy (7.1 +/- 7.1 versus 5.0 +/- 7.0 seconds [+/- SD], P < .05), a greater total number of junctional beats during the applications (24 +/- 16 versus 15 +/- 8, P < .01), and a greater total span of time during which junctional ectopy occurred (19 +/- 15 versus 11 +/- 12 seconds, P < .01). Four of the 52 patients plus an additional 5 patients developed transient AV block lasting 34 +/- 37 seconds. In 1 of the 9 patients who had transient AV block, third-degree AV nodal block requiring a permanent pacemaker recurred 2 weeks later. In each of the 9 patients who developed AV block, there was ventriculoatrial (VA) block in association with junctional ectopy during the RF energy application immediately preceding the AV block. Among 48 patients who did not develop AV block, 17 patients had at least one episode of VA block during junctional ectopy. The positive predictive value of VA block during junctional ectopy for the development of AV block was 19% in the consecutive series of 52 patients. Among 31 patients who always had 1:1 VA conduction in association with junctional ectopy, 12 had poor VA conduction in the baseline state, with a VA block cycle length of at least 500 milliseconds during ventricular pacing.

CONCLUSIONS

In patients with AVNRT undergoing slow pathway ablation, junctional ectopy during the application of RF energy is a sensitive but nonspecific marker of successful ablation. The bursts of junctional ectopy are significantly longer at effective target sites than at ineffective sites. VA conduction should be expected during the junctional ectopy that accompanies slow pathway ablation, even when there is poor VA conduction during baseline ventricular pacing. VA block during junctional ectopy is a harbinger of AV block in patients undergoing RF ablation of the slow pathway. If energy applications are discontinued as soon as VA block occurs, the risk of AV block may be markedly reduced.

The efficacy of K-edge filters in diagnostic radiology

The application of K-edge filters in diagnostic radiology has been investigated by many workers for over twenty years. These investigations have analysed the effects of such filters on image quality and radiation dose as well as the practicalities of their application. This paper presents a synopsis of the published works and concludes that K-edge filters do not perceptibly improve image quality and make only limited reductions in patient dose. K-edge filters are also costly to purchase and potentially result in a reduction in the cost effectiveness of x-ray examinations by increasing the x-ray tube loading. Equivalent contrast enhancement and dose reductions can be achieved by the assiduous choice of non-selective filters.

Electrophysiologic effects of sotalol and amiodarone in patients with sustained monomorphic ventricular tachycardia

No prospective studies have compared sotalol and amiodarone during electropharmacologic testing. The purpose of this prospective, randomized study was to compare the electrophysiologic effects of sotalol and amiodarone in patients with coronary artery disease and sustained monomorphic ventricular tachycardia (VT). Patients with coronary artery disease and sustained monomorphic VT inducible by programmed stimulation were randomly assigned to receive either sotalol (n = 17) or amiodarone (n = 17). The sotalol dose was titrated to 240 mg twice daily over 7 days. Amiodarone dosing consisted of 600 mg 3 times daily for 10 days. An electrophysiologic test was performed in the baseline state and at the end of the loading regimen. An adequate response was defined as the inability to induce VT or the ability to induce only relatively slow hemodynamically stable VT. During the follow-up electrophysiologic test, 24% of patients taking sotalol and 41% of those taking amiodarone had an adequate response to therapy (p = 0.30). Amiodarone lengthened the mean VT cycle length to a greater degree than sotalol (28% vs 12%, p < 0.01). There were no significant differences in the effects of sotalol and amiodarone on the ventricular effective refractory period. In patients with coronary artery disease, amiodarone and sotalol are similar in efficacy in the treatment of VT as assessed by electropharmacologic testing. The effects of the 2 drugs on ventricular refractoriness are similar, but amiodarone slows VT to a greater extent than sotalol.

Results and efficiency of programmed ventricular stimulation with four extrastimuli compared with one, two, and three extrastimuli

BACKGROUND

Conventional programmed ventricular stimulation protocols are inefficient compared with more recently proposed protocols. The purpose of the present study was to determine if additional efficiency could be derived from a 6-step programmed ventricular stimulation protocol that exclusively uses four extrastimuli.

METHODS AND RESULTS

The subjects were 209 consecutive patients with coronary artery disease and documented sustained monomorphic ventricular tachycardia, nonsustained ventricular tachycardia, aborted sudden death, or syncope. These patients underwent 159 electrophysiological tests in the absence of antiarrhythmic drug therapy and 105 electrophysiological tests in the presence of antiarrhythmic therapy. Programmed stimulation was performed with two protocols in random order in each patient. Both protocols used an eight-beat drive train, 4-s intertrain pause, and basic drive cycle lengths of 350, 400, and 600 ms. The 6-step protocol started with coupling intervals of 290, 280, 270, and 260 ms, which were shortened simultaneously in 10-ms steps until S2 was refractory. The 18-step protocol used one, two and three extrastimuli in conventional sequential fashion. The end points were 30 s of sustained monomorphic ventricular tachycardia, two episodes of polymorphic ventricular tachycardia requiring cardioversion, or completion of the protocol at two right ventricular sites. There was no significant difference in the yield of sustained monomorphic ventricular tachycardia using the two protocols, regardless of the clinical presentation or treatment with antiarrhythmic drugs. Polymorphic ventricular tachycardia occurred with the 18-step protocol twice as frequently as with the 6-step protocol (6% versus 3%, P < .001). The duration of the 18-step protocol was significantly longer than that of the 6-step protocol in patients with inducible ventricular tachycardia (5.5 +/- 7 versus 2.3 +/- 2 minutes, P < .001), as well as in patients without inducible ventricular tachycardia (25.4 +/- 7 versus 6.9 +/- 2 minutes, P < .001).

CONCLUSION

A stimulation protocol that exclusively uses four extrastimuli improves the specificity and efficiency of programmed ventricular stimulation without compromising the yield of monomorphic ventricular tachycardia in patients with coronary artery disease.