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Introducción. La descripción de las características y los diagnósticos de pacientes psiquiátricos con COVID-19 durante la pandemia ha sido poco descrito en el Perú. Objetivo. Describir la frecuencia de diagnósticos psiquiátricos y sus características sociodemográficas en pacientes con prueba antigénica positiva a COVID-19 en un hospital psiquiátrico peruano durante julio 2020 a julio 2021. Métodos. Se realizó un estudio descriptivo basado en la revisión de 100 historias clínicas de pacientes entre 18 y 70 años. Las variables estudiadas fueron el diagnóstico de ingreso y variables sociodemográficas como edad, sexo, nivel académico, ocupación, días de estancia. Resultados. Los diagnósticos más frecuentes fueron esquizofrenia, trastornos esquizotípicos y trastornos de ideas delirantes (49%) y los trastornos del humor (37%). El 66% pertenecía a los niveles socioeconómicos más bajos y el 60% eran pacientes continuadores. El mes de abril de 2021 presentó la mayor cantidad de ingresos (n=15). Conclusión. Durante un año de observación en tiempos de emergencia sanitaria por la COVID-19, ingresaron a un hospital psiquiátrico de referencia 100 pacientes con diagnóstico psiquiátrico que además tuvieron infección por SARS-CoV-2, la mayoría de estos pacientes tuvieron trastornos psicóticos.

Introduction. The description of the characteristics and diagnoses of psychiatric patients with COVID-19 during the pandemic has been poorly described in Peru. Objective. To describe the frequency of mental disorders and the associated sociodemographic characteristics of patients with a positive antigen test for COVID-19 in a peruvian psychiatric hospital from July 2020 to July 2021. Methods. For this descriptive study we analyzed 100 medical records of patients between 18 and 70 years old. The variables studied were the diagnosis according to ICD-10 and sociodemographic features such as age, gender, educational status, employment, days of admission. Results. The most common diagnoses were "Schizophrenia, schizotypal disorders and delusional disorders" (49%) and "mood disorders" (37%), 66% belonged to the lowest socioeconomic levels and 60% were recurrent patients. The month of April 2021 presented the highest number of admissions (n=15). Conclusion. In a year of observation during the COVID-19 outbreak, 100 patients with psychiatric diagnosis who also had SARS-CoV-2 infection were admitted to a reference psychiatric hospital, most of these patients had psychotic disorders.

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OBJECTIVES: To predict behavioral disruptions in middle childhood, we identified latent classes of prenatal substance use. STUDY DESIGN: As part of the Environmental influences on Child Health Outcomes Program, we harmonized prenatal substance use data and child behavior outcomes from 2195 women and their 6- to 11-year-old children across 10 cohorts in the US and used latent class-adjusted regression models to predict parent-rated child behavior. RESULTS: Three latent classes fit the data: low use (90.5%; n = 1986), primarily using no substances; licit use (6.6%; n = 145), mainly using nicotine with a moderate likelihood of using alcohol and marijuana; and illicit use (2.9%; n = 64), predominantly using illicit substances along with a moderate likelihood of using licit substances. Children exposed to primarily licit substances in utero had greater levels of externalizing behavior than children exposed to low or no substances (P = .001, d = .64). Children exposed to illicit substances in utero showed small but significant elevations in internalizing behavior than children exposed to low or no substances (P < .001, d = .16). CONCLUSIONS: The differences in prenatal polysubstance use may increase risk for specific childhood problem behaviors; however, child outcomes appeared comparably adverse for both licit and illicit polysubstance exposure. We highlight the need for similar multicohort, large-scale studies to examine childhood outcomes based on prenatal substance use profiles.

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Studies often rely on medical record abstraction as a major source of data. However, data quality from medical record abstraction has long been questioned. Electronic Health Records (EHRs) potentially add variability to the abstraction process due to the complexity of navigating and locating study data within these systems. We report training for and initial quality assessment of medical record abstraction for a clinical study conducted by the IDeA States Pediatric Clinical Trials Network (ISPCTN) and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Neonatal Research Network (NRN) using medical record abstraction as the primary data source. As part of overall quality assurance, study-specific training for medical record abstractors was developed and deployed during study start-up. The training consisted of a didactic session with an example case abstraction and an independent abstraction of two standardized cases. Sixty-nine site abstractors from thirty sites were trained. The training was designed to achieve an error rate for each abstractor of no greater than 4.93% with a mean of 2.53%, at study initiation. Twenty-three percent of the trainees exceeded the acceptance limit on one or both of the training test cases, supporting the need for such training. We describe lessons learned in the design and operationalization of the study-specific, medical record abstraction training program.

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