Clinical Care Research Research Articles

Neurofibromatosis Type 1 Has a Wide Spectrum of Growth Hormone Excess.

Overgrowth due to growth hormone (GH) excess affects approximately 10% of patients with neurofibromatosis type 1 (NF1) and optic pathway glioma (OPG). Our aim is to describe the clinical, biochemical, pathological, and genetic features of GH excess in a retrospective case series of 10 children and adults with NF1 referred to a tertiary care clinical research center. Six children (median age = 4 years, range of 3–5 years), one 14-year-old adolescent, and three adults (median age = 42 years, range of 29–52 years) were diagnosed with NF1 and GH excess. GH excess was confirmed by the failure to suppress GH (<1 ng/mL) on oral glucose tolerance test (OGTT, n = 9) and frequent overnight sampling of GH levels (n = 6). Genetic testing was ascertained through targeted or whole-exome sequencing (n = 9). Five patients (all children) had an OPG without any pituitary abnormality, three patients (one adolescent and two adults) had a pituitary lesion (two tumors, one suggestive hyperplasia) without an OPG, and two patients (one child and one adult) had a pituitary lesion (a pituitary tumor and suggestive hyperplasia, respectively) with a concomitant OPG. The serial overnight sampling of GH levels in six patients revealed abnormal overnight GH profiling. Two adult patients had a voluminous pituitary gland on pituitary imaging. One pituitary tumor from an adolescent patient who harbored a germline heterozygous p.Gln514Pro NF1 variant stained positive for GH and prolactin. One child who harbored a heterozygous truncating variant in exon 46 of NF1 had an OPG that, when compared to normal optic nerves, stained strongly for GPR101, an orphan G protein-coupled receptor causing GH excess in X-linked acrogigantism. We describe a series of patients with GH excess and NF1. Our findings show the variability in patterns of serial overnight GH secretion, somatotroph tumor or hyperplasia in some cases of NF1 and GH excess. Further studies are required to ascertain the link between NF1, GH excess and GPR101, which may aid in the characterization of the molecular underpinning of GH excess in NF1.

Focus on rural adolescent cannabis use and abuse: ignored epidemiologic trends, unique risks, long-term concerns, and hope.

Cannabis-related issues for adolescents and young adults are emerging from the shadow of rural opioid addiction and deaths. The rural pediatric population has multiple risk factors putting them at increased risk for adverse consequences with the expansion of cannabis legalization across the United States. Research in this area is rich but scattered across professional disciplines. Differences in demographics and cultures between rural and urban youth are gaining attention. Epidemiological factors relevant to rurality as a risk for cannabis and other substance use are considered for formulating clinical care, public policymakers, and future research. Race, culture, community stability, basic demographics of age, gender, educational status, and demands for more and better, accessible services for rural, nonmetropolitan areas comprise factors for consideration and are detailed. Research findings provide direction for policymakers and clinicians for prevention and intervention efforts to improve care for rural populations, validating and expanding upon insights gained to date.

Respect, justice and learning are limited when patients are deidentified data subjects.

IntroductionCritical for advancing a Learning Health System (LHS) in the U.S., a regulatory safe harbor for deidentified data reduces barriers to learning from care at scale while minimizing privacy risks. We examine deidentified data policy as a mechanism for synthesizing the ethical obligations underlying clinical care and human subjects research for an LHS which conceptually and practically integrates care and research, blurring the roles of patient and subject.MethodsFirst, we discuss respect for persons vis‐a‐vis the systemic secondary use of data and tissue collected in the fiduciary context of clinical care. We argue that, without traditional informed consent or duty to benefit the individual, deidentification may allow secondary use to supersede the primary purpose of care. Next, we consider the effectiveness of deidentification for minimizing harms via privacy protection and maximizing benefits via promoting learning and translational care. We find that deidentification is unable to fully protect privacy given the vastness of health data and current technology, yet it imposes limitations to learning and barriers for efficient translation. After that, we evaluate the impact of deidentification on distributive justice within an LHS ethical framework in which patients are obligated to contribute to learning and the system has a duty to translate knowledge into better care. Such a system may permit exacerbation of health disparities as it accelerates learning without mechanisms to ensure that individuals' contributions and benefits are fair and balanced.ResultsWe find that, despite its established advantages, system‐wide use of deidentification may be suboptimal for signaling respect, protecting privacy or promoting learning, and satisfying requirements of justice for patients and subjects.ConclusionsFinally, we highlight ethical, socioeconomic, technological and legal challenges and next steps, including a critical appreciation for novel approaches to realize an LHS that maximizes efficient, effective learning and just translation without the compromises of deidentification.

Clinical Evidence Generation During a Pandemic: Lessons Learned for Sustaining Progress.

Because of significant adaptations forced by the COVID-19 pandemic, resultant changes within health care delivery and clinical research introduced the potential for evaluation of novel evidence generation approaches in oncology. On July 26 and 27, 2021, the National Academies of Science, Engineering, and Medicine, National Cancer Policy Forum hosted a virtual workshop entitled “Cancer Care and Cancer Research in the Context of the COVID-19 Pandemic: A Workshop on Lessons Learned.” This workshop examined changes in cancer care and cancer research that occurred in response to the COVID-19 pandemic and considered lessons learned from that experience. The goal was to identify what changes could improve the delivery of high-quality cancer care and the conduct of cancer clinical trials in the postpandemic era, with an emphasis on health equity. How can we sustain the valuable lessons learned that might accelerate progress and enhance clinical evidence generation for patients and clinicians? In this overview, we discuss ways in which the COVID-19 experience has catalyzed research efficiencies as well as fostered a broader array of trial design and research methods that may facilitate improved cancer drug development during the pandemic and beyond.

Scoping review: bladder cancer in Nigeria – what are the gaps in clinical care and research?

ObjectivesThere are currently no national guidelines regarding bladder cancer treatment and clinical care pathways in Nigeria. The aim of this scoping review was to identify any gaps in the knowledge...

Disordered Eating and Body Dissatisfaction in Transgender and Gender-Expansive Adults: An Evaluation and Integration of the Gender Minority Stress and Resilience and Tripartite Influence Models

Transgender and gender-expansive (TGE) people, including transgender and nonbinary individuals, experience elevated rates of body dissatisfaction and disordered eating compared to cisgender individuals, but little is known about why. To address this research gap, we compared the ability of TGE-specific factors as proposed in the gender minority stress and resilience (GMSR) model, general psychological factors contained in the tripartite influence (TI) model, and an integration of these frameworks to explain body dissatisfaction and disordered eating among TGE individuals. Regression analyses were conducted to test the models’ abilities to explain experiences reported in a survey of 93 U.S. TGE adults, including 43 transgender women respondents (46.2%) and 31 transgender men respondents (33.3%). Participants were diverse with regard to age (M = 34.19, SD = 12.02) and ethnoracial background (e.g., 29.0% Hispanic/Latinx, 17.2% Black/African American, 6.5% American Indian/Alaska Native; 5.4% multiracial). Results demonstrated both models’ abilities to explain body dissatisfaction and disordered eating independently, except for the relationship between body dissatisfaction and the thinness-oriented TI model. An integration of the models better explained body dissatisfaction and disordered eating compared to either model alone. Notably, some findings did not align with the two frameworks, suggesting existing models may not adequately describe pathways through which disordered eating emerges in TGE populations. Specifically, body dissatisfaction showed no significant relationship with disordered eating and was not well explained by the TI model, and higher gender identity pride was related to greater disordered eating symptoms. Implications for clinical care and future research are discussed.

Malnutrition identification and management variability: An administrative database study of children with solid tumors.

BackgroundMalnutrition during cancer treatment increases treatment‐related morbidity and mortality. Our study better characterizes variability in malnutrition identification and treatment by examining nutrition‐related diagnoses and support for children with central nervous system (CNS) and non‐CNS solid tumors during therapy. We examined diagnosis of malnutrition, use of tube feeding or parenteral nutrition (PN), and appetite stimulants.MethodsWe retrospectively reviewed 0 to 21‐year‐old patients in the Pediatric Health Information System from 2015 to 2019. Patients were classified as having (1) billed malnutrition diagnosis, (2) malnutrition diagnosis or using PN and enteral nutrition (“functional malnutrition”), and (3) any previous criteria or prescribed appetite stimulants (“possible malnutrition”), as well as associated risk factors.ResultsAmong 13,375 unique patients, CNS tumors were most common (24.4%). Overall, 26.5% of patients had malnutrition diagnoses, 45.4% met functional malnutrition criteria, and 56.0% had possible malnutrition. Patients with adrenal tumors had highest billed, functional, and possible malnutrition (36.6%, 64.1%, and 69.4%, respectively) followed by CNS tumors (29.1%, 52.4%, and 64.1%). Patients with adrenal tumors had highest rates of PN use (47.4%) and those with CNS tumors had the highest tube feeding use (26.8%). Hospital admissions with malnutrition had a longer hospital length of stay (LOS) (6 vs 3 days, P < 0.0001), more emergency department admissions (24.4% vs 21.8%, P < 0.0001), and more opioid use (58.6% vs 41.4%, P < 0.0001).ConclusionsVariability in malnutrition diagnoses hinders clinical care and nutrition research in pediatric oncology. Improving disease‐specific recognition and treatment of malnutrition can target nutrition support, ensure appropriate reimbursement, and potentially improve outcomes for children with solid tumors.

Recognizing Racism in US Bioethics as the Subject of Bioethical Concern

Attending to racism and US bioethics raises the question of whether and how racism in bioethics has been the subject of bioethical scrutiny. Bioethics has certainly brought its analytical tools to bear on racist aspects of clinical care and biomedical research. But has bioethics studied racism in bioethics as its subject? A close examination of relevant reports, articles, and books in the US bioethics literature published in the early days of the field, pre-2000, shows mixed findings. In the 1970s, racism as a bioethical concern was variously nonexistent, vaguely implied, and powerfully examined and condemned. In the late 1980s/early to mid-1990s, racism was more frequently described and critiqued, often in the context of discussions about African American perspectives of biomedical ethics and inequities in health care. Understanding how racism in bioethics has been addressed as an ethical concern has consequences for the historical narratives told about the field, for antiracist bioethics work today, and for envisioning an antiracist future for bioethics.

Synchronization of Codification of Unspecified Schizophrenia Againts Back-Referral System of Mirit Public Health Center

Background: The disease classification system is a grouping of diseases following the International Statistical Classification of Diseases and Related Health Problems Tenth Revisions ICD-10. The coding application must be in accordance with ICD-10 to obtain a valid code in disease indexing, national, international reporting of morbidity and mortality, analysis of health care costs, and epidemiological and clinical research. The diagnosis of schizoaffective disorder is made if schizophrenia and affective disorder are symptoms based on the ICD-10 diagnostic criteria. This study aims to determine the synchronization of the codification of unspecified schizophrenia and determine the factors that influence it against the back-referral system at the Mirit Health Center. Method: This research is qualitative research with a descriptive approach. Respondents were four officers, i.e. one doctor, one medical record officer, one person holding a mental program, one pharmacy officer. The number of observed medical record documents was 96 data with research indicators of accuracy and completeness of the diagnosis code in patients referred from First Level Health Facilities (FKTP) to Advanced Health Facilities (FKTL). Result: The results showed 30 referrals, with nine referrals having the accuracy of the patient referral diagnosis code. The back-referral program (PRB) for mental illness at the Mirit Health Center, in collaboration with Mbah Marsio's mental health rehabilitation center, was carried out well. However, the implementation of the Chronic Disease Management program (Prolanis) for mental health was still not good. Conclusion: There are many unsynchronized codifications. It is recommended to conduct an evaluation where they communicate with each other about the patient's condition to supervise the implementation of Referback Patients, especially to specialists who write the back-referral form.

Neuroimaging of astroblastomas: A case series and systematic review.

Astroblastoma is a rare type of glial tumor, histologically classified into two types with different prognoses: high and low grade. We aimed to investigate the CT and MRI findings of astroblastomas by collecting studies with analyzable neuroimaging data and extracting the imaging features useful for tumor grading. We searched for reports of pathologically proven astroblastomas with analyzable neuroimaging data using PubMed, Scopus, and Embase. Sixty-five studies with 71 patients with astroblastomas met the criteria for a systematic review. We added eight patients from our hospital, resulting in a final study cohort of 79 patients. The proportion of high-grade tumors was compared in groups based on the morphology (typical and atypical) using Fisher's exact test. High- and low-grade tumors were 35/71 (49.3%) and 36/71 (50.7%), respectively. There was a significant difference in the proportion of high-grade tumors based on the tumor morphology (typical morphology: high-grade = 33/58 [56.9%] vs. atypical morphology, 2/13 [15.4%], p = .012).The reviews of neuroimaging findings were performed using the images included in each article. The articles had missing data due to the heterogeneity of the collected studies. Detailed neuroimaging features were clarified, including tumor location, margin status, morphology, CT attenuation, MRI signal intensity, and contrast enhancement pattern. The classification of tumor morphology may help predict the tumor's histological grade, contributing to clinical care and future oncologic research.

The simple observational critical care studies: estimations by students, nurses, and physicians of in-hospital and 6-month mortality

BackgroundPrognostic assessments of the mortality of critically ill patients are frequently performed in daily clinical practice and provide prognostic guidance in treatment decisions. In contrast to several sophisticated tools, prognostic estimations made by healthcare providers are always available and accessible, are performed daily, and might have an additive value to guide clinical decision-making. The aim of this study was to evaluate the accuracy of students’, nurses’, and physicians’ estimations and the association of their combined estimations with in-hospital mortality and 6-month follow-up.MethodsThe Simple Observational Critical Care Studies is a prospective observational single-center study in a tertiary teaching hospital in the Netherlands. All patients acutely admitted to the intensive care unit were included. Within 3 h of admission to the intensive care unit, a medical or nursing student, a nurse, and a physician independently predicted in-hospital and 6-month mortality. Logistic regression was used to assess the associations between predictions and the actual outcome; the area under the receiver operating characteristics (AUROC) was calculated to estimate the discriminative accuracy of the students, nurses, and physicians.ResultsIn 827 out of 1,010 patients, in-hospital mortality rates were predicted to be 11%, 15%, and 17% by medical students, nurses, and physicians, respectively. The estimations of students, nurses, and physicians were all associated with in-hospital mortality (OR 5.8, 95% CI [3.7, 9.2], OR 4.7, 95% CI [3.0, 7.3], and OR 7.7 95% CI [4.7, 12.8], respectively). Discriminative accuracy was moderate for all students, nurses, and physicians (between 0.58 and 0.68). When more estimations were of non-survival, the odds of non-survival increased (OR 2.4 95% CI [1.9, 3.1]) per additional estimate, AUROC 0.70 (0.65, 0.76). For 6-month mortality predictions, similar results were observed.ConclusionsBased on the initial examination, students, nurses, and physicians can only moderately predict in-hospital and 6-month mortality in critically ill patients. Combined estimations led to more accurate predictions and may serve as an example of the benefit of multidisciplinary clinical care and future research efforts.

How different domains of quality of life are associated with latent dimensions of mental health measured by GHQ-12

Background and objectivesA short form of the General Health Questionnaire (GHQ-12) is a useful screening instrument for assessing mental health. Furthermore, Quality of life (QoL) is a critical treatment outcome in many clinical and health care research settings. This study aimed to reassess the dimensionality of GHQ-12 using Multidimensional Graded Response Model (MGRM) and evaluate how its extracted dimensions are associated with the QoL's domains.MethodsIsfahan Cohort Study 2 (ICS2) is a population-based, ongoing prospective cohort study among adults aged 35 years and older who were free of cardiovascular diseases (CVDs) at the beginning of the study in 2013. A total of 1316 participants, all living in urban and rural areas of Isfahan and Najafabad, Iran was completed the GHQ-12 and WHO QoL-brief version at baseline. Five competing MGRMs with different latent structures were specified for GHQ-12. Factor scores derived from the best fitted model were used to associate with various domains of QoL. Results: The Three-Dimensional model for GHQ-12 was the best-fitted model explaining the Social Function (SF), Self Confidence (SC), and Anxiety/Depression (A/D) as three correlated yet different latent dimensions of mental health. Our findings in full adjusted multivariate regression models showed that a one-SD increase in dimensions of SC and SF was associated with a 38- to 48%-SD and 27- to 38%-SD increase in the domains scores of QoL, respectively. Moreover, for each one‐SD increase in score of A/D dimension, the domains scores of QoL decreased by 29- to 40%-SD. The highest to the lowest standardized coefficients for all latent dimensions of mental health were respectively related to the psychological, physical health, social relationships, and environmental condition domains of QoL. Furthermore, SC, A/D, and SF dimensions of GHQ-12 showed the highest to the lowest degree of association with all domains of QoL.ConclusionsOur findings confirm that the GHQ-12 as a multidimensional rather than unitary instrument measures distinct dimensions of mental health. Furthermore, all aspects of QoL changed when the intensity of latent dimensions of mental health increased. Moreover, the psychological domain of QoL is the most affected by all latent dimensions of mental health, followed by physical health, social relationships, and environmental condition domains. It seems that in an attempt to full recovery as assessed by improved QoL outcomes, treatment of clinical symptoms may not be sufficient. Identifying and differentiating the structures of mental health in each community as well as implementing intervention programs aimed at focusing on specific dimensions may help in the prevention of further deterioration of mental health and improved QoL in the community.

Risk Factors Associated With Nonfatal Opioid Overdose Leading to Intensive Care Unit Admission: A Cross-sectional Study.

BackgroundOpioid overdose (OD) and related deaths have significantly increased in the United States over the last 2 decades. Existing studies have mostly focused on demographic and clinical risk factors in noncritical care settings. Social and behavioral determinants of health (SBDH) are infrequently coded in the electronic health record (EHR) and usually buried in unstructured EHR notes, reflecting possible gaps in clinical care and observational research. Therefore, SBDH often receive less attention despite being important risk factors for OD. Natural language processing (NLP) can alleviate this problem.ObjectiveThe objectives of this study were two-fold: First, we examined the usefulness of NLP for SBDH extraction from unstructured EHR text, and second, for intensive care unit (ICU) admissions, we investigated risk factors including SBDH for nonfatal OD.MethodsWe performed a cross-sectional analysis of admission data from the EHR of patients in the ICU of Beth Israel Deaconess Medical Center between 2001 and 2012. We used patient admission data and International Classification of Diseases, Ninth Revision (ICD-9) diagnoses to extract demographics, nonfatal OD, SBDH, and other clinical variables. In addition to obtaining SBDH information from the ICD codes, an NLP model was developed to extract 6 SBDH variables from EHR notes, namely, housing insecurity, unemployment, social isolation, alcohol use, smoking, and illicit drug use. We adopted a sequential forward selection process to select relevant clinical variables. Multivariable logistic regression analysis was used to evaluate the associations with nonfatal OD, and relative risks were quantified as covariate-adjusted odds ratios (aOR).ResultsThe strongest association with nonfatal OD was found to be drug use disorder (aOR 8.17, 95% CI 5.44-12.27), followed by bipolar disorder (aOR 2.69, 95% CI 1.68-4.29). Among others, major depressive disorder (aOR 2.57, 95% CI 1.12-5.88), being on a Medicaid health insurance program (aOR 2.26, 95% CI 1.43-3.58), history of illicit drug use (aOR 2.09, 95% CI 1.15-3.79), and current use of illicit drugs (aOR 2.06, 95% CI 1.20-3.55) were strongly associated with increased risk of nonfatal OD. Conversely, Blacks (aOR 0.51, 95% CI 0.28-0.94), older age groups (40-64 years: aOR 0.65, 95% CI 0.44-0.96; >64 years: aOR 0.16, 95% CI 0.08-0.34) and those with tobacco use disorder (aOR 0.53, 95% CI 0.32-0.89) or alcohol use disorder (aOR 0.64, 95% CI 0.42-1.00) had decreased risk of nonfatal OD. Moreover, 99.82% of all SBDH information was identified by the NLP model, in contrast to only 0.18% identified by the ICD codes.ConclusionsThis is the first study to analyze the risk factors for nonfatal OD in an ICU setting using NLP-extracted SBDH from EHR notes. We found several risk factors associated with nonfatal OD including SBDH. SBDH are richly described in EHR notes, supporting the importance of integrating NLP-derived SBDH into OD risk assessment. More studies in ICU settings can help health care systems better understand and respond to the opioid epidemic.

Child Poverty and Health in the United States: Introduction and Executive Summary.

Child Poverty and Health in the United States: Introduction and Executive Summary.

Natural language processing enabling COVID-19 predictive analytics to support data-driven patient advising and pooled testing.

The COVID-19 (coronavirus disease 2019) pandemic response at the Medical University of South Carolina included virtual care visits for patients with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The telehealth system used for these visits only exports a text note to integrate with the electronic health record, but structured and coded information about COVID-19 (eg, exposure, risk factors, symptoms) was needed to support clinical care and early research as well as predictive analytics for data-driven patient advising and pooled testing. To capture COVID-19 information from multiple sources, a new data mart and a new natural language processing (NLP) application prototype were developed. The NLP application combined reused components with dictionaries and rules crafted by domain experts. It was deployed as a Web service for hourly processing of new data from patients assessed or treated for COVID-19. The extracted information was then used to develop algorithms predicting SARS-CoV-2 diagnostic test results based on symptoms and exposure information. The dedicated data mart and NLP application were developed and deployed in a mere 10-day sprint in March 2020. The NLP application was evaluated with good accuracy (85.8% recall and 81.5% precision). The SARS-CoV-2 testing predictive analytics algorithms were configured to provide patients with data-driven COVID-19 testing advices with a sensitivity of 81% to 92% and to enable pooled testing with a negative predictive value of 90% to 91%, reducing the required tests to about 63%. SARS-CoV-2 testing predictive analytics and NLP successfully enabled data-driven patient advising and pooled testing.

Elimination of the Race Coefficient from eGFR Calculation on Clinical Care and CKD Research Among a National US Veteran Cohort

Elimination of the Race Coefficient from eGFR Calculation on Clinical Care and CKD Research Among a National US Veteran Cohort

Make writing a daily habit: An evaluation of an educational intervention to improve writing self-efficacy among DNP students

Background and objective: Doctorate of Nursing Practice (DNP) students are trained to integrate both clinical care and evidence-based research in order to bring together science with application. However, the educational pathways in DNP programs can be problematic, especially with regards to scholarly writing. While several interventions have been utilized for DNP students, the results show that the intervention(s) used should be tailored to the specific student body being served. However, limited evidence exists regarding the effectiveness of tailored interventions on improving central concepts such as writing self-efficacy. Given these differences in the design and delivery of the DNP curricula, we created a tailored educational-writing curriculum for new DNP students at a medium-sized academic medical center in a Southern state.Methods: We assessed changes in writing self-efficacy over the three measurement intervals using linear mixed effects modeling to account for within-student clustering of writing self-efficacy scores over time.Results: Baseline scores of writing self-efficacy improved immediately after the workshop (Timepoint 2 – immediate post-test) and a full semester later (Timepoint 3 – semester post-test). However, we observed no statistically significant difference between Timepoint 2 (immediate post-test) and Timepoint 3 (semester post-test).Conclusions: We saw a significant benefit in writing self-efficacy among incoming DNP students from baseline scores. The tailored format and integration of real-life anecdotal feedback from faculty may have been fundamental to creating an increase in writing self-efficacy among students—a concept foundational to student, and possibly professional, nursing success.

Select controversies in the management of methicillin-resistant Staphylococcus aureus bacteremia: answers and remaining questions from recent evidence.

Methicillin-resistant Staphylococcus aureus (MRSA) bacteremia continues to cause significant morbidity and mortality despite advances in medical therapy. Vancomycin therapy remains the standard of care for most cases of MRSA bacteremia but has pharmacokinetic and pharmacodynamic limitations, dosing complications, and known toxicity. Welcomed clinical trials have recently addressed some of the controversies that plague this field, including optimization of vancomycin dosing and use of combination therapy. In this review, we discuss these trials and their implications for clinical care and future research.

Disrupted nighttime sleep and sleep instability in narcolepsy.

This review aimed to summarize current knowledge about disrupted nighttime sleep (DNS) and sleep instability in narcolepsy, including self-reported and objective assessments, potential causes of sleep instability, health consequences and functional burden, and management. One hundred two peer-reviewed publications from a PubMed search were included. DNS is a key symptom of narcolepsy but has received less attention than excessive daytime sleepiness and cataplexy. There has been a lack of clarity regarding the definition of DNS, as many sleep-related symptoms and conditions disrupt sleep quality in narcolepsy (eg, hallucinations, sleep paralysis, rapid eye movement sleep behavior disorder, nightmares, restless legs syndrome/periodic leg movements, nocturnal eating, sleep apnea, depression, anxiety). In addition, the intrinsic sleep instability of narcolepsy results in frequent spontaneous wakings and sleep stage transitions, contributing to DNS. Sleep instability likely emerges in the setting of orexin insufficiency/deficiency, but its exact pathophysiology remains unknown. DNS impairs quality of life among people with narcolepsy, and more research is needed to determine its contributions to cardiovascular risk. Multimodal treatment is appropriate for DNS management, including behavioral therapies, counseling on sleep hygiene, and/or medication. There is strong evidence showing improvement in self-reported sleep quality and objective sleep stability measures with sodium oxybate, but rigorous clinical trials with other pharmacotherapies are needed. Treatment may be complicated by comorbidities, concomitant medications, and mood disorders. DNS is a common symptom of narcolepsy deserving consideration in clinical care and future research. Maski K, Mignot E, Plazzi G, Dauvilliers Y. Disrupted nighttime sleep and sleep instability in narcolepsy. J Clin Sleep Med. 2022;18(1):289-304.

Incorporating Patient Narratives to Enhance Audiological Care and Clinical Research Outcomes.

Purpose The engagement of patients as key stakeholders in their experience of care processes is a critical component of quality improvement efforts for both clinical care and translational research. Increasingly, health care systems are soliciting input from patients on care processes and experiences through surveys, patient interviews, and patient video narratives. The purpose of this viewpoint article is twofold: (a) to describe the increasing role of patient narratives about their experiences with adverse health conditions to inform patient-centered research and quality improvement efforts and (b) to present three patient narratives that highlight the real-world impacts of hearing loss and tinnitus, the life enhancing impacts of aural rehabilitation, and the importance of prospective ototoxicity monitoring in individuals with complex health conditions. Conclusion Patient narratives provide individual patient perspectives that can be used to build awareness of the range of experiences and impact of hearing disorders, and to explore patient preferences for when and how to implement hearing-related clinical services.