Citations

Introduction Online symptom checkers are a way to address patient concerns and potentially offload a burdened healthcare system. However, safety outcomes of self-triage are unknown, so we reviewed triage recommendations and outcomes of our institution's depression symptom checker. Methods We examined endpoint recommendations and follow-up encounters seven days afterward during 2 December 2021 to 13 December 2022. Patients with an emergency department visit or hospitalization within seven days of self-triaging had a manual review of the electronic health record to determine if the visit was related to depression, suicidal ideation, or suicide attempt. Charts were reviewed for deaths within seven days of self-triage. Results There were 287 unique encounters from 263 unique patients. In 86.1% (247/287), the endpoint was an instruction to call nurse triage; in 3.1% of encounters (9/287), instruction was to seek emergency care. Only 20.2% (58/287) followed the recommendations given. Of the 229 patients that did not follow the endpoint recommendations, 121 (52.8%) had some type of follow-up within seven days. Nearly 11% (31/287) were triaged to endpoints not requiring urgent contact and 9.1% (26/287) to an endpoint that would not need any healthcare team input. No patients died in the study period. Conclusions Most patients did not follow the recommendations for follow-up care although ultimately most patients did receive care within seven days. Self-triage appears to appropriately sort patients with depressed mood to emergency care. On-line self-triaging tools for depression have the potential to safely offload some work from clinic personnel.

Abstract Introduction To further characterize the many struggles and unmet needs of people with narcolepsy (PWN), passive social listening was used to explore how PWN describe the condition using their own words. Methods MyNarcolepsyTeam is a social network where members can organically share their experiences living with narcolepsy with one another. Following an online survey, organic posts, comments, questions, and answers posted from January 2022 to present were analyzed. Results Of 110 survey respondents, 31% reported that the time from symptom onset to diagnosis was ≥10 years. Social listening highlighted both misdiagnoses (eg, depression) and “missed” diagnoses (eg, sleep apnea but not narcolepsy). Almost half (43%) of respondents reported pain as a comorbidity. Social listening revealed the burden of painful comorbidities (eg, fibromyalgia, migraines, neuropathy), which often lead to additional medications and further sleep disruption. While 90% of respondents reported excessive daytime sleepiness, 81% also reported sleep disturbances. Nighttime disruptions experienced by PWN included poor sleep quality, vivid dreams, frequent awakenings, sleep paralysis, and abnormal REM cycles. Structured routines helped improve sleep for some PWN. Additionally, 33% of respondents reporting cataplexy always experienced full body cataplexy; 21% always experienced localized cataplexy; 43% experienced a mix of both, with the remaining answering ‘not sure.’ Social listening highlighted the dangers of cataplexy, including falls/fractures. Organic conversations also brought to bear the full range of emotions that can trigger an attack – from laughter, to being startled, to feeling stressed. In total, 65% of respondents were taking ≥2 medications to treat daytime and/or nighttime narcolepsy symptoms. Organic conversations highlighted the challenges PWN experience managing complex treatment regimens in an attempt to cope with the full spectrum of narcolepsy symptoms. Conclusion Insight into how narcolepsy is experienced in patients’ own words and how patients try to mitigate their symptoms will help sleep specialists better understand the challenges and needs of PWN, which can lead to both faster diagnosis and more effective, individualized treatment. Support (if any) Avadel Pharmaceuticals

Abstract Introduction The definition of respiratory events has evolved over decades. The current American Academy of Sleep Medicine scoring manual recommends hypopneas be defined by a ≥ 30% airflow reduction with either ≥ 3% desaturation or an arousal, while the prior “recommended” criteria of a ≥ 30% airflow reduction and associated ≥ 4% oxygen desaturation (with no requirement of arousal) was changed to “optional”. Consequently, events previously characterized as a respiratory effort related arousal (RERA) may now be defined as a 3% hypopnea. We hypothesized that while the 3% apnea-hypopnea index (3%AHI) will be higher than the 4%AHI, the 3%AHI will be similar to the 4% respiratory disturbance index (4%RDI), and that the measurement of RERAs under 3% scoring criteria will be clinically insignificant. Methods We prospectively collected 70 consecutive in-lab polysomnography results in 4 adult age groups. We re-scored the respiratory events utilizing the 3% hypopnea rule, and compared the differences between 3% and 4% scoring criteria. Results Among the 70 studies (mean age 50, males 46%), the 3%AHI was significantly higher than the 4%AHI (+9.247 ± 1.161, p< 0.001). This was mainly due to increased hypopnea events (+10.313 ± 1.617, p< 0.001). The 3%AHI was significantly different from the 4%RDI (+7.096 ± 1.133, p< 0.001). There were no significant differences between the 3% and 4% RERA indices, with both values being minimal. Results were similar in both diagnostic and titration phases of testing. Conclusion As previously shown, utilizing the 3% hypopnea rule results in an increased AHI. Most of this difference is related to hypopneas with negligible influence of RERAs. This may lead to increased diagnosis and severity of sleep-disordered breathing in the adult population, and potentially be associated with payer ramifications. Our findings demonstrated negligible RERA indices on average with either rule, thus calling into question the clinical significance of this index in most patients. Support (if any) NA

Abstract Background Error analysis plays a crucial role in clinical concept extraction, a fundamental subtask within clinical natural language processing (NLP). The process typically involves a manual review of error types, such as contextual and linguistic factors contributing to their occurrence, and the identification of underlying causes to refine the NLP model and improve its performance. Conducting error analysis can be complex, requiring a combination of NLP expertise and domain-specific knowledge. Due to the high heterogeneity of electronic health record (EHR) settings across different institutions, challenges may arise when attempting to standardize and reproduce the error analysis process. Objectives This study aims to facilitate a collaborative effort to establish common definitions and taxonomies for capturing diverse error types, fostering community consensus on error analysis for clinical concept extraction tasks. Materials and Methods We iteratively developed and evaluated an error taxonomy based on existing literature, standards, real-world data, multisite case evaluations, and community feedback. The finalized taxonomy was released in both .dtd and .owl formats at the Open Health Natural Language Processing Consortium. The taxonomy is compatible with several different open-source annotation tools, including MAE, Brat, and MedTator. Results The resulting error taxonomy comprises 43 distinct error classes, organized into 6 error dimensions and 4 properties, including model type (symbolic and statistical machine learning), evaluation subject (model and human), evaluation level (patient, document, sentence, and concept), and annotation examples. Internal and external evaluations revealed strong variations in error types across methodological approaches, tasks, and EHR settings. Key points emerged from community feedback, including the need to enhancing clarity, generalizability, and usability of the taxonomy, along with dissemination strategies. Conclusion The proposed taxonomy can facilitate the acceleration and standardization of the error analysis process in multi-site settings, thus improving the provenance, interpretability, and portability of NLP models. Future researchers could explore the potential direction of developing automated or semi-automated methods to assist in the classification and standardization of error analysis.

Evidence from medicine and other fields has shown that gender diversity results in better decision making and outcomes. The incoming workforce of congenital heart specialists (especially in pediatric cardiology) appears to be more gender balanced, but past studies have shown many inequities. Gender‐associated differences in leadership positions, opportunities presented for academic advancement, and recognition for academic contributions to the field persist. In addition, compensation packages remain disparate if evaluated based on gender with equivalent experience and expertise. This review explores these inequities and has suggested individual and institutional changes that could be made to recruit and retain women, monitor the climate of the institution, and identify and eliminate bias in areas like salary and promotions.

PURPOSE The multicenter, open-label, randomized phase 2 NCI-9944 study ( NCT02595892 ) demonstrated that addition of ATR inhibitor (ATRi) berzosertib to gemcitabine increased progression-free survival (PFS) compared to gemcitabine alone (hazard ratio [HR]=0.57, one-sided log-rank P = .044, which met the one-sided significance level of 0.1 used for sample size calculation). METHODS We report here the final overall survival (OS) analysis and biomarker correlations (ATM expression by immunohistochemistry, mutational signature 3 and a genomic biomarker of replication stress) along with post-hoc exploratory analyses to adjust for crossover from gemcitabine to gemcitabine/berzosertib. RESULTS At the data cutoff of January 27, 2023 (>30 months of additional follow-up from the primary analysis), median OS was 59.4 weeks with gemcitabine/berzosertib versus 43.0 weeks with gemcitabine alone (HR 0.79, 90% CI 0.52 to 1.2, one-sided log-rank P = .18). An OS benefit with addition of berzosertib to gemcitabine was suggested in patients stratified into the platinum-free interval ≤3 months (N = 26) subgroup (HR, 0.48, 90% CI 0.22 to 1.01, one-sided log-rank P =.04) and in patients with ATM-negative/low (N = 24) tumors (HR, 0.50, 90% CI 0.23 to 1.08, one-sided log-rank P = .06). CONCLUSION The results of this follow-up analysis continue to support the promise of combined gemcitabine/ATRi therapy in platinum resistant ovarian cancer, an active area of investigation with several ongoing clinical trials.

Peripartum cardiomyopathy (PPCM) is an idiopathic form of pregnancy-induced heart failure associated with preeclampsia. Circulating factors in late pregnancy are thought to contribute to both diseases, suggesting a common underlying pathophysiological process. However, what drives this process remains unclear. Using serum proteomics, we identified the senescence-associated secretory phenotype (SASP), a marker of cellular senescence associated with biological aging, as the most highly up-regulated pathway in young women with PPCM or preeclampsia. Placentas from women with preeclampsia displayed multiple markers of amplified senescence and tissue aging, as well as overall increased gene expression of 28 circulating proteins that contributed to SASP pathway enrichment in serum samples from patients with preeclampsia or PPCM. The most highly expressed placental SASP factor, activin A, was associated with cardiac dysfunction or heart failure severity in women with preeclampsia or PPCM. In a murine model of PPCM induced by cardiomyocyte-specific deletion of the gene encoding peroxisome proliferator–activated receptor γ coactivator-1α, inhibiting activin A signaling in the early postpartum period with a monoclonal antibody to the activin type II receptor improved heart function. In addition, attenuating placental senescence with the senolytic compound fisetin in late pregnancy improved cardiac function in these animals. These findings link senescence biology to cardiac dysfunction in pregnancy and help to elucidate the pathogenesis underlying cardiovascular diseases of pregnancy.

Chronic lymphocytic leukemia (CLL) and small lymphocytic lymphoma (SLL) are essentially different manifestations of the same disease that are similarly managed. A number of molecular and cytogenetic variables with prognostic implications have been identified. Undetectable minimal residual disease at the end of treatment with chemoimmunotherapy or venetoclax-based combination regimens is an independent predictor of improved survival among patients with previously untreated or relapsed/refractory CLL/SLL. The selection of treatment is based on the disease stage, presence or absence of del(17p) or TP53 mutation, immunoglobulin heavy chain variable region mutation status, patient age, performance status, comorbid conditions, and the agent’s toxicity profile. This manuscript discusses the recommendations outlined in the NCCN Guidelines for the diagnosis and management of patients with CLL/SLL.

Background: Pancreatic adenocarcinoma (PC) is a highly lethal malignancy with a survival rate of only 12%. Surveillance is recommended for high-risk individuals (HRIs), but it is not widely adopted. To address this unmet clinical need and drive early diagnosis research, we established the Pancreatic Cancer Early Detection (PRECEDE) Consortium. Methods: PRECEDE is a multi-institutional international collaboration that has undertaken an observational prospective cohort study. Individuals (aged 18–90 years) are enrolled into 1 of 7 cohorts based on family history and pathogenic germline variant (PGV) status. From April 1, 2020, to November 21, 2022, a total of 3,402 participants were enrolled in 1 of 7 study cohorts, with 1,759 (51.7%) meeting criteria for the highest-risk cohort (Cohort 1). Cohort 1 HRIs underwent germline testing and pancreas imaging by MRI/MR-cholangiopancreatography or endoscopic ultrasound. Results: A total of 1,400 participants in Cohort 1 (79.6%) had completed baseline imaging and were subclassified into 3 groups based on familial PC (FPC; n=670), a PGV and FPC (PGV+/FPC+; n=115), and a PGV with a pedigree that does not meet FPC criteria (PGV+/FPC–; n=615). One HRI was diagnosed with stage IIB PC on study entry, and 35.1% of HRIs harbored pancreatic cysts. Increasing age (odds ratio, 1.05; P <.001) and FPC group assignment (odds ratio, 1.57; P <.001; relative to PGV+/FPC–) were independent predictors of harboring a pancreatic cyst. Conclusions: PRECEDE provides infrastructure support to increase access to clinical surveillance for HRIs worldwide, while aiming to drive early PC detection advancements through longitudinal standardized clinical data, imaging, and biospecimen captures. Increased cyst prevalence in HRIs with FPC suggests that FPC may infer distinct biological processes. To enable the development of PC surveillance approaches better tailored to risk category, we recommend adoption of subclassification of HRIs into FPC, PGV+/FPC+, and PGV+/FPC– risk groups by surveillance protocols.

AbstractIntroductionShared decision‐making (SDM) is a method of care by which patients and clinicians work together to co‐create a plan of care. Electronic health record (EHR) integration of SDM tools may increase adoption of SDM. We conducted a “lightweight” integration of a freely available electronic SDM tool, CV Prevention Choice, within the EHRs of three healthcare systems. Here, we report how the healthcare systems collaborated to achieve integration.MethodsThis work was conducted as part of a stepped wedge randomized pragmatic trial. CV Prevention Choice was developed using guidelines for HTML5‐based web applications. Healthcare systems integrated the tool in their EHR using documentation the study team developed and refined with lessons learned after each system integrated the electronic SDM tool into their EHR. CV Prevention Choice integration populates the tool with individual patient data locally without sending protected health information between the EHR and the web. Data abstraction and secure transfer systems were developed to manage data collection to assess tool implementation and effectiveness outcomes.ResultsTime to integrate CV Prevention Choice in the EHR was 12.1 weeks for the first system, 10.4 weeks for the second, and 9.7 weeks for the third. One system required two 1‐hour meetings with study team members and two healthcare systems required a single 1‐hour meeting. Healthcare system information technology teams collaborated by sharing information and offering improvements to documentation. Challenges included tracking CV Prevention Choice use for reporting and capture of combination medications. Data abstraction required refinements to address differences in how each healthcare system captured data elements.ConclusionTargeted documentation on tool features and resource mapping supported collaboration of IT teams across healthcare systems, enabling them to integrate a web‐based SDM tool with little additional research team effort or oversight. Their collaboration helped overcome difficulties integrating the web application and address challenges to data harmonization for trial outcome analyses.