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OBJECTIVE: To evaluate real-world implications of updated Surviving Sepsis Campaign (SSC) recommendations for antibiotic timing. DESIGN: Retrospective cohort study. SETTING: Twelve hospitals in the Southeastern United States between 2017 and 2021. PATIENTS: One hundred sixty-six thousand five hundred fifty-nine adult hospitalized patients treated in the emergency department for suspected serious infection. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We determined the number and characteristics of patients affected by updated SSC recommendations for initiation of antibiotics that incorporate a risk- and probability-stratified approach. Using an infection prediction model with a cutoff of 0.5 to classify possible vs. probable infection, we found that 30% of the suspected infection cohort would be classified as shock absent, possible infection and thus eligible for the new 3-hour antibiotic recommendation. In real-world practice, this group had a conservative time to antibiotics (median, 5.5 hr; interquartile range [IQR], 3.2-9.8 hr) and low mortality (2%). Patients categorized as shock absent, probable infection had a median time to antibiotics of 3.2 hours (IQR, 2.1-5.1 hr) and mortality of 3%. Patients categorized as shock present, the probable infection had a median time to antibiotics 2.7 hours (IQR, 1.7-4.6 hr) and mortality of 17%, and patients categorized as shock present, the possible infection had a median time to antibiotics 6.9 hours (IQR, 3.5-16.3 hr) and mortality of 12%. CONCLUSIONS: These data support recently updated SSC recommendations to align antibiotic timing targets with risk and probability stratifications. Our results provide empirical support that clinicians and hospitals should not be held to 1-hour targets for patients without shock and with only possible sepsis. [ABSTRACT FROM AUTHOR]

The article discusses the use of the win ratio as a method for evaluating evidence from clinical trials. The win ratio allows for the inclusion of patient-reported outcomes and surrogate measures in addition to traditional clinical outcomes like death and hospitalization. However, the win ratio has limitations, such as the difficulty in prioritizing component events and the potential for the inclusion of unimportant events. The article provides examples of how the win ratio can lead to overestimation of treatment effects or be driven by biased measures. Overall, the utility of the win ratio depends on the prespecified definition and ranking of clinically relevant components. [Extracted from the article]

Objective: To assess whether different methods for communicating the probability of treatment complications for operative and nonoperative appendicitis treatments result in differences in risk perception. Background: Surgeons must communicate the probability of treatment complications to patients, and how risks are communicated may impact the accuracy and variability in patient risk perceptions and ultimately their decision making. Methods: A series of online surveys of American adults communicated the probability of complications associated with surgical or antibiotic treatment of acute appendicitis. Probability was communicated with verbal descriptors (eg, "uncommon"), point estimates (eg, "3% risk"), or risk ranges (eg, "1% to 5%"). Respondents then estimated the probability of a complication for a "typical patient with appendicitis." The Fligner-Killeen test of homogeneity of variance was used to compare the variability in respondent risk estimates based on the method of probability communication. Results: Among 296 respondents, variance in probability estimates was significantly higher when verbal descriptions were used compared to point estimates (P < 0.001) or risk ranges (P < 0.001). Identical verbal descriptors produced meaningfully different risk estimates depending on the complication being described. For example, "common" was perceived as a 45.6% for surgical site infection but 61.7% for antibiotic-associated diarrhea. Conclusion: Verbal probability descriptors are associated with widely varying and inaccurate perceptions about treatment risks. Surgeons should consider alternative ways to communicate probability during informed consent and shared decision-making discussions. [ABSTRACT FROM AUTHOR]

Background: The Poisson distribution is used to find the probability of an event occurring over an interval of time, distance, area, or volume. Problem: It is a helpful statistical tool, especially when evaluating rare events, and is underused in nursing practice. Approach: A single-group study design is used to demonstrate use of the Poisson distribution in determining whether a change in the number of discrete events is due to random variation or reflects a change in practice patterns and in determining the probability of seeing the number of observed events. Outcomes: Steps demonstrate how one can easily use the Poisson distribution to answer common questions. Conclusion: Use of the Poisson distribution can help nurses make better informed decisions about observed variations in care, especially when the data are not normally distributed, and can prevent undue concern when fluctuations in the number of events are associated with random fluctuations. [ABSTRACT FROM AUTHOR]

Competing Interests: Dr Wittes has consulting contracts with various companies that study heart failure, including Amgen, AstraZeneca, Bristol Myers Squibb, Cytokinetics, and Novartis,

Background: In 2019, Organ Procurement and Transplantation Network/United Network for Organ Sharing changed the exception policy for liver allocation to the median model for end-stage liver disease at transplantation (MMaT). This study evaluated the effects of this change on-waitlist outcomes of simultaneous liver-kidney transplantation (SLKT) for patients with polycystic liver-kidney disease (PLKD)., Methods: Using the Organ Procurement and Transplantation Network/United Network for Organ Sharing registry, 317 patients with PLKD listed for SLKT between January 2016 and December 2021 were evaluated. Waitlist outcomes were compared between prepolicy (Era 1) and postpolicy (Era 2) eras., Results: One-year transplant probability was significantly higher in Era 2 than in Era 1 (55.7% versus 37.9%; P  = 0.001), and the positive effect on transplant probability of Era 2 was significant after risk adjustment (adjusted hazard ratio, 1.76; 95% confidence interval, 1.22-2.54; P  = 0.002 [ref. Era 1]), whereas waitlist mortality was comparable. Transplant centers were separated into the high and low MMaT groups with a score of 29 (median MMaT) and transplant probability in each group between eras was compared. In the high MMaT transplant centers, the 1-y transplant probability was significantly higher in Era 2 (27.5% versus 52.4%; P  = 0.003). The positive effect remained significant in the high MMaT center group (adjusted hazard ratio, 2.79; 95% confidence interval, 1.43-5.46; P  = 0.003 [ref. Era 1]) but not in the low MMaT center group. Although there was a difference between center groups in Era 1 ( P  = 0.006), it became comparable in Era 2 ( P  = 0.54)., Conclusions: The new policy increased 1-y SLKT probability in patients with PKLD and successfully reduced the disparities based on center location., Competing Interests: The authors declare no funding or conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Theoretical guarantees for causal inference using propensity scores are partially based on the scores behaving like conditional probabilities. However, prediction scores between zero and one do not necessarily behave like probabilities, especially when output by flexible statistical estimators. We perform a simulation study to assess the error in estimating the average treatment effect before and after applying a simple and well-established postprocessing method to calibrate the propensity scores. We observe that postcalibration reduces the error in effect estimation and that larger improvements in calibration result in larger improvements in effect estimation. Specifically, we find that expressive tree-based estimators, which are often less calibrated than logistic regression-based models initially, tend to show larger improvements relative to logistic regression-based models. Given the improvement in effect estimation and that postcalibration is computationally cheap, we recommend its adoption when modeling propensity scores with expressive models., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Analyses using population-based health administrative data can return erroneous results if case identification is inaccurate ("misclassification bias"). An acetabular fracture (AF) prediction model using administrative data decreased misclassification bias compared to identifying AFs using diagnostic codes. This study measured the accuracy of this AF prediction model in another hospital. We calculated AF probability in all hospitalizations in the validation hospital between 2015 and 2020. A random sample of 1000 patients stratified by expected AF probability was selected. Patient imaging studies were reviewed to determine true AF status. The validation population included 1000 people. The AF prediction model was very discriminative (c-statistic 0.90, 95% CI: 0.87-0.92) and very well calibrated (integrated calibration index 0.056, 95% CI: 0.039-0.074). AF probability can be accurately determined using routinely collected health administrative data. This observation supports using the AF prediction model to minimize misclassification bias when studying AF using health administrative data., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Outcome under-ascertainment, characterized by the incomplete identification or reporting of cases, poses a substantial challenge in epidemiologic research. While capture-recapture methods can estimate unknown case numbers, their role in estimating exposure effects in observational studies is not well established. This paper presents an ascertainment probability weighting framework that integrates capture-recapture and propensity score weighting. We propose a nonparametric estimator of effects on binary outcomes that combines exposure propensity scores with data from two conditionally independent outcome measurements to simultaneously adjust for confounding and under-ascertainment. Demonstrating its practical application, we apply the method to estimate the relationship between health care work and coronavirus disease 2019 testing in a Swedish region. We find that ascertainment probability weighting greatly influences the estimated association compared to conventional inverse probability weighting, underscoring the importance of accounting for under-ascertainment in studies with limited outcome data coverage. We conclude with practical guidelines for the method's implementation, discussing its strengths, limitations, and suitable scenarios for application., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Predictions under interventions are estimates of what a person's risk of an outcome would be if they were to follow a particular treatment strategy, given their individual characteristics. Such predictions can give important input to medical decision-making. However, evaluating the predictive performance of interventional predictions is challenging. Standard ways of evaluating predictive performance do not apply when using observational data, because prediction under interventions involves obtaining predictions of the outcome under conditions that are different from those that are observed for a subset of individuals in the validation dataset. This work describes methods for evaluating counterfactual performance of predictions under interventions for time-to-event outcomes. This means we aim to assess how well predictions would match the validation data if all individuals had followed the treatment strategy under which predictions are made. We focus on counterfactual performance evaluation using longitudinal observational data, and under treatment strategies that involve sustaining a particular treatment regime over time. We introduce an estimation approach using artificial censoring and inverse probability weighting that involves creating a validation dataset mimicking the treatment strategy under which predictions are made. We extend measures of calibration, discrimination (c-index and cumulative/dynamic AUCt) and overall prediction error (Brier score) to allow assessment of counterfactual performance. The methods are evaluated using a simulation study, including scenarios in which the methods should detect poor performance. Applying our methods in the context of liver transplantation shows that our procedure allows quantification of the performance of predictions supporting crucial decisions on organ allocation., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Several observational studies have described an inverse association between cancer diagnosis and subsequent dementia risk. Multiple biologic mechanisms and potential biases have been proposed in attempts to explain this association. One proposed explanation is the opposite expression of Pin1 in cancer and dementia, and we use this explanation and potential drug target to illustrate the required assumptions and potential sources of bias for inferring an effect of Pin1 on dementia risk from analyses measuring cancer diagnosis as a proxy for Pin1 expression., Methods: We used data from the Rotterdam Study, a population-based cohort. We estimate the association between cancer diagnosis (as a proxy for Pin1) and subsequent dementia diagnosis using two different proxy methods and with confounding and censoring for death addressed with inverse probability weights. We estimate and compare the complements of a weighted Kaplan-Meier survival estimator at 20 years of follow-up., Results: Out of 3634 participants, 899 (25%) were diagnosed with cancer, of whom 53 (6%) had dementia, and 567 (63%) died. Among those without cancer, 15% (411) were diagnosed with dementia, and 667 (24%) died over follow-up. Depending on the confounding and selection bias control, and the way in which cancer was used as a time-varying proxy exposure, the risk ratio for dementia diagnosis ranged from 0.71 (95% confidence interval [CI] = 0.49, 0.95) to 1.1 (95% CI = 0.79, 1.3)., Conclusion: Being explicit about the underlying mechanism of interest is key to maximizing what we can learn from this cancer-dementia association given available or readily collected data, and to defining, detecting, and preventing potential biases., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: HIV molecular epidemiology (ME) is the analysis of sequence data together with individual-level clinical, demographic, and behavioral data to understand HIV epidemiology. The use of ME has raised concerns regarding identification of the putative source in direct transmission events. This could result in harm ranging from stigma to criminal prosecution in some jurisdictions. Here we assessed the risks of ME using simulated HIV genetic sequencing data., Methods: We simulated social networks of men-who-have-sex-with-men, calibrating the simulations to data from San Diego. We used these networks to simulate consensus and next-generation sequence (NGS) data to evaluate the risks of identifying direct transmissions using different HIV sequence lengths, and population sampling depths. To identify the source of transmissions, we calculated infector probability and used phyloscanner software for the analysis of consensus and NGS data, respectively., Results: Consensus sequence analyses showed that the risk of correctly inferring the source (direct transmission) within identified transmission pairs was very small and independent of sampling depth. Alternatively, NGS analyses showed that identification of the source of a transmission was very accurate, but only for 6.5% of inferred pairs. False positive transmissions were also observed, where one or more unobserved intermediaries were present when compared to the true network., Conclusion: Source attribution using consensus sequences rarely infers direct transmission pairs with high confidence but is still useful for population studies. In contrast, source attribution using NGS data was much more accurate in identifying direct transmission pairs, but for only a small percentage of transmission pairs analyzed., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

BACKGROUND: Among patients with heart failure (HF), fatigue is common and linked to quality of life and functional status. Fatigue is hypothesized to manifest as multiple types, with general and exertional components. Unique subtypes of fatigue in HF may require differential assessment and treatment to improve outcomes. We conducted this study to identify fatigue subtypes in persons with prevalent HF in the ARIC study (Atherosclerosis Risk in Communities) and describe the distribution of characteristics across subtypes. METHODS: We performed a cross-sectional analysis of 1065 participants with prevalent HF at ARIC visit 5 (2011–2013). We measured exertional fatigue using the Modified Medical Research Council Breathlessness scale and general fatigue using the Patient Reported Outcomes Measurement Information System fatigue scale. We used latent class analysis to identify subtypes of fatigue. Number of classes was determined using model fit statistics, and classes were interpreted and assigned fatigue severity rating based on the conditional probability of endorsing survey items given class. We compared characteristics across classes using multinomial regression. RESULTS: Overall, participants were 54% female and 38% Black with a mean age of 77. We identified 4 latent classes (fatigue subtypes): (1) high general/high exertional fatigue (18%), (2) high general/low exertional fatigue (27%), (3) moderate general/moderate exertional fatigue (20%), and (4) low/no general and exertional fatigue (35%). Female sex, Black race, lower education level, higher body mass index, increased depressive symptoms, and higher prevalence of diabetes were associated with higher levels of general and exertional fatigue. CONCLUSIONS: We identified unique subtypes of fatigue in patients with HF who have not been previously described. Within subtype, general and exertional fatigue were mostly concordant in severity, and exertional fatigue only occurred in conjunction with general fatigue, not alone. Further understanding these fatigue types and their relationships to outcomes may enhance our understanding of the symptom experience and inform prognostication and secondary prevention efforts for persons with HF. [ABSTRACT FROM AUTHOR]

BACKGROUND: Prompt initiation of bystander cardiopulmonary resuscitation (CPR) is critical to survival for out-of-hospital cardiac arrest (OHCA). However, the association between delays in bystander CPR and OHCA survival is poorly understood. METHODS: In this observational study using a nationally representative US registry, we identified patients who received bystander CPR from a layperson for a witnessed OHCA from 2013 to 2021. Hierarchical logistic regression was used to estimate the association between time to CPR (<1 minute versus 2–3, 4–5, 6–7, 8–9, and ≥10-minute intervals) and survival to hospital discharge and favorable neurological survival (survival to discharge with cerebral performance category of 1 or 2 [ie, without severe neurological disability]). RESULTS: Of 78 048 patients with a witnessed OHCA treated with bystander CPR, the mean age was 63.5±15.7 years and 25, 197 (32.3%) were women. The median time to bystander CPR was 2 (1–5) minutes, with 10% of patients having a≥10-minute delay before initiation of CPR. Overall, 15 000 (19.2%) patients survived to hospital discharge and 13 159 (16.9%) had favorable neurological survival. There was a graded inverse relationship between time to bystander CPR and survival to hospital discharge (P for trend <0.001). Compared with patients who received CPR within 1 minute, those with a time to CPR of 2 to 3 minutes were 9% less likely to survive to discharge (adjusted odds ratio, 0.91 [95% CI, 0.87–0.95]) and those with a time to CPR 4 to 5 minutes were 27% less likely to survive (adjusted odds ratio, 0.73 [95% CI, 0.68–0.77]). A similar graded inverse relationship was found between time to bystander CPR and favorable neurological survival (P for trend <0.001). CONCLUSIONS: Among patients with witnessed OHCA, there was a dose-response relationship between delays in bystander initiation of CPR and lower survival rates. [ABSTRACT FROM AUTHOR]

Background: Clinical disease activity associated with inflammatory bowel disease (IBD) can place physical limitations on youths' activities of daily living. In turn, functional limitations potentially contribute to youths' heightened experience of IBD-induced intrusions on a wide range of routine and valued activities (i.e., illness intrusiveness), which can increase their risk for depressive symptoms. The present study examined the contributions of clinical disease activity, functional disability, and illness intrusiveness to depressive symptoms in youth with IBD., Methods: Youth (N = 180) completed the Functional Disability Inventory (FDI), Illness Intrusiveness Scale-Child (IIS-C), and Children's Depression Inventory-2 (CDI-2). Physicians completed the Physicians Global Assessment of disease activity (PGA)., Results: Results revealed a mediating effect for functional disability in the association between disease activity and depressive symptoms (PGA → FDI → CDI-2); illness intrusiveness mediated the association between functional disability and depressive symptoms (i.e., FDI → IIS-C → CDI-2). Serial mediation revealed that clinical disease activity conferred an indirect effect on youth depressive symptoms through the sequential effects of functional disability and illness intrusiveness (i.e., PGA → FDI → IIS-C → CDI-2)., Conclusions: Taken together, these findings indicate that youth who encounter more physical limitations as a function of clinical disease activity are more likely to experience an amplified sense of IBD-related intrusions on their ability to participate in meaningful activities. In turn, heightened illness intrusiveness increases the likelihood of depressive symptoms. Clinical interventions that help youth maintain adequate functional ability in the face of IBD disease activity and encourage involvement in positively valued activities could decrease the negative impact of IBD on youths' emotional adjustment., (© 2023 European Society for Pediatric Gastroenterology, Hepatology, and Nutrition and North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition.)

Objectives: Whether or not a gastric cancer (GC) patient exhibits lymph node metastasis (LNM) is critical to accurately guiding their treatment and prognostic evaluation, necessitating the ability to reliably predict preoperative LNM status. The present meta-analysis sought to examine the diagnostic value of computed tomography (CT)-based predictive models as a tool to gauge the preoperative LNM status of patients with GC., Methods: Relevant articles were identified in the PubMed, Web of Science, and Wanfang databases. These studies were used to conduct pooled analyses examining sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) values, and area under the curve values were computed for summary receiver operating characteristic curves., Results: The final meta-analysis incorporated data from 15 studies, all of which were conducted in China, enrolling 3,817 patients with GC (LNM+: 1790; LNM-: 2027). The developed CT-based predictive model exhibited respective pooled sensitivity, specificity, PLR, and NLR values of 84% (95% confidence interval [CI], 0.79-0.87), 81% (95% CI, 0.76-0.85), 4.39 (95% CI, 3.40-5.67), and 0.20 (95% CI, 0.16-0.26). The identified results were not associated with significant potential for publication bias ( P = 0.071). Similarly, CT-based analyses of LN status exhibited respective pooled sensitivity, specificity, PLR, and NLR values of 62% (95% CI, 0.53-0.70), 77% (95% CI, 0.72-0.81), 2.71 (95% CI, 2.20-3.33), and 0.49 (95% CI, 0.40-0.61), with no significant risk of publication bias ( P = 0.984)., Conclusions: Overall, the present meta-analysis revealed that a CT-based predictive model may outperform CT-based analyses alone when assessing the preoperative LNM status of patients with GC, offering superior diagnostic utility., Competing Interests: The authors declare no conflict of interest., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Studies designed to estimate the effect of an action in a randomized or observational setting often do not represent a random sample of the desired target population. Instead, estimates from that study can be transported to the target population. However, transportability methods generally rely on a positivity assumption, such that all relevant covariate patterns in the target population are also observed in the study sample. Strict eligibility criteria, particularly in the context of randomized trials, may lead to violations of this assumption. Two common approaches to address positivity violations are restricting the target population and restricting the relevant covariate set. As neither of these restrictions is ideal, we instead propose a synthesis of statistical and simulation models to address positivity violations. We propose corresponding g-computation and inverse probability weighting estimators. The restriction and synthesis approaches to addressing positivity violations are contrasted with a simulation experiment and an illustrative example in the context of sexually transmitted infection testing uptake. In both cases, the proposed synthesis approach accurately addressed the original research question when paired with a thoughtfully selected simulation model. Neither of the restriction approaches was able to accurately address the motivating question. As public health decisions must often be made with imperfect target population information, model synthesis is a viable approach given a combination of empirical data and external information based on the best available knowledge., Competing Interests: The authors report no conflicts of interest., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Background and Objectives: Determining whether multiple sclerosis (MS) causes death is challenging. Our objective was to contrast 2 frameworks to estimate probabilities of death attributed to MS (P MS ) and other causes (P other ): the cause-specific framework (CSF), which requires the causes of death, and the excess mortality framework (EMF), which does not., Methods: We used data from the Observatoire Français de la Sclérose en Plaques (OFSEP, n = 37,524) and from a comparative subset where causes of death were available (4,004 women with relapsing-onset MS [R-MS]). In CSF, the probabilities were estimated using the Aalen-Johansen method. In EMF, they were estimated from the excess mortality hazard, which is the additional mortality among patients with MS as compared with the expected mortality in the matched general population. P MS values were estimated at 30 years of follow-up, (1) with both frameworks in the comparative subset, by age group at onset, and (2) with EMF only in the OFSEP population, by initial phenotype, sex, and age at onset., Results: In the comparative subset, the estimated 30-year P MS values were greater using EMF than CSF: 10.9% (95% CI 8.3-13.6) vs 8.7% (6.4-11.8) among the youngest and 20.4% (11.3-29.5) vs 16.2% (8.7-30.2) for the oldest groups, respectively. In the CSF, probabilities of death from unknown causes ranged from 1.5% (0.7-3.0) to 6.4% (2.5-16.4), and even after their reallocation, P MS values remained lower with CSF than with EMF. The estimated probabilities of being alive were close using the 2 frameworks, and the estimated P Other (EMF vs CSF) was 2.6% (2.5-2.6) vs 2.1% (1.2-3.9) and 18.1% (16.9-19.3) vs 26.4% (16.5-42.2), respectively, for the youngest and oldest groups. In the OFSEP population, the estimated 30-year P MS values ranged from 7.5% (6.4-8.7) to 24.0% (19.1-28.9) in patients with R-MS and from 25.4% (21.1-29.7) to 36.8% (28.3-45.3) in primary progressive patients, depending on sex and age., Discussion: EMF has the great advantage of not requiring death certificates, their quality being less than optimal. Conceptually, it also seems more relevant because it avoids having to state, for each individual, whether death was directly or indirectly caused by MS or whether it would have occurred anyway, which is especially difficult in such chronic diseases.

Background: Availability of detailed data from electronic health records (EHRs) has increased the potential to examine the comparative effectiveness of dynamic treatment strategies using observational data. Inverse probability (IP) weighting of dynamic marginal structural models can control for time-varying confounders. However, IP weights for continuous treatments may be sensitive to model choice., Methods: We describe a target trial comparing strategies for treating anemia with darbepoetin in hemodialysis patients using EHR data from the UK Renal Registry 2004 to 2016. Patients received a specified dose (microgram/week) or did not receive darbepoetin. We compared 4 methods for modeling time-varying treatment: (A) logistic regression for zero dose, standard linear regression for log dose; (B) logistic regression for zero dose, heteroscedastic linear regression for log dose; (C) logistic regression for zero dose, heteroscedastic linear regression for log dose, multinomial regression for patients who recently received very low or high doses; and (D) ordinal logistic regression., Results: For this dataset, method (C) was the only approach that provided a robust estimate of the mortality hazard ratio (HR), with less-extreme weights in a fully weighted analysis and no substantial change of the HR point estimate after weight truncation. After truncating IP weights at the 95th percentile, estimates were similar across the methods., Conclusions: EHR data can be used to emulate target trials estimating the comparative effectiveness of dynamic strategies adjusting treatment to evolving patient characteristics. However, model checking, monitoring of large weights, and adaptation of model strategies to account for these is essential if an aspect of treatment is continuous., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Background and Objectives: Bayesian analysis of randomized controlled trials (RCTs) can extend the value of trial data beyond interpretations based on conventional p value-based binary cutoffs. We conducted an exploratory post hoc Bayesian reanalysis of the minimally invasive surgery with thrombolysis for intracerebral hemorrhage (ICH) evacuation (MISTIE-3) trial and derived probabilities of potential intervention effect on functional and survival outcomes., Methods: MISTIE-3 was a multicenter phase 3 RCT designed to evaluate the efficacy and safety of the MISTIE intervention. Five hundred and six adults (18 years or older) with spontaneous, nontraumatic, supratentorial ICH of ≥30 mL were randomized to receive either the MISTIE intervention (n = 255) or standard medical care (n = 251). We provide Bayesian-derived estimates of the effect of the MISTIE intervention on achieving a good 365-day modified Rankin Scale score (mRS score 0-3) as relative risk (RR) and absolute risk difference (ARD), and the probabilities that these treatment effects are greater than prespecified thresholds. We used 2 sets of prior distributions: (1) reference priors, including minimally informative, enthusiastic, and skeptical priors, and (2) data-derived prior distribution, using a hierarchical random effects model. We additionally evaluated the potential effects of the MISTIE intervention on 180-day and 30-day mRS and 365-, 180-, and 30-day mortality using data-derived priors., Results: The Bayesian-derived probability that MISTIE intervention has any beneficial effect (RR >1) on achieving a good 365-day mRS score was 70% using minimally informative prior, 87% with enthusiastic prior, 68% with skeptical prior, and 73% with data-derived prior. However, these probabilities were ≤55% for RR >1.10 and 0% for RR >1.52 across a range of priors. The probabilities of achieving RR >1 for 180- and 30-day mRS scores are 65% and 80%, respectively. Furthermore, the probabilities of achieving RR <1 for 365-, 180-, and 30-day mortality are 93%, 98%, and 99%, respectively., Discussion: Our exploratory analyses indicate that across a range of priors, the Bayesian-derived probability of MISTIE intervention having any beneficial effect on 365-day mRS for patients with ICH is between 68% and 87%. These analyses do not change the frequentist-based interpretation of the trial. However, unlike the frequentist p values, which indirectly evaluate treatment effects and only provide an arbitrary binary cutoff (such as 0.05), the Bayesian framework directly estimates the probabilities of potential treatment effects., Trial Registration Information: ClinicalTrials.gov/ct2/show/NCT01827046., Classification of Evidence: This study provides Class II evidence that minimally invasive surgery (MIS) + recombinant tissue plasminogen activator (rt-PA) does not significantly improve functional outcome in patients with ICH. However, this study lacks the precision to exclude a potential benefit of MIS + rt-PA., (© 2023 American Academy of Neurology.)

Visualization is a key aspect of communicating the results of any study aiming to estimate causal effects. In studies with time-to-event outcomes, the most popular visualization approach is depicting survival curves stratified by the variable of interest. This approach cannot be used when the variable of interest is continuous. Simple workarounds, such as categorizing the continuous covariate and plotting survival curves for each category, can result in misleading depictions of the main effects. Instead, we propose a new graphic, the survival area plot, to directly depict the survival probability over time and as a function of a continuous covariate simultaneously. This plot utilizes g-computation based on a suitable time-to-event model to obtain the relevant estimates. Through the use of g-computation, those estimates can be adjusted for confounding without additional effort, allowing a causal interpretation under the standard causal identifiability assumptions. If those assumptions are not met, the proposed plot may still be used to depict noncausal associations. We illustrate and compare the proposed graphics to simpler alternatives using data from a large German observational study investigating the effect of the Ankle-Brachial Index on survival. To facilitate the usage of these plots, we additionally developed the contsurvplot R-package, which includes all methods discussed in this paper., Competing Interests: The authors report no conflicts of interest., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)

Competing Interests: Disclosures None.

Background and Objectives: This study aimed to evaluate and predict the effects of interictal epileptiform discharges (IEDs) on driving ability using simple reaction tests and a driving simulator., Methods: Patients with various epilepsies were evaluated with simultaneous EEGs during their response to visual stimuli in a single-flash test, a car-driving video game, and a realistic driving simulator. Reaction times (RTs) and missed reactions or crashes (miss/crash) during normal EEG and IEDs were measured. IEDs, as considered in this study, were a series of epileptiform potentials (>1 potential) and were classified as generalized typical, generalized atypical, or focal. RT and miss/crash in relation to IED type, duration, and test type were analyzed. RT prolongation, miss/crash probability, and odds ratio (OR) of miss/crash due to IEDs were calculated., Results: Generalized typical IEDs prolonged RT by 164 ms, compared with generalized atypical IEDs (77.0 ms) and focal IEDs (48.0 ms) ( p < 0.01). Generalized typical IEDs had a session miss/crash probability of 14.7% compared with a zero median for focal and generalized atypical IEDs ( p < 0.01). Long repetitive bursts of focal IEDs lasting >2 seconds had a 2.6% miss/crash probability IED . Cumulated miss/crash probability could be predicted from RT prolongation: 90.3 ms yielded a 20% miss/crash probability. All tests were nonsuperior to each other in detecting miss/crash probabilities IED (zero median for all 3 tests) or RT prolongations (flash test: 56.4 ms, car-driving video game: 75.5 ms, simulator 86.6 ms). IEDs increased the OR of miss/crash in the simulator by 4.9-fold compared with normal EEG. A table of expected RT prolongations and miss/crash probabilities for IEDs of a given type and duration was created., Discussion: IED-associated miss/crash probability and RT prolongation were comparably well detected by all tests. Long focal IED bursts carry a low risk, while generalized typical IEDs are the primary cause of miss/crash. We propose a cumulative 20% miss/crash risk at an RT prolongation of 90.3 ms as a clinically relevant IED effect. The IED-associated OR in the simulator approximates the effects of sleepiness or low blood alcohol level while driving on real roads. A decision aid for fitness-to-drive evaluation was created by providing the expected RT prolongations and misses/crashes when IEDs of a certain type and duration are detected in routine EEG., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Background and Objectives: Current scales used in amyotrophic lateral sclerosis (ALS) attempt to summarize different functional domains or "dimensions" into 1 overall score, which may not accurately characterize the individual patient's disease severity or prognosis. The use of composite score risks declaring treatments ineffective if not all dimensions of ALS disease progression are affected equally. We aimed to develop the ALS Impairment Multidomain Scale (AIMS) to comprehensively characterize disease progression and increase the likelihood of identifying effective treatments., Methods: The Revised ALS Functional Rating Scale (ALSFRS-R) and a preliminary questionnaire, based on literature review and patient input, were completed online by patients from the Netherlands ALS registry at bimonthly intervals over a period of 12 months. A 2-week test-retest, factor analysis, Rasch analysis, and a signal-to-noise optimization strategy were performed to create a multidomain scale. Reliability, longitudinal decline, and associations with survival were evaluated. The sample size required to detect a 35% reduction in progression rate over 6 or 12 months was assessed for a clinical trial that defines the ALSFRS-R or AIMS subscales as a primary endpoint family., Results: The preliminary questionnaire, consisting of 110 questions, was completed by 367 patients. Three unidimensional subscales were identified, and a multidomain scale was constructed with 7 bulbar, 11 motor, and 5 respiratory questions. Subscales fulfilled Rasch model requirements, with excellent test-retest reliability of 0.91-0.94 and a strong relationship with survival ( p < 0.001). Compared with the ALSFRS-R, signal-to-noise ratios were higher as patients declined more uniformly per subscale. Consequently, the estimated sample size reductions achieved with the AIMS compared with those achieved with the ALSFRS-R were 16.3% and 25.9% for 6-month and 12-month clinical trials, respectively., Discussion: We developed the AIMS, consisting of unidimensional bulbar, motor, and respiratory subscales, which may characterize disease severity better than a total score. AIMS subscales have high test-retest reliability, are optimized to measure disease progression, and are strongly related to survival time. The AIMS can be easily administered and may increase the likelihood of identifying effective treatments in ALS clinical trials., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Background: The current understanding of untreated ruptured intracranial aneurysms has been limited by study design and inaccurate patient data. Multicenter clinical registry studies on untreated ruptured intracranial aneurysms in Chinese patients are scarce. We aimed to calculate the mortality of patients with untreated ruptured intracranial aneurysms in a current, clearly defined hospital cohort in China, with emphasis on mortality predictors over a 2-year period., Methods: Patients with saccular untreated ruptured intracranial aneurysms were identified from the Chinese Multicenter Cerebral Aneurysm Database, a multicenter, prospective, observational database registered in China, which involved 32 tertiary medical centers covering 4 northern Chinese provincial regions. Patients with intracranial aneurysms, regardless of ruptured status, shape, age, or comorbidities, were consecutively included in 12 of 32 medical centers between 2017 and 2020. Survival probabilities were computed using the Kaplan-Meier method. Univariate and multivariate Cox regression analyses were conducted to determine the risk factors for the cumulative 2-year mortality. We analyzed the reasons for treatment decisions stratified by demographic characteristics and clinical features., Results: For 941 enrolled patients, 58.6% of patients died within 1 month of symptom onset; and 68.1% within 2 years. 98 patients underwent surgical repair during follow-up. Multivariate Cox regression analysis identified Hunt and Hess grades 3 to 5 (hazard ratio, 1.54 [95% CI, 1.01-2.35]; P =0.047), loss of consciousness at symptom onset (hazard ratio, 1.56 [95% CI, 1.18-2.07]; P =0.002), and largest aneurysm size of ≥5 mm (hazard ratio, 1.29 [95% CI, 1.05-1.59]; P =0.014) as mortality predictors during the 2-year follow-up. Among patients who were successfully followed up, 42.6% (280) of them refused surgical treatment., Conclusions: Patients with poor Hunt and Hess grades, loss of consciousness at symptom onset, or largest aneurysms ≥5 mm in size showed a high mortality rate. A high number of treatment refusals was present in this study. These findings have implications for medical insurance policy, doctor-patient communication, and popular science education., Competing Interests: Disclosures None.

Background: Repeat stereotactic radiosurgery (SRS) for persistent cerebral arteriovenous malformation (AVM) has generally favorable patient outcomes. However, reporting studies are limited by small patient numbers and single-institution biases. The purpose of this study was to provide the combined experience of multiple centers, in an effort to fully define the role of repeat SRS for patients with arteriovenous malformation., Methods: This multicenter, retrospective cohort study included patients treated with repeat, single-fraction SRS between 1987 and 2022. Follow-up began at repeat SRS. The primary outcome was a favorable patient outcome, defined as a composite of nidus obliteration in the absence of hemorrhage or radiation-induced neurological deterioration. Secondary outcomes were obliteration, hemorrhage risk, and symptomatic radiation-induced changes. Competing risk analysis was performed to compute yearly rates and identify predictors for each outcome., Results: The cohort comprised 505 patients (254 [50.3%] males; median [interquartile range] age, 34 [15] years) from 14 centers. The median clinical and magnetic resonance imaging follow-up was 52 (interquartile range, 61) and 47 (interquartile range, 52) months, respectively. At last follow-up, favorable outcome was achieved by 268 (53.1%) patients (5-year probability, 50% [95% CI, 45%-55%]) and obliteration by 300 (59.4%) patients (5-year probability, 56% [95% CI, 51%-61%]). Twenty-eight patients (5.6%) experienced post-SRS hemorrhage with an annual incidence rate of 1.38 per 100 patient-years. Symptomatic radiation-induced changes were evident in 28 (5.6%) patients, with most occurring in the first 3 years. Larger nidus volumes (between 2 and 4 cm 3 , subdistribution hazard, 0.61 [95% CI, 0.44-0.86]; P =0.005; >4 cm 3 , subdistribution hazard, 0.47 [95% CI, 0.32-0.7]; P <0.001) and brainstem/basal ganglia involvement (subdistribution hazard, 0.6 [95% CI, 0.45-0.81]; P <0.001) were associated with reduced probability of favorable outcome., Conclusions: Repeat SRS confers reasonable obliteration rates with a low complication risk. With most complications occurring in the first 3 years, extending the latency period to 5 years generally increases the rate of favorable patient outcomes and reduces the necessity of a third intervention., Competing Interests: Disclosures Dr Palmer has received grants from Genentech Inc. and Varian Medical Systems Inc, speaking fees from Varian Medical Systems Inc, and is a consultant for Novocure Inc. Dr Lunsford has ownership interest (shareholder) in Elekta AB and is a consultant Chair DSMB for Insightec Inc. Dr Cifarelli has received a speaking honorarium from Carl Zeiss Meditech AG. Dr Liscak is a consultant for Elekta AB. Dr McInerney has received funding from Elekta AB for research unrelated to this study. The other authors report no conflicts.

Background: With genetic testing advancements, the burden of incidentally identified cardiac disease-associated gene variants is rising. These variants may carry a risk of sudden cardiac death, highlighting the need for accurate diagnostic interpretation. We sought to identify pathogenic hotspots in sudden cardiac death-associated genes using amino acid-level signal-to-noise (S:N) analysis and develop a web-based precision medicine tool, DiscoVari , to improve variant evaluation., Methods: The minor allele frequency of putatively pathogenic variants was derived from cohort-based cardiomyopathy and channelopathy studies in the literature. We normalized disease-associated minor allele frequencies to rare variants in an ostensibly healthy population (Genome Aggregation Database) to calculate amino acid-level S:N. Amino acids with S:N above the gene-specific threshold were defined as hotspots. DiscoVari was built using JavaScript ES6 and using open-source JavaScript library ReactJS, web development framework Next.js, and JavaScript runtime NodeJS. We validated the ability of DiscoVari to identify pathogenic variants using variants from ClinVar and individuals clinically evaluated at the Duke University Hospitals with cardiac genetic testing., Results: We developed DiscoVari as an internet-based tool for S:N-based variant hotspots. Upon validation, a higher proportion of ClinVar likely pathogenic/pathogenic variants localized to DiscoVari hotspots (43.1%) than likely benign/benign variants (17.8%; P< 0.0001). Further, 75.3% of ClinVar variants reclassified to likely pathogenic/pathogenic were in hotspots, compared with 41.3% of those reclassified as variants of uncertain significance ( P< 0.0001) and 23.4% of those reclassified as likely benign/benign ( P <0.0001). Of the clinical cohort variants, 73.1% of likely pathogenic/pathogenic were in hotspots, compared with 0.0% of likely benign/benign ( P< 0.01)., Conclusions: DiscoVari reliably identifies disease-susceptible amino acid residues to evaluate variants by searching amino acid-specific S:N ratios., Competing Interests: Disclosures Dr Rosamilia was paid a consulting fee by Nable Bio for a project unrelated to the present article. The other authors report no conflicts.

Background: Several methods for conducting power analysis of studies with outcomes across the full ordinal modified Rankin Scale are proposed in the literature. No systematic comparison of accuracy, agreement, and sensitivity to small changes in hypothesized effect sizes for these methods is available. Our aim is to conduct such a systematic comparative analysis and to introduce a comprehensive freely available online tool to facilitate appropriate power analyses for ordinal outcomes., Methods: We performed simulation studies utilizing the control arm modified Rankin Scale distributions from the AVERT (A Very Early Rehabilitation Trial), EXTEND (Extending the Time for Thrombolysis in Emergency Neurological Deficits), and HERMES (Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials) studies, as well as a uniform distribution, in combination with hypothetical treatment effects. We systematically evaluated published power formulas for Ordinal Logistic Regression and Tournament Methods (generalized odds ratio; Win Probability; Win Ratio; and Wilcoxon-Mann-Whitney U test). We also developed an online and downloadable Shiny R app facilitating sample size calculation for, and ordinal analysis of, modified Rankin Scale data., Results: Power formulas for Tournament Methods performed well, while the formula for ordinal logistic regression was inaccurate. Tang's Wilcoxon-Mann-Whitney U test sample size formula exhibited the highest accuracy. All methods, including ordinal logistic regression, had almost identical empirical power for a given sample size. All power methods exhibited sensitivity to small changes in hypothesized effect size. The developed freely available online app supports analytical and visualization requirements for all investigated methods for power and statistical analyses of ordinal modified Rankin Scale outcomes., Conclusions: As Tournament Method sample size formulas are assumption-free and accurately calculate power, stroke researchers should use these methods when designing studies with outcomes measured on the full or partially collapsed modified Rankin Scale as well as other ordinal scales, even if they intend to use ordinal logistic regression for analysis. Conducting sensitivity analyses of the effect size assumptions are essential for appropriate sample size estimation. Our developed tool supports both of these recommendations (https://www.thembc.com.au/tournamentmethods)., Competing Interests: Disclosures None.

Background: Practice patterns and outcomes associated with the use of oral anticoagulation for arterial thromboembolism prevention following a hospitalization with new-onset atrial fibrillation (AF) during sepsis are unclear. Methods: Retrospective, observational cohort study of patients ≥40 years of age discharged alive following hospitalization with new-onset AF during sepsis across 21 hospitals in the Kaiser Permanente Northern California health care delivery system, years 2011 to 2018. Primary outcomes were ischemic stroke/transient ischemic attack (TIA), with a safety outcome of major bleeding events, both within 1 year of discharge alive from sepsis hospitalization. Adjusted risk differences for outcomes between patients who did and did not receive oral anticoagulation within 30 days of discharge were estimated using marginal structural models fitted by inverse probability weighting using Super Learning within a target trial emulation framework. Results: Among 82 748 patients hospitalized with sepsis, 3992 (4.8%) had new-onset AF and survived to hospital discharge; mean age was 78±11 years, 53% were men, and 70% were White. Patients with new-onset AF during sepsis averaged 45±33% of telemetry monitoring entries with AF, and 27% had AF present on the day of hospital discharge. Within 1 year of hospital discharge, 89 (2.2%) patients experienced stroke/TIA, 225 (5.6%) had major bleeding, and 1011 (25%) died. Within 30 days of discharge, 807 (20%) patients filled oral anticoagulation prescriptions, which were associated with higher 1-year adjusted risks of ischemic stroke/TIA (5.69% versus 2.32%; risk difference, 3.37% [95% CI, 0.36–6.38]) and no significant difference in 1-year adjusted risks of major bleeding (6.51% versus 7.10%; risk difference, −0.59% [95% CI, −3.09 to 1.91]). Sensitivity analysis of ischemic stroke–only outcomes showed a risk difference of 0.15% (95% CI, −1.72 to 2.03). Conclusions: After hospitalization with new-onset AF during sepsis, oral anticoagulation use was uncommon and associated with potentially higher stroke/TIA risk. Further research to inform mechanisms of stroke and TIA and management of new-onset AF after sepsis is needed. [ABSTRACT FROM AUTHOR]

Background and Objectives: The question of the long-term safety of pregnancy is a major concern in patients with multiple sclerosis (MS), but its study is biased by reverse causation (women with higher disability are less likely to experience pregnancy). Using a causal inference approach, we aimed to estimate the unbiased long-term effects of pregnancy on disability and relapse risk in patients with MS and secondarily the short-term effects (during the perpartum and postpartum years) and delayed effects (occurring beyond 1 year after delivery)., Methods: We conducted an observational cohort study with data from patients with MS followed in the Observatoire Français de la Sclérose en Plaques registry between 1990 and 2020. We included female patients with MS aged 18-45 years at MS onset, clinically followed up for more than 2 years, and with ≥3 Expanded Disease Status Scale (EDSS) measurements. Outcomes were the mean EDSS score at the end of follow-up and the annual probability of relapse during follow-up. Counterfactual outcomes were predicted using the longitudinal targeted maximum likelihood estimator in the entire study population. The patients exposed to at least 1 pregnancy during their follow-up were compared with the counterfactual situation in which, contrary to what was observed, they would not have been exposed to any pregnancy. Short-term and delayed effects were analyzed from the first pregnancy of early-exposed patients (who experienced it during their first 3 years of follow-up)., Results: We included 9,100 patients, with a median follow-up duration of 7.8 years, of whom 2,125 (23.4%) patients were exposed to at least 1 pregnancy. Pregnancy had no significant long-term causal effect on the mean EDSS score at 9 years (causal mean difference [95% CI] = 0.00 [-0.16 to 0.15]) or on the annual probability of relapse (causal risk ratio [95% CI] = 0.95 [0.93-1.38]). For the 1,253 early-exposed patients, pregnancy significantly decreased the probability of relapse during the perpartum year and significantly increased it during the postpartum year, but no significant delayed effect was found on the EDSS and relapse rate., Discussion: Using a causal inference approach, we found no evidence of significantly deleterious or beneficial long-term effects of pregnancy on disability. The beneficial effects found in other studies were probably related to a reverse causation bias., (© 2022 American Academy of Neurology.)

Background: In many research settings, the intervention implied by the average causal effect of a time-varying exposure is impractical or unrealistic, and we might instead prefer a more realistic target estimand. Instead of requiring all individuals to be always exposed versus unexposed, incremental effects quantify the impact of merely shifting each individual's probability of being exposed., Methods: We demonstrate the estimation of incremental effects in the time-varying setting, using data from the Effects of Aspirin in Gestation and Reproduction trial, which assessed the effect of preconception low-dose aspirin on pregnancy outcomes. Compliance to aspirin or placebo was summarized weekly and was affected by time-varying confounders such as bleeding or nausea. We sought to estimate what the incidence of pregnancy by 26 weeks postrandomization would have been if we shifted each participant's probability of taking aspirin or placebo each week by odds ratios (OR) between 0.30 and 3.00., Results: Under no intervention (OR = 1), the incidence of pregnancy was 77% (95% CI: 74%, 80%). Decreasing women's probability of complying with aspirin had little estimated effect on pregnancy incidence. When we increased women's probability of taking aspirin, estimated incidence of pregnancy increased, from 83% (95% confidence interval [CI] = 79%, 87%) for OR = 2 to 89% (95% CI = 84%, 93%) for OR=3. We observed similar results when we shifted women's probability of complying with a placebo., Conclusions: These results estimated that realistic interventions to increase women's probability of taking aspirin would have yielded little to no impact on the incidence of pregnancy, relative to similar interventions on placebo., Competing Interests: The authors report no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Patients with rheumatoid arthritis require frequent consultations to monitor disease activity and intensify medication when treatment targets are not met. However, because most patients are in remission during follow-up, it should be possible to reduce the number of consultations for them. Electronic patient-reported outcomes (ePROs) could be used to identify patients who meet their treatment goal and who could therefore be eligible to skip their visit., Objective: The aim of this study was to assess the probability that patients with low disease activity scores on their ePROs do not need a disease-modifying antirheumatic drug (DMARD) or steroid intensification in the first 2 weeks after completion of the ePROs., Methods: This medical-records review study compared results of ePROs answered during routine care with DMARD or steroid intensifications collected from anonymized electronic medical record at Reade. The primary outcome was the positive predictive value (PPV) of having a low disease activity score on an ePRO for not receiving a DMARD or steroid intensifications within 2 weeks. The 3 studied ePROs (and respective low disease activity outcome) were the Routine Assessment of Patient Index Data 3 (RAPID3) (score <2), Patient Acceptable Symptom State (PASS) (yes), and the flare question (no). The secondary aim of the study was to assess which combination of ePROs resulted in the best PPV for DMARD or steroid intensifications., Results: Of the 400 randomly selected records, ultimately 321 were included (302 unique patients). The PPV of a RAPID3 <2, being in PASS, and a negative answer on the flare question were, respectively, 99%, 95%, and 83% to not receive a DMARD or steroid intensification within 2 weeks. The combination of a RAPID3 <2 and a negative flare question resulted in a PPV of 100%; this combination was present in 29% (93/321) of the total study population., Conclusion: The RAPID3, PASS, and flare question have a high diagnostic accuracy to identify individuals who will not receive a DMARD or steroid intensification in the following 2 weeks. The combination of the RAPID3 and flare question yielded the best combination of diagnostic accuracy and highest percentage of patients who could be eligible to skip a visit. These results suggest that accurate identification of patients who meet their treatment goal with ePROs is possible., Competing Interests: The authors declare no conflict of interest., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Whether the effect of switch probability on switch and mixing costs is explained by an activation or preparation account is unclear., Objective: To investigate the account of the effect of switch probability on switch and mixing costs., Method: We used a cued task-switching paradigm with three switch probabilities (high, 75%; medium, 50%; and low, 25%) with 19 healthy young adults and recorded the cue- and target-locked event-related potentials (ERPs) and behavioral performance. The task included switch and stay trials under high, medium, and low switch conditions, as well as pure trials., Results: There was no significant difference in reaction time (RT) in switch and mixing costs between the high and medium switch conditions. The RT in switch and mixing costs in the high and medium switch conditions was significantly less and more than in the low switch condition, respectively. The cue-locked ERPs revealed significant effects on mixing costs (stay - pure) that were cue early frontal positivity (260-300 ms) in the high and medium switch conditions, and on switch costs (switch - stay) that were cue early central positivity (240-260 ms) in the low switch condition. Moreover, the target-locked ERPs of the mixing costs revealed significant effects on mixing costs that were target P3b (440-540 ms) in all three switch conditions, and on switch costs that were target P3b in the medium and low switch conditions., Conclusion: The effect of switch probability on switch and mixing costs is explained by the activation account., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: To systematically review all studies that developed or validated a vaginal birth after cesarean (VBAC) prediction model., Data Sources: MEDLINE, EMBASE, CINAHL, Cochrane Library, and ClinicalTrials.gov were searched from inception until February 2022., Methods of Study Selection: We included observational studies that developed or validated a multivariable VBAC prediction model in women with a singleton pregnancy and one previous lower segment cesarean delivery. A total of 3,758 articles were identified and screened., Tabulation, Integration, and Results: For 57 included studies, data were extracted in duplicate using a CHARMS (Critical Appraisal and Data Extraction for Systematic Review of Prediction Modelling Studies) checklist-based tool and included participants' characteristics, sample size, predictors, timing of application, and performance. PROBAST (Prediction model Risk of Bias Assessment Tool) and TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis) were used to assess risk of bias and transparency of reporting. Several studies developed or validated more than one model. There were 38 unique prediction models, 42 external validations of 10 existing prediction models, and six modifications of existing models. Of the 38 unique models, only 19 (19/38, 50%) were internally validated in the initial study. No studies externally validated their model in the initial study. Age, previous vaginal birth, and previous cesarean delivery for labor dystocia were the commonest predictors. The area under the curve in included studies ranged from 0.61 to 0.95. Models used close to delivery generally outperformed those used earlier in pregnancy. Most studies demonstrated a high risk of bias (45/57, 79%), the remainder were unclear (7/57, 12%) and low (5/57, 9%). Median TRIPOD checklist adherence was 70% (range 32-93%)., Conclusion: Several prediction models for VBAC success exist, but many lack external validation and are at high risk of bias. Models used close to delivery outperformed those used earlier in pregnancy; however, their generalizability and applicability remain unclear. High-quality external validation and effect studies are required to guide clinical use., Systematic Review Registration: PROSPERO, CRD42020190930., Competing Interests: Financial Disclosure The authors did not report any potential conflicts of interest., (Copyright © 2022 by the American College of Obstetricians and Gynecologists. Published by Wolters Kluwer Health, Inc. All rights reserved.)

To investigate the significance of postmastectomy radiotherapy (PMRT) for different molecular subtypes of female breast cancer T1-2N1M0 based on inverse probability of treatment weighting (IPTW). The data of breast cancer patients diagnosed between 2010 and 2014 from the Surveillance, Epidemiology, and End Results (SEER) database were extracted. According to the status of hormone receptor (HR) and human epidermal growth factor receptor-2 (HER2), the patients were classified into luminal-A (HR+/HER2-), luminal-B (HR+/HER2+), HER2-enriched (HR-/HER2+), and TNBC (HR-/HER2-) subtypes. The association between radiation therapy and breast cancer-specific survival (BCSS) and Overall survival (OS) was retrospectively analyzed. Inverse probability of treatment weighting (IPTW) was applied to balance measurable confounders. Among the 16 894 patients, 6 055 (35.8%) were in the PMRT group and 10 839 (64.2%) were in the nonPMRT group, with a median follow-up of 48 months. There were 1003 deaths from breast cancer and 754 deaths from other causes. After IPTW, the covariates between groups reached complete equilibrium, the multifactorial Cox regression analysis showed that PMRT significantly prolonged OS and BCSS in Luminal-A and TNBC subtype breast cancer patients, yet it brought little significant survival advantage in Luminal-B and HER2-enriched subtype patients. Our study demonstrates a beneficial impact for PMRT on OS and BCSS among Luminal-A and TNBC subtype breast cancer patients with T1-2N1 disease., (Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Wilkins modification of the Gartland classification (WMGC) type IIB supracondylar humeral fractures (SCHFs) are unstable, and their primary treatment is surgery. This study sought to evaluate the chance of closed reduction and long arm cast (CR&LAC) treatment of type IIB fractures., Methods: In this retrospective case-control study, pediatric patients with WMGC type II fractures whose initial treatment was CR&LAC were examined. Cases were subdivided according to WMGC. Type IIA and IIB cases were compared in terms of the reduction loss rate and clinical and radiologic results. Then, patients with type IIB fractures who were treated conservatively or surgically were compared in terms of clinical and radiologic results., Results: A total of 817 pediatric SCHFs were examined, of which 233 had type II fractures. This study finally enrolled 87 cases who met the inclusion criteria, including 52 with type IIA fractures and 35 with type IIB fractures. Among those with type IIB fractures, the first-time reduction success rate was 44.3%. Although the probability of a loss of reduction among type IIB fractures in conservative follow-up was ~5 times higher than that among type IIA fractures, all the cases with reduction loss were detected among the first-week controls, and 9 of them were type IIB and 3 were type IIA ( P =0.011). The treatment of 26 (32.9%) cases with type IIB fractures was completed conservatively. There was no difference in the clinical or radiologic comparison results of type IIA and type IIB fractures whose treatment was completed conservatively. There was no clinical or radiologic difference in the comparison of type IIB fractures whose treatment began with CR&LAC but was completed conservatively or surgically., Conclusions: Although the initial reduction success is not high among WMGC type IIB fractures, the results are like those of conservatively managed type IIA fractures if successful reduction is achieved. This study showed that the treatment results of all type II SCHFs with no loss of reduction in the first week after CR&LAC are satisfactory. No reduction loss was observed in any of the cases after the first week., Level of Evidence: Level III, case-control study., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Background: The authors estimate the probability of successful development and duration of clinical trials for medications to treat neuropathic and nociceptive pain. The authors also consider the effect of the perceived abuse potential of the medication on these variables., Methods: This study uses the Citeline database to compute the probabilities of success, duration, and survivorship of pain medication development programs between January 1, 2000, and June 30, 2020, conditioned on the phase, type of pain (nociceptive vs. neuropathic), and the abuse potential of the medication., Results: The overall probability of successful development of all pain medications from phase 1 to approval is 10.4% (standard error, 1.5%). Medications to treat nociceptive and neuropathic pain have a probability of successful development of 13.3% (standard error, 2.3%) and 7.1% (standard error, 1.9%), respectively. The probability of successful development of medications with high abuse potential and low abuse potential are 27.8% (standard error, 4.6%) and 4.7% (standard error, 1.2%), respectively. The most common period for attrition is between phase 3 and approval., Conclusions: The authors' data suggest that the unique attributes of pain medications, such as their abuse potential and intended pathology, can influence the probability of successful development and duration of development., (Copyright © 2022, the American Society of Anesthesiologists. All Rights Reserved.)

Background: There have been multiple efforts toward individual prediction of recurrent strokes based on structured clinical and imaging data using machine learning algorithms. Some of these efforts resulted in relatively accurate prediction models. However, acquiring clinical and imaging data is typically possible at provider sites only and is associated with additional costs. Therefore, we developed recurrent stroke prediction models based solely on data easily obtained from the patient at home., Methods: Data from 384 patients with ischemic stroke were obtained from the Erlangen Stroke Registry. Patients were followed at 3 and 12 months after first stroke and then annually, for about 2 years on average. Multiple machine learning algorithms were applied to train predictive models for estimating individual risk of recurrent stroke within 1 year. Double nested cross-validation was utilized for conservative performance estimation and models' learning capabilities were assessed by learning curves. Predicted probabilities were calibrated, and relative variable importance was assessed using explainable artificial intelligence techniques., Results: The best model achieved the area under the curve of 0.70 (95% CI, 0.64-0.76) and relatively good probability calibration. The most predictive factors included patient's family and housing circumstances, rehabilitative measures, age, high calorie diet, systolic and diastolic blood pressures, percutaneous endoscopic gastrotomy, number of family doctor's home visits, and patient's mental state., Conclusions: Developing fairly accurate models for individual risk prediction of recurrent ischemic stroke within 1 year solely based on registry data is feasible. Such models could be applied in a home setting to provide an initial risk assessment and identify high-risk patients early.

Background: Percutaneous coronary intervention (PCI) has been used increasingly as an alternative means of revascularization for patients with chronic total occlusion and multivessel disease. We investigated 5-year clinical outcomes following coronary artery bypass grafting (CABG) and PCI in patients with chronic total occlusion and multivessel disease. Methods: In this single-center, retrospective cohort study, 4324 consecutive patients with >=1 chronic total occlusion and multivessel disease were treated with either CABG (n=2264) or PCI (n=2060) between 2010 and 2013. The primary outcome was 5-year composite of death, myocardial infarction, or stroke. An inverse-probability-of-treatment weighting method was used adjusting for both patient and lesion characteristics. Results: The unadjusted 5-year composite outcomes were similar between CABG group and PCI group (12.1% [258/2264] versus 11.4% [218/2060]; P =0.52). After adjustment for baseline variables, PCI was associated with significantly higher risk of composite outcomes (adjusted hazard ratio: 1.21 [95% CI, 1.02-1.44]; P =0.03). The inferiority of PCI in 5-year composite outcome was significant in patients with CABG recommendation according to SYNTAX (Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery) score II (adjusted hazard ratio: 1.55 [95% CI, 1.14-2.09]; P =0.005) but not evident in patients with PCI or PCI/CABG equipoise recommendation according to SYNTAX score II (adjusted hazard ratio: 0.94 [95% CI, 0.75-1.17]; P =0.56). A similar risk of 5-year composite outcomes was observed between CABG and PCI with residual SYNTAX score <=8. /p> Conclusions: In this single-center retrospective study among patients with chronic total occlusion and multivessel disease, PCI was associated with higher risk of 5-year composite death, myocardial infarction, or stroke. * Percutaneous coronary intervention (PCI) has been used increasingly as an alternative means of revascularization for patients with chronic total occlusion and multivessel disease. * In patients with chronic total occlusion and multivessel disease, PCI was associated with higher risk of 5-year composite of death, myocardial infarction, and stroke compared with coronary artery bypass grafting (CABG). * This trend remained significant in patients with CABG recommendation according to SYNTAX (Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery) score II but was not evident in patients with PCI or PCI/CABG equipoise recommendation. * A similar risk of 5-year composite outcomes was observed between CABG and PCI with residual SYNTAX score <=8. /div> * CABG may still be the gold standard for patients with chronic total occlusion and multivessel disease; however, PCI with appropriate indication may be considered an alternative means of revascularization in the clinical setting. [ABSTRACT FROM AUTHOR]

Supplemental Digital Content is available in the text. Background: Left atrial (LA) myopathy is common in patients with heart failure and preserved ejection fraction and leads to the development of atrial fibrillation (AF). We investigated whether the likelihood of LA remodeling, LA dysfunction, altered hemodynamics, and risk for incident AF could be identified from a single 12-lead ECG using a novel artificial intelligence (AI)-enabled ECG analysis. Methods: Patients with heart failure and preserved ejection fraction (n=613) underwent AI-enabled ECG analysis, echocardiography, and cardiac catheterization. Individuals were grouped by AI-enabled ECG probability of contemporaneous AF, taken as an indicator of underlying LA myopathy. Results: Structural heart disease was more severe in patients with higher AI-probability of AF, with more left ventricular hypertrophy, larger LA volumes, and lower LA reservoir and booster strain. Cardiac filling pressures and pulmonary artery pressures were higher in patients with higher AI-probability, while cardiac output reserve was more impaired during exercise. Among patients with sinus rhythm and no prior AF, each 10% increase in AI-probability was associated with a 31% greater risk of developing new-onset AF (hazard ratio, 1.31 [95% CI, 1.20–1.42]; P <0.001). In the population as a whole, each 10% increase in AI-probability was associated with a 12% greater risk of death (hazard ratio, 1.12 [95% CI, 1.08–1.17]; P <0.001) during long-term follow-up, which was no longer significant after adjustments for baseline characteristics. Conclusions: A novel AI-enabled score derived from a single 12-lead ECG identifies the presence of underlying LA myopathy in patients with heart failure and preserved ejection fraction as evidenced by structural, functional, and hemodynamic abnormalities, as well as long-term risk for incident AF. Further research is required to determine the role of the AI-enabled ECG in the evaluation and care of patients with heart failure and preserved ejection fraction. [ABSTRACT FROM AUTHOR]

Abstract: The word "measurand" means "the quantity intended to be measured." The authors argue that health physicists should distinguish between measurands and measurement results because the former exist in the domain of theory, while the latter exist in the domain of reality in which we make measurements and observations. The authors demonstrate the importance of separating the quantities used in theory and those used in experiment, clearing up conceptual confusions in three examples of problems routinely encountered in health physics: (1) detection and quantification of radioactive material; (2) multiple definitions of "activity," and (3) the relationship between radiation and health effects. The first example looks into probabilities of various measurement results (mi) given the measurand (μ) in comparison with the inverse problem: determining probable values of the measurand (μ) based on observed measurement results (mi). The second example addresses the distinction between measurands and measurement results given two definitions of activity A provided by the International Commission on Radiation Units and Measurements. Additional consideration is given to use of N + 1 counts in (activity) calculations when we have observed N counts, which results from correctly stating and solving the inverse problem. This makes our measurement uncertainties more accurate and our detection decisions more reliable. The last example emphasizes how the observational results of epidemiology, animal experiments, and other radiation biology studies are used to estimate the probability of a particular cancer in an individual-a measurand that is not otherwise accessible to direct observation. Our measurement results, and our use of those results, are more easily understood when we understand the difference between a measurand and a measurement result and can choose the best calculational approach., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Health Physics Society.)