Genome-Wide Association Study of Treatment-Resistant Depression: Shared Biology With Metabolic Traits.

OBJECTIVE: Treatment-resistant depression (TRD) occurs in roughly one-third of all individuals with major depressive disorder (MDD). Although research has suggested a significant common variant genetic component of liability to TRD, with heritability estimated at 8% when compared with non-treatment-resistant MDD, no replicated genetic loci have been identified, and the genetic architecture of TRD remains unclear. A key barrier to this work has been the paucity of adequately powered cohorts for investigation, largely because of the challenge in prospectively investigating this phenotype. The objective of this study was to perform a well-powered genetic study of TRD. METHODS: Using receipt of electroconvulsive therapy (ECT) as a surrogate for TRD, the authors applied standard machine learning methods to electronic health record data to derive predicted probabilities of receiving ECT. These probabilities were then applied as a quantitative trait in a genome-wide association study of 154,433 genotyped patients across four large biobanks. RESULTS: Heritability estimates ranged from 2% to 4.2%, and significant genetic overlap was observed with cognition, attention deficit hyperactivity disorder, schizophrenia, alcohol and smoking traits, and body mass index. Two genome-wide significant loci were identified, both previously implicated in metabolic traits, suggesting shared biology and potential pharmacological implications. CONCLUSIONS: This work provides support for the utility of estimation of disease probability for genomic investigation and provides insights into the genetic architecture and biology of TRD.

Genetics Visit Uptake Among Individuals Receiving Clinically Actionable Genomic Screening Results.

Importance: Screening unselected populations for clinically actionable genetic disease risk can improve ascertainment and facilitate risk management. Genetics visits may encourage at-risk individuals to perform recommended management, but little has been reported on genetics visit completion or factors associated with completion in genomic screening programs. Objective: To identify factors associated with postdisclosure genetics visits in a genomic screening cohort. Design, Setting, and Participants: This was a cohort study of biobank data in a health care system in central Pennsylvania. Participants' exome sequence data were reviewed for pathogenic or likely pathogenic (P/LP) results in all genes on the American College of Medical Genetics and Genomics Secondary Findings list. Clinically confirmed results were disclosed by phone and letter. Participants included adult MyCode biobank participants who received P/LP results between July 2015 and November 2019. Data were analyzed from May 2021 to March 2022. Exposure: Clinically confirmed P/LP result disclosed by phone or letter. Main Outcomes and Measures: Completion of genetics visit in which the result was discussed and variables associated with completion were assessed by electronic health record (EHR) review. Results: Among a total of 1160 participants (703 [60.6%] female; median [IQR] age, 57.0 [42.1-68.5] years), fewer than half of participants (551 of 1160 [47.5%]) completed a genetics visit. Younger age (odds ratio [OR] for age 18-40 years, 2.98; 95% CI, 1.40-6.53; OR for age 41-65 years, 2.36; 95% CI, 1.22-4.74; OR for age 66-80 years, 2.60; 95% CI, 1.41-4.98 vs age ≥81 years); female sex (OR, 1.49; 95% CI, 1.14-1.96); being married (OR, 1.74; 95% CI, 1.23-2.47) or divorced (OR, 1.80; 95% CI, 1.11-2.91); lower Charlson comorbidity index (OR for score of 0-2, 1.76; 95% CI, 1.16-2.68; OR for score of 3-4, 1.73; 95% CI, 1.18-2.54 vs score of ≥5); EHR patient portal use (OR, 1.42; 95% CI, 1.06-1.89); living closer to a genetics clinic (OR, 1.64; 95% CI, 1.14-2.36 for <8.9 miles vs >20.1 miles); successful results disclosure (OR for disclosure by genetic counselor, 16.32; 95% CI, 8.16-37.45; OR for disclosure by research assistant, 20.30; 95% CI, 10.25-46.31 vs unsuccessful phone disclosure); and having a hereditary cancer result (OR, 2.13; 95% CI, 1.28-3.58 vs other disease risk) were significantly associated with higher rates of genetics visit completion. Preference to follow up with primary care was the most common reported reason for declining a genetics visit (68 of 152 patients [44.7%]). Conclusions and Relevance: This cohort study of a biobank-based population genomic screening program suggests that targeted patient engagement, improving multidisciplinary coordination, and reducing barriers to follow-up care may be necessary for enhancing genetics visit uptake.

Comparison of Blood Concentration and Weight-Based Heparin and Protamine Dosing Strategies for Cardiopulmonary Bypass: A Systematic Review and Meta-Analysis.

BACKGROUND:  The conventional method of heparin and protamine management during cardiopulmonary bypass (CPB) is based on total body weight which fails to account for the heterogeneous response to heparin in each patient. On the other hand, the literature is inconclusive on whether individualized anticoagulation management based on real-time blood heparin concentration improves post-CBP outcomes. METHODS:  We searched databases of Medline, Excerpta Medica dataBASE (EMBASE), PubMed, Cumulative Index to Nursing and Allied Health Literature (CINHL), and Google Scholar, recruiting randomized controlled trials (RCTs) and prospective studies comparing the outcomes of dosing heparin and/or protamine based on measured heparin concentration versus patient's total body weight for CPB. Random effects meta-analyses and meta-regression were conducted to compare the outcome profiles. Primary endpoints include postoperative blood loss and the correlation with heparin and protamine doses, the reversal protamine and loading heparin dose ratio; secondary endpoints included postoperative platelet counts, antithrombin III, fibrinogen levels, activated prothrombin time (aPTT), incidences of heparin rebound, and re-exploration of chest wound for bleeding. RESULTS:  Twenty-six studies, including 22 RCTs and four prospective cohort studies involving 3,810 patients, were included. Compared to body weight-based dosing, patients of individualized, heparin concentration-based group had significantly lower postoperative blood loss (mean difference (MD)=49.51 mL, 95% confidence interval (CI): 5.33-93.71), lower protamine-to-heparin dosing ratio (MD=-0.20, 95% CI: -0.32 ~ -0.12), and higher early postoperative platelet counts (MD=8.83, 95% CI: 2.07-15.59). The total heparin doses and protamine reversal were identified as predictors of postoperative blood loss by meta-regression. CONCLUSIONS:  There was a significant correlation between the doses of heparin and protamine with postoperative blood loss; therefore, précised dosing of both could be critical for reducing bleeding and transfusion requirements. Data from the enrolled studies indicated that compared to conventional weight-based dosing, individualized, blood concentration-based heparin and protamine dosing may have outcome benefits reducing postoperative blood loss. The dosing calculation of heparin based on the assumption of a one-compartment pharmacokinetic/pharmacodynamic (PK/PD) model and linear relationship between the calculated dose and blood heparin concentration may be inaccurate. With the recent advancement of the technologies of machine learning, individualized, precision management of anticoagulation for CPB may be possible in the near future.

Using implementation science to develop a familial hypercholesterolemia screening program in primary care: The CARE-FH study.

BACKGROUND: We designed the Collaborative Approach to Reach Everyone with Familial Hypercholesterolemia (CARE-FH) clinical trial to improve FH screening in primary care and facilitate guideline-based care. OBJECTIVE: The goal was to incorporate perspectives from end-users (healthcare system leaders, primary care clinicians, cardiologists, genetic counselors, nurses, and clinic staff) and improve translation of screening guidance into practice. METHODS: We partnered with end-users to sequentially define the current state of FH screening, assess acceptability, feasibility, and appropriateness of implementing an FH screening program, and select clinically actionable strategies at the patient-, clinician-, and system-level to be deployed as a package in the CARE-FH clinical trial. Methods informed by implementation science and human centered design included: contextual inquiries, surveys, and deliberative engagement sessions. RESULTS: Screening for FH occurred rarely in primary care, and then only after a cardiovascular event or sometimes due to a family history of high cholesterol or early heart attack. Surveys suggested FH screening in primary care was acceptable, appropriate, and feasible. Reported and observed barriers to screening include insufficient time at patient encounters to screen, cost and convenience of testing for patients, and knowledge regarding causes of dyslipidemia. Facilitators included clear guidance on screening criteria and new therapies to treat FH. These results led to the development of multilevel strategies that were presented to end-users, modified, and then pilot tested in one primary care clinic. CONCLUSIONS: A refined implementation strategy package for FH screening was created with a goal of improving FH awareness, identification, and initiation of guideline-based care. CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/study/NCT05284513?id=NCT05284513&rank=1 Unique Identifier: NCT05284513.

Development and multi-site external validation of a generalizable risk prediction model for bipolar disorder.

Bipolar disorder is a leading contributor to disability, premature mortality, and suicide. Early identification of risk for bipolar disorder using generalizable predictive models trained on diverse cohorts around the United States could improve targeted assessment of high risk individuals, reduce misdiagnosis, and improve the allocation of limited mental health resources. This observational case-control study intended to develop and validate generalizable predictive models of bipolar disorder as part of the multisite, multinational PsycheMERGE Network across diverse and large biobanks with linked electronic health records (EHRs) from three academic medical centers: in the Northeast (Massachusetts General Brigham), the Mid-Atlantic (Geisinger) and the Mid-South (Vanderbilt University Medical Center). Predictive models were developed and valid with multiple algorithms at each study site: random forests, gradient boosting machines, penalized regression, including stacked ensemble learning algorithms combining them. Predictors were limited to widely available EHR-based features agnostic to a common data model including demographics, diagnostic codes, and medications. The main study outcome was bipolar disorder diagnosis as defined by the International Cohort Collection for Bipolar Disorder, 2015. In total, the study included records for 3,529,569 patients including 12,533 cases (0.3%) of bipolar disorder. After internal and external validation, algorithms demonstrated optimal performance in their respective development sites. The stacked ensemble achieved the best combination of overall discrimination (AUC = 0.82-0.87) and calibration performance with positive predictive values above 5% in the highest risk quantiles at all three study sites. In conclusion, generalizable predictive models of risk for bipolar disorder can be feasibly developed across diverse sites to enable precision medicine. Comparison of a range of machine learning methods indicated that an ensemble approach provides the best performance overall but required local retraining. These models will be disseminated via the PsycheMERGE Network website.

The Phenotypic Spectrum of COL4A3 Heterozygotes.

Introduction: The penetrance and phenotypic spectrum of autosomal dominant Alport Syndrome (ADAS), affecting 1 in 106, remains understudied. Methods: Using data from 174,418 participants in the Geisinger MyCode/DiscovEHR study, an unselected health system-based cohort with whole exome sequencing, we identified 403 participants who were heterozygous for likely pathogenic COL4A3 variants. Phenotypic data was evaluated using International Classification of Diseases (ICD) codes, laboratory data, and chart review. To evaluate the phenotypic spectrum of genetically-determined ADAS, we matched COL4A3 heterozygotes 1:5 to nonheterozygotes using propensity scores by demographics, hypertension, diabetes, and nephrolithiasis. Results: COL4A3 heterozygotes were at significantly increased risks of hematuria, decreased estimated glomerular filtration rate (eGFR), albuminuria, and kidney failure (P < 0.05 for all comparisons) but not bilateral sensorineural hearing loss (P = 0.9). Phenotypic severity was more severe for collagenous domain glycine missense variants than protein truncating variants (PTVs). For example, patients with Gly695Arg (n = 161) had markedly increased risk of dipstick hematuria (odds ratio [OR] 9.50; 95% confidence interval [CI]: 6.32, 14.28) and kidney failure (OR 7.02; 95% CI: 3.48, 14.16) whereas those with PTVs (n = 119) had moderately increased risks of dipstick hematuria (OR 1.64; 95% CI: 1.03, 2.59) and kidney failure (OR 3.44; 95% CI: 1.28, 9.22). Less than a third of patients had albuminuria screening completed, and fewer than 1 of 3 were taking inhibitors of the renin-angiotensin-aldosterone system. Conclusion: This study demonstrates a wide spectrum of phenotypic severity in ADAS due to COL4A3 with phenotypic variability by genotype. Future studies are needed to evaluate the impact of earlier diagnosis, appropriate evaluation, and treatment of ADAS.

Association Between Psychiatric Polygenic Scores, Healthcare Utilization and Comorbidity Burden.

Purpose: To estimate the association of psychiatric polygenic scores with healthcare utilization and comorbidity burden. Methods: Observational cohort study (N = 118,882) of adolescent and adult biobank participants with linked electronic health records (EHRs) from three diverse study sites; (Massachusetts General Brigham, Vanderbilt University Medical Center, Geisinger). Polygenic scores (PGS) were derived from the largest available GWAS of major depressive depression, bipolar disorder, and schizophrenia at the time of analysis. Negative binomial regression models were used to estimate the association between each psychiatric PGS and healthcare utilization and comorbidity burden. Healthcare utilization was measured as frequency of emergency department (ED), inpatient (IP), and outpatient (OP) visits. Comorbidity burden was defined by the Elixhauser Comorbidity Index and the Charlson Comorbidity Index. Results: Participants had a median follow-up duration of 12 years in the EHR. Individuals in the top decile of polygenic score for major depressive disorder had significantly more ED visits (RR=1.22, 95% CI; 1.17, 1.29) compared to those the lowest decile. Increases were also observed with IP and comorbidity burden. Among those diagnosed with depression and in the highest decile of the PGS, there was an increase in all utilization types (ED: RR=1.56, 95% CI 1.41, 1.72; OP: RR=1.16, 95% CI 1.08, 1.24; IP: RR=1.23, 95% CI 1.12, 1.36) post-diagnosis. No clinically significant results were observed with bipolar and schizophrenia polygenic scores. Conclusions: Polygenic score for depression is modestly associated with increased healthcare resource utilization and comorbidity burden, in the absence of diagnosis. Following a diagnosis of depression, the PGS was associated with further increases in healthcare utilization. These findings suggest that depression genetic risk is associated with utilization and burden of chronic disease in real-world settings.

Sensitivity and Specificity of Examination Maneuvers for Carpal Tunnel Syndrome: A Meta-Analysis.

Our purpose was to assess the diagnostic validity (sensitivity (Sn) and specificity (Sp)) of physical examination maneuvers for carpal tunnel syndrome (CTS). This meta-analysis utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Studies assessing exam maneuvers (including components of the CTS-6) for CTS were identified in MEDLINE (Medical Literature Analysis and Retrieval System Online) and Embase (Excerpta Medica Database) databases. Assessed maneuvers assessed included: Phalen's test, Tinel's sign, Durkan test, scratch-collapse test, Semmes-Weinstein monofilament (SWM), and static 2-point discrimination (2PD) test. Data extracted included: article name, total number of subjects/hands, type of exam, and exam Sn/Sp. Forest plots were presented to display the estimated Sn/Sp and boxplots were used to demonstrate the locality, spread, and skewness of the Sn/Sp through the quartiles. After screening 570 articles, 67 articles involving 8924 hands were included. Forty-eight articles assessed Phalen's test, 45 assessed Tinel's sign, 21 assessed the Durkan test, seven assessed the scratch-collapse test, 11 assessed SWM, and six assessed the static 2PD test. Phalen's test demonstrated the greatest median Sn (0.70, (Q1, Q3): (0.51, 0.85)), followed by the Durkan test (0.67, (Q1, Q3): (0.46, 0.82)). 2PD demonstrated the highest median Sp (0.90, (Q1, Q3): (0.88, 0.90)), followed by SWM (0.85, (Q1, Q3): (0.51, 0.89)). There is considerable variability with respect to the validity of physical exam tests used in the diagnosis of CTS. Upper-extremity surgeons should be aware of inherent limitations for individual exam maneuvers. In the absence of a uniformly accepted diagnostic gold standard, a combination of exams, along with pertinent patient history, should guide the diagnosis of CTS.

The Phenotypic Spectrum of COL4A3 Heterozygotes.

Most data on Alport Syndrome (AS) due to COL4A3 are limited to families with autosomal recessive AS or severe manifestations such as focal segmental glomerulosclerosis (FSGS). Using data from 174,418 participants in the Geisinger MyCode/DiscovEHR study, an unselected health system-based cohort with whole exome sequencing, we identified 403 participants (0.2%) who were heterozygous for likely pathogenic COL4A3 variants. Phenotypic data was evaluated using International Classification of Diseases (ICD) codes, laboratory data, and chart review. To evaluate the phenotypic spectrum of genetically-determined autosomal dominant AS, we matched COL4A3 heterozygotes 1:5 to non-heterozygotes using propensity scores by demographics, hypertension, diabetes, and nephrolithiasis. COL4A3 heterozygotes were at significantly increased risks of hematuria, decreased estimated glomerular filtration rate (eGFR), albuminuria, and end-stage kidney disease (ESKD) (p<0.05 for all comparisons) but not bilateral sensorineural hearing loss (p=0.9). Phenotypic severity tended to be more severe among patients with glycine missense variants located within the collagenous domain. For example, patients with Gly695Arg (n=161) had markedly increased risk of dipstick hematuria (OR 9.47, 95% CI: 6.30, 14.22) and ESKD diagnosis (OR 7.01, 95% CI: 3.48, 14.12) whereas those with PTVs (n=119) had moderately increased risks of dipstick hematuria (OR 1.63, 95% CI: 1.03, 2.58) and ESKD diagnosis (OR 3.43, 95% CI: 1.28, 9.19). Less than a third of patients had albuminuria screening completed, and fewer than 1/3 were taking inhibitors of the renin-angiotensin-aldosterone system (RAASi). Future studies are needed to evaluate the impact of earlier diagnosis, appropriate evaluation, and treatment of ADAS.

Diagnostic Yield of Exome Sequencing in Cerebral Palsy and Implications for Genetic Testing Guidelines: A Systematic Review and Meta-analysis.

Importance: Exome sequencing is a first-tier diagnostic test for individuals with neurodevelopmental disorders, including intellectual disability/developmental delay and autism spectrum disorder; however, this recommendation does not include cerebral palsy. Objective: To evaluate if the diagnostic yield of exome or genome sequencing in cerebral palsy is similar to that of other neurodevelopmental disorders. Data Sources: The study team searched PubMed for studies published between 2013 and 2022 using cerebral palsy and genetic testing terms. Data were analyzed during March 2022. Study Selection: Studies performing exome or genome sequencing in at least 10 participants with cerebral palsy were included. Studies with fewer than 10 individuals and studies reporting variants detected by other genetic tests were excluded. Consensus review was performed. The initial search identified 148 studies, of which 13 met inclusion criteria. Data Extraction and Synthesis: Data were extracted by 2 investigators and pooled using a random-effects meta-analysis. Incidence rates with corresponding 95% CIs and prediction intervals were calculated. Publication bias was evaluated by the Egger test. Variability between included studies was assessed via heterogeneity tests using the I2 statistic. Main Outcomes and Measures: The primary outcome was the pooled diagnostic yield (rate of pathogenic/likely pathogenic variants) across studies. Subgroup analyses were performed based on population age and on the use of exclusion criteria for patient selection. Results: Thirteen studies were included consisting of 2612 individuals with cerebral palsy. The overall diagnostic yield was 31.1% (95% CI, 24.2%-38.6%; I2 = 91%). The yield was higher in pediatric populations (34.8%; 95% CI, 28.3%-41.5%) than adult populations (26.9%; 95% CI, 1.2%-68.8%) and higher among studies that used exclusion criteria for patient selection (42.1%; 95% CI, 36.0%-48.2%) than those that did not (20.7%; 95% CI, 12.3%-30.5%). Conclusions and Relevance: In this systematic review and meta-analysis, the genetic diagnostic yield in cerebral palsy was similar to that of other neurodevelopmental disorders for which exome sequencing is recommended as standard of care. Data from this meta-analysis provide evidence to support the inclusion of cerebral palsy in the current recommendation of exome sequencing in the diagnostic evaluation of individuals with neurodevelopmental disorders.

Development and Multi-Site External Validation of a Generalizable Risk Prediction Model for Bipolar Disorder.

Bipolar disorder is a leading contributor to disability, premature mortality, and suicide. Early identification of risk for bipolar disorder using generalizable predictive models trained on diverse cohorts around the United States could improve targeted assessment of high risk individuals, reduce misdiagnosis, and improve the allocation of limited mental health resources. This observational case-control study intended to develop and validate generalizable predictive models of bipolar disorder as part of the multisite, multinational PsycheMERGE Consortium across diverse and large biobanks with linked electronic health records (EHRs) from three academic medical centers: in the Northeast (Massachusetts General Brigham), the Mid-Atlantic (Geisinger) and the Mid-South (Vanderbilt University Medical Center). Predictive models were developed and validated with multiple algorithms at each study site: random forests, gradient boosting machines, penalized regression, including stacked ensemble learning algorithms combining them. Predictors were limited to widely available EHR-based features agnostic to a common data model including demographics, diagnostic codes, and medications. The main study outcome was bipolar disorder diagnosis as defined by the International Cohort Collection for Bipolar Disorder, 2015. In total, the study included records for 3,529,569 patients including 12,533 cases (0.3%) of bipolar disorder. After internal and external validation, algorithms demonstrated optimal performance in their respective development sites. The stacked ensemble achieved the best combination of overall discrimination (AUC = 0.82 - 0.87) and calibration performance with positive predictive values above 5% in the highest risk quantiles at all three study sites. In conclusion, generalizable predictive models of risk for bipolar disorder can be feasibly developed across diverse sites to enable precision medicine. Comparison of a range of machine learning methods indicated that an ensemble approach provides the best performance overall but required local retraining. These models will be disseminated via the PsycheMERGE Consortium website.

Identifying High-Risk Comorbidities Associated with Opioid Use Patterns Using Electronic Health Record Prescription Data.

Introduction: Opioid use disorders (OUDs) constitute a major public health issue, and we urgently need alternative methods for characterizing risk for OUD. Electronic health records (EHRs) are useful tools for understanding complex medical phenotypes but have been underutilized for OUD because of challenges related to underdiagnosis, binary diagnostic frameworks, and minimally characterized reference groups. As a first step in addressing these challenges, a new paradigm is warranted that characterizes risk for opioid prescription misuse on a continuous scale of severity, i.e., as a continuum. Methods: Across sites within the PsycheMERGE network, we extracted prescription opioid data and diagnoses that co-occur with OUD (including psychiatric and substance use disorders, pain-related diagnoses, HIV, and hepatitis C) for over 2.6 million patients across three health registries (Vanderbilt University Medical Center, Mass General Brigham, Geisinger) between 2005 and 2018. We defined three groups based on levels of opioid exposure: no prescriptions, minimal exposure, and chronic exposure and then compared the comorbidity profiles of these groups to the full registries and to those with OUD diagnostic codes. Results: Our results confirm that EHR data reflects known higher prevalence of substance use disorders, psychiatric disorders, medical, and pain diagnoses in patients with OUD diagnoses and chronic opioid use. Comorbidity profiles that distinguish opioid exposure are strikingly consistent across large health systems, indicating the phenotypes described in this new quantitative framework are robust to health systems differences. Conclusion: This work indicates that EHR prescription opioid data can serve as a platform to characterize complex risk markers for OUD using existing data.

A Simpler Machine Learning Model for Acute Kidney Injury Risk Stratification in Hospitalized Patients.

Background: Hospitalization-associated acute kidney injury (AKI), affecting one-in-five inpatients, is associated with increased mortality and major adverse cardiac/kidney endpoints. Early AKI risk stratification may enable closer monitoring and prevention. Given the complexity and resource utilization of existing machine learning models, we aimed to develop a simpler prediction model. Methods: Models were trained and validated to predict risk of AKI using electronic health record (EHR) data available at 24 h of inpatient admission. Input variables included demographics, laboratory values, medications, and comorbidities. Missing values were imputed using multiple imputation by chained equations. Results: 26,410 of 209,300 (12.6%) inpatients developed AKI during admission between 13 July 2012 and 11 July 2018. The area under the receiver operating characteristic curve (AUROC) was 0.86 for Random Forest and 0.85 for LASSO. Based on Youden's Index, a probability cutoff of >0.15 provided sensitivity and specificity of 0.80 and 0.79, respectively. AKI risk could be successfully predicted in 91% patients who required dialysis. The model predicted AKI an average of 2.3 days before it developed. Conclusions: The proposed simpler machine learning model utilizing data available at 24 h of admission is promising for early AKI risk stratification. It requires external validation and evaluation of effects of risk prediction on clinician behavior and patient outcomes.

Collaborative Approach to Reach Everyone with Familial Hypercholesterolemia: CARE-FH Protocol.

The Collaborative Approach to Reach Everyone with Familial Hypercholesterolemia (CARE-FH) study aims to improve diagnostic evaluation rates for FH at Geisinger, an integrated health delivery system. This clinical trial relies upon implementation science to transition the initial evaluation for FH into primary care, attempting to identify individuals prior to the onset of atherosclerotic cardiovascular disease events. The protocol for the CARE-FH study of this paper is available online. The first phase of the project focuses on trial design, including the development of implementation strategies to deploy evidence-based guidelines. The second phase will study the intervention, rolled out regionally to internal medicine, community medicine, and pediatric care clinicians using a stepped-wedge design, and analyzing data on diagnostic evaluation rates, and implementation, service, and health outcomes.

The Impact of a Hematopoietic Cellular Therapy Pharmacist on Clinical and Humanistic Outcomes: A RE-AIM Framework Analysis.

The hematopoietic cellular therapy (HCT) pharmacist is an essential member of the multidisciplinary care team. Yet, standardized incorporation of a pharmacist at transplantation centers remains challenging. Implementation science uses theory-driven and systematic approaches to integrate interventions into clinical practice. We describe our experience implementing an HCT pharmacist at our center and conducted a program evaluation using the Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) framework. We implemented 1 full-time equivalent pharmacist to provide medication management services through a collaborative practice agreement (CPA) to the allogeneic transplantation population at a medium-sized center in rural Pennsylvania over a 2-year period. The HCT pharmacist documented all in-person and telephonic care encounters in the electronic medical record. A pharmacist intervention tool was developed to document identified medication-related problems with corresponding interventions and magnitude of intervention. Summary statistics including frequency and percentages were presented for categorical variables in RE-AIM domain. Over the 2-year period, the HCT pharmacist monitored 40 allogeneic patients at our institution accounting for 1531 patient encounters. The average duration of follow-up was 299 days. The HCT pharmacist medication therapy services were able to reach all allogeneic transplants at our institute. The HCT pharmacist managed 388 medications and identified 2156 medication related problems for which the pharmacist provided 2959 interventions. Time in therapeutic range of immunosuppression was 73.9% when managed by the HCT pharmacist through a CPA. Of the 24 patients and 9 caregivers who completed the patient satisfaction survey, 25 (76%) were strongly satisfied with their care. Pharmacy services were gradually adopted and expanded to incorporate additional populations, including 121 autologous transplant and 272 hematology patient encounters. The role of the HCT pharmacist was justified with hospital administration and sustained as a designated pharmacist role at our center. The implementation of an HCT pharmacist service can positively impact patient care. The RE-AIM framework provides a methodological approach for programmatic evaluation and generalizability. © 2022 American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.

Circ_0003611 acts as a miR-885-5p sponge to aggravate the amyloid-ß-induced neuronal injury in Alzheimer's disease.

Alzheimer's disease (AD) is a chronic degenerative disease in the central nervous system and circular RNAs (circRNAs) are identified as essential regulators in AD. The current research was designed for exploration of circ_0003611 in AD. Circ_0003611 was overexpressed in AD patients and Aß-treated SK-N-SH cells. Aß-induced apoptotic, inflammatory and oxidative damages were relieved after knockdown of circ_0003611. MiR-885-5p was validated as a miRNA target of circ_0003611. The protective function of circ_0003611 downregulation was achieved by releasing miR-885-5p in Aß-treated SK-N-SH cells. KREMEN1 was a downstream gene of miR-885-5p. Overexpression of miR-885-5p attenuated the Aß-triggered cell injury by reducing the KREMEN1 expression. KREMEN1 was regulated by circ_0003611 via sponging miR-885-5p in Aß-treated SK-N-SH cells. These experimental data demonstrated that circ_0003611 enhanced the Aß-induced neuronal cell injury in AD by serving as the miR-885-5p sponge to regulate the level of KREMEN1.

Evaluation of a Web-Based Medication Reconciliation Application Within a Primary Care Setting: Cluster-Randomized Controlled Trial.

BACKGROUND: Despite routine review of medication lists during patient encounters, patients' medication lists are often incomplete and not reflective of actual medication use. Contributing to this situation is the challenge of reconciling medication information from existing health records, along with external locations (eg, pharmacies, other provider/hospital records, and care facilities) and patient-reported use. Advances in the interoperability and digital collection of information provides a foundation for integration of these once disparate information sources. OBJECTIVE: We aim to evaluate the effectiveness of and satisfaction with an electronic health record (EHR)-integrated web-based medication reconciliation application, MedTrue (MT). METHODS: We conducted a cluster-randomized controlled trial of MT in 6 primary care clinics within an integrated health care delivery system. Our primary outcome was medication list accuracy, as determined by a pharmacist-collected best-possible medication history (BPMH). Patient and staff perspectives were evaluated through surveys and semistructured interviews. RESULTS: Overall, 224 patients were recruited and underwent a BPMH with the pharmacist (n=118 [52.7%] usual care [UC], n=106 [47.3%] MT). For our primary outcome of medication list accuracy, 8 (7.5%) patients in the MT arm and 9 (7.6%) in the UC arm had 0 discrepancies (odds ratio=1.01, 95% CI 0.38-2.72, P=.98). The most common discrepancy identified was patients reporting no longer taking a medication (UC mean 2.48 vs MT mean 2.58, P=.21). Patients found MT easy to use and on average would highly recommend MT (average net promoter score=8/10). Staff found MT beneficial but difficult to implement. CONCLUSIONS: The use of a web-based application integrated into the EHR which combines EHR, patient-reported data, and pharmacy-dispensed data did not improve medication list accuracy among a population of primary care patients compared to UC but was well received by patients. Future studies should address the limitations of the current application and assess whether improved implementation strategies would impact the effectiveness of the application.

Perioperative diltiazem therapy was not associated with improved perioperative and long-term outcomes in patients undergoing on-pump coronary artery bypass grafting.

Background: Diltiazem has been used during the perioperative period in patients undergoing coronary artery bypass grafting (CABG) to prevent arterial graft spasm. However, its long-term outcome effects remain unclear. Methods: Patient records obtained from the Society of Thoracic Surgeons and the Geisinger Clinic electronic health records between October 2008 and October 2018 were screened. Adult patients who had isolated CABG with cardiopulmonary bypass were included. Cohorts of patients who received diltiazem (DILT) and those who did not (non-DILT) were matched by propensity scores based on age, gender, surgical year, Society of Thoracic Surgeons mortality and morbidity scores, and number of arterial grafts. Incidence rate ratios (IRRs) were estimated for DILT vs non-DILT on short-term adverse outcomes. Long-term survival over time was compared between DILT vs non-DILT using Kaplan-Meier curves. Results: Among the 1004 patients included in the analyses, IRRs for the DILT group relative to the non-DILT group were: 30-day all-cause mortality, IRR: 2.33, 95% confidence interval (CI): 0.91-5.96, P=0.07; postoperative myocardial ischaemia, IRR: 1.10, 95% CI: 0.60-2.02, P=0.75; new onset atrial fibrillation, IRR: 1.06, 95% CI: 0.78-1.43, P=0.73; stroke/transient ischaemic attack, IRR: 0.76, 95% CI: 0.17-3.38, P=0.71. For long-term survival, Kaplan-Meier curves stratified by diltiazem revealed no differences in survival rates between DILT and non-DILT groups. Conclusion: For patients undergoing on-pump CABG, perioperative diltiazem therapy did not show significant short- or long-term outcome advantages over those who did not receive diltiazem.

Feasibility and Assessment of a Cascade Traceback Screening Program (FACTS): Protocol for a Multisite Study to Implement and Assess an Ovarian Cancer Traceback Cascade Testing Program.

Ovarian cancer (OVCA) patients may carry genes conferring cancer risk to biological family; however, fewer than one-quarter of patients receive genetic testing. "Traceback" cascade testing -outreach to potential probands and relatives-is a possible solution. This paper outlines a funded study (U01 CA240747-01A1) seeking to determine a Traceback program's feasibility, acceptability, effectiveness, and costs. This is a multisite prospective observational feasibility study across three integrated health systems. Informed by the Conceptual Model for Implementation Research, we will outline, implement, and evaluate the outcomes of an OVCA Traceback program. We will use standard legal research methodology to review genetic privacy statutes; engage key stakeholders in qualitative interviews to design communication strategies; employ descriptive statistics and regression analyses to evaluate the site differences in genetic testing and the OVCA Traceback testing; and assess program outcomes at the proband, family member, provider, system, and population levels. This study aims to determine a Traceback program's feasibility and acceptability in a real-world context. It will account for the myriad factors affecting implementation, including legal issues, organizational- and individual-level barriers and facilitators, communication issues, and program costs. Project results will inform how health care providers and systems can develop effective, practical, and sustainable Traceback programs.