Specific patterns and potential risk factors to predict 3-year risk of death among non-cancer patients with advanced chronic kidney disease by machine learning.

Chronic kidney disease (CKD) is a major public health concern. But there are limited machine learning studies on non-cancer patients with advanced CKD, and the results of machine learning studies on cancer patients with CKD may not apply directly on non-cancer patients. We aimed to conduct a comprehensive investigation of risk factors for a 3-year risk of death among non-cancer advanced CKD patients with an estimated glomerular filtration rate < 60.0 mL/min/1.73m2 by several machine learning algorithms. In this retrospective cohort study, we collected data from in-hospital and emergency care patients from 2 hospitals in Taiwan from 2009 to 2019, including their international classification of disease at admission and laboratory data from the hospital's electronic medical records (EMRs). Several machine learning algorithms were used to analyze the potential impact and degree of influence of each factor on mortality and survival. Data from 2 hospitals in northern Taiwan were collected with 6565 enrolled patients. After data cleaning, 26 risk factors and approximately 3887 advanced CKD patients from Shuang Ho Hospital were used as the training set. The validation set contained 2299 patients from Taipei Medical University Hospital. Predictive variables, such as albumin, PT-INR, and age, were the top 3 significant risk factors with paramount influence on mortality prediction. In the receiver operating characteristic curve, the random forest had the highest values for accuracy above 0.80. MLP, and Adaboost had better performance on sensitivity and F1-score compared to other methods. Additionally, SVM with linear kernel function had the highest specificity of 0.9983, while its sensitivity and F1-score were poor. Logistic regression had the best performance, with an area under the curve of 0.8527. Evaluating Taiwanese advanced CKD patients' EMRs could provide physicians with a good approximation of the patients' 3-year risk of death by machine learning algorithms.

Atypical Presentation of Rocky Mountain Spotted Fever in Pregnancy.

Rocky Mountain spotted fever (RMSF) is a common tick-borne disease and can have variable presentation with potentially fatal outcomes when untreated. We describe an atypical presentation of RMSF in the third trimester. A 37-year-old multiparous woman at 31 0/7 weeks' gestation presented normotensive with headaches and fever but no rash or significant tick exposure. She was initially treated for atypical hemolysis, elevated liver enzymes, and low platelet count syndrome but further decompensated, requiring intensive care unit transfer, intubation, and emergent delivery. Doxycycline administration was associated with marked improvement with no significant sequalae to mother or infant. Later convalescent serologies were positive for RMSF. RMSF is a clinically challenging diagnosis in pregnancy. Given significant morbidity and mortality associated with delayed treatment, high suspicion in endemic areas is needed, and prompt antibiotic use with doxycycline should be administered.

Induced Abortion for Maternal Cardiac Indication: 2 Cases of Unintended Pregnancy With LVAD.

We present 2 cases of patients with left ventricular assist device who underwent an induced abortion in the first and second trimester, respectively. Comprehensive counseling is critical for this patient population, and close coordination of interdisciplinary teams is required in the setting of continuing pregnancy or medically indicated abortion.

The #IVF journey: content analysis of IVF videos on TikTok.

RESEARCH QUESTION: What patient populations and outcomes are depicted on IVF videos on the short-form video-sharing application 'TikTok'? DESIGN: This cross-sectional study investigated the 100 most-viewed videos utilizing the #IVF hashtag on TikTok. Only videos in English or Spanish were included in the analysis. An automated web-scraping platform was used to extract information from these videos. Standardized video coding was used to evaluate the featured subject(s), phase of care and IVF outcomes from the videos. RESULTS: Videos meeting the inclusion criteria (n=93) had 731 million views, 91 million likes and 893,000 shares. Patients' personal stories about IVF are over-represented relative to videos created by healthcare professionals. #IVF videos popular on TikTok disproportionately depict same-sex couples (38.1%), gestational carriers (14.0%), multiple gestations (60.0%) and live births (89.3%) relative to real-world data. Among the videos making scientific claims (n=16), nearly all were moderately to highly accurate (93.8%). Most videos had a positive (55.9%) or neutral (5.5%) tone towards IVF. CONCLUSIONS: Popular #IVF videos on TikTok contribute to public discourse about infertility, and highlight demographics that have traditionally been under-represented in health care. Videos rarely focused on health education or made informational claims, with low scores on measures of quality of information and actionability. This gap represents an opportunity for health providers and educators to create more engaging and educational content to reach patients considering IVF.

Autonomic complexity dynamically indexes affect regulation in everyday life.

Affect regulation often is disrupted in depression. Understanding biomarkers of affect regulation in ecologically valid contexts is critical for identifying moments when interventions can be delivered to improve regulation and may have utility for identifying which individuals are vulnerable to psychopathology. Autonomic complexity, which includes linear and nonlinear indices of heart rate variability, has been proposed as a novel marker of neurovisceral integration. However, it is not clear how autonomic complexity tracks with regulation in everyday life, and whether low complexity serves as a marker of related psychopathology. To measure regulation phenotypes with diminished influence of current symptoms, 37 young adults with remitted major depressive disorder (rMDD) and 28 healthy comparisons (HCs) completed ambulatory assessments of autonomic complexity and affect regulation across one week in everyday life. Multilevel models indicated that in HCs, but not rMDD, autonomic complexity fluctuated in response to regulation cues, increasing in response to reappraisal and distraction and decreasing in response to negative affect. Higher complexity across the week predicted greater everyday regulation success, whereas greater variability of complexity predicted lower (and less variable) negative affect, rumination, and mind-wandering. Results suggest that ambulatory assessment of autonomic complexity can passively index dynamic aspects of real-world affect and regulation, and that dynamic physiological reactivity to regulation is restricted in rMDD. These results demonstrate how intensive sampling of dynamic, nonlinear regulatory processes can advance our understanding of potential mechanisms underlying psychopathology. Such measurements might inform how to test interventions to enhance neurovisceral complexity and affect regulation success in real time. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Exploring the Potential Performance of Fibroscan for Predicting and Evaluating Metabolic Syndrome using a Feature Selected Strategy of Machine Learning.

Metabolic syndrome (MetS) includes several conditions that can increase an individual's predisposition to high-risk cardiovascular events, morbidity, and mortality. Non-alcoholic fatty liver disease (NAFLD) is a predominant cause of cirrhosis, which is a global indicator of liver transplantation and is considered the hepatic manifestation of MetS. FibroScan® provides an accurate and non-invasive method for assessing liver steatosis and fibrosis in patients with NAFLD, via a controlled attenuation parameter (CAP) and liver stiffness measurement (LSM or E) scores and has been widely used in current clinical practice. Several machine learning (ML) models with a recursive feature elimination (RFE) algorithm were applied to evaluate the importance of the CAP score. Analysis by ANOVA revealed that five symptoms at different CAP and E score levels were significant. All eight ML models had accuracy scores > 0.9, while treebags and random forest had the best kappa values (0.6439 and 0.6533, respectively). The CAP score was the most important variable in the seven ML models. Machine learning models with RFE demonstrated that using the CAP score to identify patients with MetS may be feasible. Thus, a combination of CAP scores and other significant biomarkers could be used for early detection in predicting MetS.

Management of Patients with Spine Tumors Strengthened by a Dedicated Multidisciplinary Spine Tumor Board: A 15-Year Single-Institutional Experience.

BACKGROUND: Patients with spine tumors frequently require timely, multistep, and multidisciplinary care. A Spine Tumor Board (STB) provides a consistent forum wherein diverse specialists can interact, facilitating complex coordinated care for these patients. This study aims to present a single, large academic center's STB experience specifically reviewing case diversity, recommendations, and quantifying growth over time. METHODS: All patient cases discussed at STB from May 2006 (STB inception) to May 2021 were evaluated. Collected data submitted by presenting physicians and formal documentation completed during the STB are summarized. RESULTS: A total of 4549 cases were reviewed by STB over the study period, representing 2618 unique patients. Over the course of the study, a 266% increase in number of cases presented per week was observed (4.1 to 15.0). Cases were presented by surgeons (74%), radiation oncologists (18%), neurologists (2%), and other specialists (6%). The most common pathologic diagnoses discussed were spinal metastases (n = 1832; 40%), intradural extramedullary tumors (n = 798; 18%), and primary glial tumors (n = 567; 12%). Treatment recommendations included surgery, radiation therapy, or systemic therapy for 1743 cases (38%), continued routine follow-up/expectant management for 1592 cases (35%), supplementary imaging to better clarify the diagnosis for 549 cases (12%), and variable tailored recommendations for the remainder of cases (18%). CONCLUSIONS: Care of patients with spine tumors is complex. We believe that the formation of a stand-alone STB is instrumental to accessing multidisciplinary input, enhancing confidence in management decisions for both patients and providers, assisting with care orchestration, and improving quality of care for patients with spine tumors.

Financial Toxicity in the Post-Health Reform Era.

The Patient Protection and Affordable Care Act (ACA), enacted in March 2010, was comprehensive health care reform legislation aimed to improve health care access and quality of care and curb health care-related costs. This review focuses on key provisions of the ACA and their impact on financial toxicity. We will focus our review on cancer care, because this is the most commonly studied disease process in respect to financial toxicity. Patients with cancer face rising expenditures and financial burden, which in turn impact quality of life, compliance to treatment, and survival outcomes. Health insurance expansion include dependent-coverage expansion, Medicaid expansion, and establishment of the Marketplace. Coverage reform focused on reducing financial barriers by limiting cost sharing. Payment reforms included new innovative payment and delivery systems to focus on improving outcomes and reducing costs. Challenges remain as efforts to reduce costs have led to the expansion of insurance plans, such as high-deductible health plans, that may ultimately worsen financial toxicity in cancer and high out-of-pocket costs for further diagnostic testing and procedures. Further research is necessary to evaluate the long-term impacts of the ACA provisions-and threats to the ACA-on outcomes and the costs accrued by patients.

TikTok, #IUD, and User Experience With Intrauterine Devices Reported on Social Media.

TikTok, a video-sharing application, offers a growing platform for contraception-related content. The top 100 videos tagged "#IUD" were compiled using a web-scraping application. User demographics and video content were analyzed by two independent reviewers, with a third to arbitrate differences. More videos had a negative tone (37.8%) about intrauterine devices (IUDs) than positive (19.4%), and 27.6% mentioned distrust of health care professionals. Of videos conveying patient experiences, all had a negative or ambiguous tone and 96.8% highlighted pain and other side effects related to IUDs. Videos scored low on information health quality (1.2/5 on DISCERN) and averaged 73.8% in understandability and 17.7% in actionability on PEMAT (Patient Education Materials Assessment Tool). #IUD videos on TikTok often portray negative experiences related to pain and informed consent.

Preliminary outcomes from a single-session, asynchronous, online stress and anxiety management workshop for college students.

OBJECTIVES: Self-guided, asynchronous, online interventions may provide college students access to evidence-based care, while mitigating barriers like limited hours of service. Thus, we examined the preliminary effectiveness of a 45-minute, self-guided, asynchronous, online, dialectical behavior therapy (DBT)-informed stress and anxiety management workshop. College undergraduates (n = 131) were randomized to either workshop (n = 65) or waitlist control (n = 66) conditions. METHODS: Participants in the workshop condition completed baseline measures of depression, stress, and anxiety, before completing the workshop. Participants in the waitlist control condition only completed the baseline measures. All participants were reassessed at 1-week follow-up. RESULTS: Controlling for baseline measures, students in the workshop condition experienced significantly less stress and greater self-efficacy to regulate stress and anxiety at follow-up, compared to waitlist controls. CONCLUSION: A 45-minute, self-guided, asynchronous, online DBT skills-informed stress and anxiety management workshop may reduce stress and improve self-efficacy to regulate stress and anxiety.

Preliminary outcomes from a single-session, asynchronous, online stress and anxiety management workshop for college students

Abstract Objectives Self-guided, asynchronous, online interventions may provide college students access to evidence-based care, while mitigating barriers like limited hours of service. Thus, we examined the preliminary effectiveness of a 45-minute, self-guided, asynchronous, online, dialectical behavior therapy (DBT)-informed stress and anxiety management workshop. College undergraduates (n = 131) were randomized to either workshop (n = 65) or waitlist control (n = 66) conditions. Methods Participants in the workshop condition completed baseline measures of depression, stress, and anxiety, before completing the workshop. Participants in the waitlist control condition only completed the baseline measures. All participants were reassessed at 1-week follow-up. Results Controlling for baseline measures, students in the workshop condition experienced significantly less stress and greater self-efficacy to regulate stress and anxiety at follow-up, compared to waitlist controls. Conclusion A 45-minute, self-guided, asynchronous, online DBT skills-informed stress and anxiety management workshop may reduce stress and improve self-efficacy to regulate stress and anxiety.

Enduring undetectable MRD and updated outcomes in relapsed/refractory CLL after fixed-duration venetoclax-rituximab.

The MURANO trial (A Study to Evaluate the Benefit of Venetoclax Plus Rituximab Compared With Bendamustine Plus Rituximab in Participants With Relapsed or Refractory Chronic Lymphocytic Leukemia [CLL]; ClinicalTrials.gov identifier #NCT02005471) reported superior progression-free survival (PFS) and overall survival (OS) with venetoclax-rituximab (VenR) vs bendamustine-rituximab (BR) in relapsed/refractory (R/R) CLL. Patients were randomized to 2 years of VenR (n = 194; rituximab for the first 6 months) or 6 months of BR (n = 195). Although undetectable minimal residual disease (uMRD) was achieved more often with VenR, the long-term implications of uMRD with this fixed-duration, chemotherapy-free regimen have not been explored. We report MRD kinetics and updated outcomes with 5 years' follow-up. Survival benefits with VenR vs BR were sustained (median PFS [95% confidence interval]: 53.6 [48.4, 57.0] vs 17.0 [15.5, 21.7] months, respectively, P < .0001; 5-year OS [95% confidence interval]: 82.1% [76.4, 87.8] vs 62.2% [54.8, 69.6], P < .0001). VenR was superior to BR, regardless of cytogenetic category. VenR-treated patients with uMRD at end of treatment (EOT; n = 83) had superior OS vs those with high-MRD+ (n = 12): 3-year post-EOT survival rates were 95.3% vs 72.9% (P = .039). In those with uMRD at EOT, median time to MRD conversion was 19.4 months. Of 47 patients with documented MRD conversion, 19 developed progressive disease (PD); median time from conversion to PD was 25.2 months. A population-based logistic growth model indicated slower MRD median doubling time post-EOT with VenR (93 days) vs BR (53 days; P = 1.2 × 10-7). No new safety signals were identified. Sustained survival, uMRD benefits, and durable responses support 2-year fixed-duration VenR treatment in R/R CLL.

Mobilization of innate and adaptive antitumor immune responses by the RNP-targeting antibody ATRC-101.

Immunotherapy approaches focusing on T cells have provided breakthroughs in treating solid tumors. However, there remains an opportunity to drive anticancer immune responses via other cell types, particularly myeloid cells. ATRC-101 was identified via a target-agnostic process evaluating antibodies produced by the plasmablast population of B cells in a patient with non-small cell lung cancer experiencing an antitumor immune response during treatment with checkpoint inhibitor therapy. Here, we describe the target, antitumor activity in preclinical models, and data supporting a mechanism of action of ATRC-101. Immunohistochemistry studies demonstrated tumor-selective binding of ATRC-101 to multiple nonautologous tumor tissues. In biochemical analyses, ATRC-101 appears to target an extracellular, tumor-specific ribonucleoprotein (RNP) complex. In syngeneic murine models, ATRC-101 demonstrated robust antitumor activity and evidence of immune memory following rechallenge of cured mice with fresh tumor cells. ATRC-101 increased the relative abundance of conventional dendritic cell (cDC) type 1 cells in the blood within 24 h of dosing, increased CD8+ T cells and natural killer cells in blood and tumor over time, decreased cDC type 2 cells in the blood, and decreased monocytic myeloid-derived suppressor cells in the tumor. Cellular stress, including that induced by chemotherapy, increased the amount of ATRC-101 target in tumor cells, and ATRC-101 combined with doxorubicin enhanced efficacy compared with either agent alone. Taken together, these data demonstrate that ATRC-101 drives tumor destruction in preclinical models by targeting a tumor-specific RNP complex leading to activation of innate and adaptive immune responses.

High-Fidelity Indirect Readout of Trapped-Ion Hyperfine Qubits.

We propose and demonstrate a protocol for high-fidelity indirect readout of trapped ion hyperfine qubits, where the state of a ^{9}Be^{+} qubit ion is mapped to a ^{25}Mg^{+} readout ion using laser-driven Raman transitions. By partitioning the ^{9}Be^{+} ground-state hyperfine manifold into two subspaces representing the two qubit states and choosing appropriate laser parameters, the protocol can be made robust to spontaneous photon scattering errors on the Raman transitions, enabling repetition for increased readout fidelity. We demonstrate combined readout and back-action errors for the two subspaces of 1.2_{-0.6}^{+1.1}×10^{-4} and 0_{-0}^{+1.9}×10^{-5} with 68% confidence while avoiding decoherence of spectator qubits due to stray resonant light that is inherent to direct fluorescence detection.

Decentering predicts attenuated perseverative thought and internalizing symptoms following stress exposure: A multi-level, multi-wave study.

While research identifies a growing list of risk factors for anxiety and depression, it is equally important to identify potential protective factors that may prevent or reduce vulnerability to developing internalizing psychopathology. We hypothesized that forms of perseverative thinking, such as rumination and worry, act as mechanisms linking negative life experiences and prospective symptoms of anxiety and depression. More specifically, we investigated whether decentering, the meta-cognitive capacity to adopt a distanced perspective toward one's thoughts and feelings, serves as a protective factor at various points along this mediational pathway. A sample of 181 undergraduate students were recruited and assessed at five time points over a 12-week period. Multilevel modeling indicated that decentering was associated with an attenuated impact of (1) negative events on prospective depressive symptoms; (2) negative events on prospective brooding, and (3) brooding, pondering and worry on prospective internalizing symptoms. Multilevel moderated mediation analyses provided partial support for the hypothesis that perseverative thinking would mediate the longitudinal associations between negative life events and internalizing symptoms, with decentering attenuating risk at several connections of the indirect pathways. The strongest support was provided for moderated mediation models in which decentering was associated with attenuated relationships between negative events, brooding, and symptoms of depression. This study is the first to elucidate the role of decentering as a protective factor against anxiety and depressive symptoms at different points in the path from stress to perseverative thought to internalizing symptoms. Decentering therefore may be a critical target for clinical intervention to promote resilience against anxiety and depression.

Resource-Efficient Dissipative Entanglement of Two Trapped-Ion Qubits.

We demonstrate a simplified method for dissipative generation of an entangled state of two trapped-ion qubits. Our implementation produces its target state faster and with higher fidelity than previous demonstrations of dissipative entanglement generation and eliminates the need for auxiliary ions. The entangled singlet state is generated in ∼7 ms with a fidelity of 0.949(4). The dominant source of infidelity is photon scattering. We discuss this error source and strategies for its mitigation.

Racial and ethnic disparities among donor oocyte banks in the United States.

OBJECTIVE: To determine whether racial and ethnic distributions of oocyte donors contributing to US oocyte banks differ from the demographics of US women and donor oocyte recipients. DESIGN: Cross-sectional study. SETTING: United States donor oocyte banks, US census, and fertility clinics reporting to the Society for Assisted Reproductive Technology Clinic Outcome Reporting System. PATIENTS: Oocyte donors from 12 banks, women aged 18-44 years based on the 2019 census, and US recipients of cryopreserved donor oocytes from 2012 to 2015. INTERVENTION: None. MAIN OUTCOME MEASURE: Proportions of donors identifying as each racial and ethnic group. RESULTS: Of the 1,574 oocyte donors, 678 (43.1%) identified as white compared with 54.8% of US women and 69.1% of donor oocyte recipients. Proportions of donors identifying as Hispanic or two or more races were larger than those of US women and donor oocyte recipients (Hispanic: 24.1% vs. 20.8%, and 24.1% vs. 8.8%, respectively; two or more races: 16.1% vs. 2.3%, and 16.1% vs. 0.5%, respectively). African American donors were underrepresented compared with US women (8.9% vs. 14.0%) and oocyte recipients (8.9% vs. 10.8%). Although the proportion of Asian donors was similar to that of US women (7.7% vs. 7.1%), Asian donors were underrepresented compared with donor oocyte recipients (7.7% vs. 10.6%). CONCLUSION: Racial and ethnic distribution of oocyte donors differs significantly from the demographics of US women and cryopreserved donor oocyte recipients. These data suggest a need for targeted recruitment of African American and Asian oocyte donors.