Browsing by Author "Salyakina, Daria"

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    EHR-based Case Identification of Pediatric Long COVID: A Report from the RECOVER EHR Cohort
    (medRxiv, 2024-05-23) Botdorf, Morgan; Dickinson, Kimberley; Lorman, Vitaly; Razzaghi, Hanieh; Marchesani, Nicole; Rao, Suchitra; Rogerson, Colin; Higginbotham, Miranda; Mejias, Asuncion; Salyakina, Daria; Thacker, Deepika; Dandachi, Dima; Christakis, Dimitri A.; Taylor, Emily; Schwenk, Hayden; Morizono, Hiroki; Cogen, Jonathan; Pajor, Nate M.; Jhaveri, Ravi; Forrest, Christopher B.; Bailey, L. Charles; RECOVER Consortium; Pediatrics, School of Medicine
    Objective: Long COVID, marked by persistent, recurring, or new symptoms post-COVID-19 infection, impacts children's well-being yet lacks a unified clinical definition. This study evaluates the performance of an empirically derived Long COVID case identification algorithm, or computable phenotype, with manual chart review in a pediatric sample. This approach aims to facilitate large-scale research efforts to understand this condition better. Methods: The algorithm, composed of diagnostic codes empirically associated with Long COVID, was applied to a cohort of pediatric patients with SARS-CoV-2 infection in the RECOVER PCORnet EHR database. The algorithm classified 31,781 patients with conclusive, probable, or possible Long COVID and 307,686 patients without evidence of Long COVID. A chart review was performed on a subset of patients (n=651) to determine the overlap between the two methods. Instances of discordance were reviewed to understand the reasons for differences. Results: The sample comprised 651 pediatric patients (339 females, M age = 10.10 years) across 16 hospital systems. Results showed moderate overlap between phenotype and chart review Long COVID identification (accuracy = 0.62, PPV = 0.49, NPV = 0.75); however, there were also numerous cases of disagreement. No notable differences were found when the analyses were stratified by age at infection or era of infection. Further examination of the discordant cases revealed that the most common cause of disagreement was the clinician reviewers' tendency to attribute Long COVID-like symptoms to prior medical conditions. The performance of the phenotype improved when prior medical conditions were considered (accuracy = 0.71, PPV = 0.65, NPV = 0.74). Conclusions: Although there was moderate overlap between the two methods, the discrepancies between the two sources are likely attributed to the lack of consensus on a Long COVID clinical definition. It is essential to consider the strengths and limitations of each method when developing Long COVID classification algorithms.
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    Prescribing Prevalence of Medications With Potential Genotype-Guided Dosing in Pediatric Patients
    (American Medical Association, 2020-12) Ramsey, Laura B.; Ong, Henry H.; Schildcrout, Jonathan S.; Shi, Yaping; Tang, Leigh Anne; Hicks, J. Kevin; El Rouby, Nihal; Cavallari, Larisa H.; Tuteja, Sony; Aquilante, Christina L.; Beitelshees, Amber L.; Lemkin, Daniel L.; Blake, Kathryn V.; Williams, Helen; Cimino, James J.; Davis, Brittney H.; Limdi, Nita A.; Empey, Philip E.; Horvat, Christopher M.; Kao, David P.; Lipori, Gloria P.; Rosenman, Marc B.; Skaar, Todd C.; Teal, Evgenia; Winterstein, Almut G.; Obeng, Aniwaa Owusu; Salyakina, Daria; Gupta, Apeksha; Gruber, Joshua; McCafferty-Fernandez, Jennifer; Bishop, Jeffrey R.; Rivers, Zach; Benner, Ashley; Tamraz, Bani; Long-Boyle, Janel; Peterson, Josh F.; Van Driest, Sara L.; Pediatrics, School of Medicine
    Importance: Genotype-guided prescribing in pediatrics could prevent adverse drug reactions and improve therapeutic response. Clinical pharmacogenetic implementation guidelines are available for many medications commonly prescribed to children. Frequencies of medication prescription and actionable genotypes (genotypes where a prescribing change may be indicated) inform the potential value of pharmacogenetic implementation. Objective: To assess potential opportunities for genotype-guided prescribing in pediatric populations among multiple health systems by examining the prevalence of prescriptions for each drug with the highest level of evidence (Clinical Pharmacogenetics Implementation Consortium level A) and estimating the prevalence of potential actionable prescribing decisions. Design, setting, and participants: This serial cross-sectional study of prescribing prevalences in 16 health systems included electronic health records data from pediatric inpatient and outpatient encounters from January 1, 2011, to December 31, 2017. The health systems included academic medical centers with free-standing children's hospitals and community hospitals that were part of an adult health care system. Participants included approximately 2.9 million patients younger than 21 years observed per year. Data were analyzed from June 5, 2018, to April 14, 2020. Exposures: Prescription of 38 level A medications based on electronic health records. Main outcomes and measures: Annual prevalence of level A medication prescribing and estimated actionable exposures, calculated by combining estimated site-year prevalences across sites with each site weighted equally. Results: Data from approximately 2.9 million pediatric patients (median age, 8 [interquartile range, 2-16] years; 50.7% female, 62.3% White) were analyzed for a typical calendar year. The annual prescribing prevalence of at least 1 level A drug ranged from 7987 to 10 629 per 100 000 patients with increasing trends from 2011 to 2014. The most prescribed level A drug was the antiemetic ondansetron (annual prevalence of exposure, 8107 [95% CI, 8077-8137] per 100 000 children). Among commonly prescribed opioids, annual prevalence per 100 000 patients was 295 (95% CI, 273-317) for tramadol, 571 (95% CI, 557-586) for codeine, and 2116 (95% CI, 2097-2135) for oxycodone. The antidepressants citalopram, escitalopram, and amitriptyline were also commonly prescribed (annual prevalence, approximately 250 per 100 000 patients for each). Estimated prevalences of actionable exposures were highest for oxycodone and ondansetron (>300 per 100 000 patients annually). CYP2D6 and CYP2C19 substrates were more frequently prescribed than medications influenced by other genes. Conclusions and relevance: These findings suggest that opportunities for pharmacogenetic implementation among pediatric patients in the US are abundant. As expected, the greatest opportunity exists with implementing CYP2D6 and CYP2C19 pharmacogenetic guidance for commonly prescribed antiemetics, analgesics, and antidepressants.
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    The impact of clinical genome sequencing in a global population with suspected rare genetic disease
    (Elsevier, 2024) Thorpe, Erin; Williams, Taylor; Shaw, Chad; Chekalin, Evgenii; Ortega, Julia; Robinson, Keisha; Button, Jason; Jones, Marilyn C.; Del Campo, Miguel; Basel, Donald; McCarrier, Julie; Davis Keppen, Laura; Royer, Erin; Foster-Bonds, Romina; Duenas-Roque, Milagros M.; Urraca, Nora; Bosfield, Kerri; Brown, Chester W.; Lydigsen, Holly; Mroczkowski, Henry J.; Ward, Jewell; Sirchia, Fabio; Giorgio, Elisa; Vaux, Keith; Peña Salguero, Hildegard; Lumaka, Aimé; Mubungu, Gerrye; Makay, Prince; Ngole, Mamy; Tshilobo Lukusa, Prosper; Vanderver, Adeline; Muirhead, Kayla; Sherbini, Omar; Lah, Melissa D.; Anderson, Katelynn; Bazalar-Montoya, Jeny; Rodriguez, Richard S.; Cornejo-Olivas, Mario; Milla-Neyra, Karina; Shinaw, Marwan; Magoulas, Pilar; Henry, Duncan; Gibson, Kate; Wiaf, Samuel; Jayakar, Parul; Salyakina, Daria; Masser-Frye, Diane; Serize, Arturo; Perez, Jorge E.; Taylor, Alan; Shenbagam, Shruti; Tayoun, Ahmad Abou; Malhotra, Alka; Bennett, Maren; Rajan, Vani; Avecilla, James; Warren, Andrew; Arseneault, Max; Kalista, Tasha; Crawford, Ali; Ajay, Subramanian S.; Perry, Denise L.; Belmont, John; Taft, Ryan J.; Medicine, School of Medicine
    There is mounting evidence of the value of clinical genome sequencing (cGS) in individuals with suspected rare genetic disease (RGD), but cGS performance and impact on clinical care in a diverse population drawn from both high-income countries (HICs) and low- and middle-income countries (LMICs) has not been investigated. The iHope program, a philanthropic cGS initiative, established a network of 24 clinical sites in eight countries through which it provided cGS to individuals with signs or symptoms of an RGD and constrained access to molecular testing. A total of 1,004 individuals (median age, 6.5 years; 53.5% male) with diverse ancestral backgrounds (51.8% non-majority European) were assessed from June 2016 to September 2021. The diagnostic yield of cGS was 41.4% (416/1,004), with individuals from LMIC sites 1.7 times more likely to receive a positive test result compared to HIC sites (LMIC 56.5% [195/345] vs. HIC 33.5% [221/659], OR 2.6, 95% CI 1.9-3.4, p < 0.0001). A change in diagnostic evaluation occurred in 76.9% (514/668) of individuals. Change of management, inclusive of specialty referrals, imaging and testing, therapeutic interventions, and palliative care, was reported in 41.4% (285/694) of individuals, which increased to 69.2% (480/694) when genetic counseling and avoidance of additional testing were also included. Individuals from LMIC sites were as likely as their HIC counterparts to experience a change in diagnostic evaluation (OR 6.1, 95% CI 1.1-∞, p = 0.05) and change of management (OR 0.9, 95% CI 0.5-1.3, p = 0.49). Increased access to genomic testing may support diagnostic equity and the reduction of global health care disparities.