To prospectively evaluate demographic, anthropometric and health-related quality of life (HRQoL) in pediatric patients with laboratory-confirmed coronavirus disease 2019 (COVID-19) This was a longitudinal observational study of surviving pediatric post-COVID-19 patients (n=53) and pediatric subjects without laboratory-confirmed COVID-19 included as controls (n=52) was performed. The median duration between COVID-19 diagnosis (n=53) and follow-up was 4.4 months (0.8-10.7). Twenty-three of 53 (43%) patients reported at least one persistent symptom at the longitudinal follow-up visit and 12/53 (23%) had long COVID-19, with at least one symptom lasting for >12 weeks. The most frequently reported symptoms at the longitudinal follow-up visit were headache (19%), severe recurrent headache (9%), tiredness (9%), dyspnea (8%), and concentration difficulty (4%). At the longitudinal follow-up visit, the frequencies of anemia (11% versus 0%, p=0.030), lymphopenia (42% versus 18%, p=0.020), C-reactive protein level of >30 mg/L (35% versus 0%, p=0.0001), and D-dimer level of >1000 ng/mL (43% versus 6%, p=0.0004) significantly reduced compared with baseline values. Chest X-ray abnormalities (11% versus 2%, p=0.178) and cardiac alterations on echocardiogram (33% versus 22%, p=0.462) were similar at both visits. Comparison of characteristic data between patients with COVID-19 at the longitudinal follow-up visit and controls showed similar age (p=0.962), proportion of male sex (p=0.907), ethnicity (p=0.566), family minimum monthly wage (p=0.664), body mass index (p=0.601), and pediatric pre-existing chronic conditions (p=1.000). The Pediatric Quality of Live Inventory 4.0 scores, median physical score (69 [0-100] versus 81 [34-100], p=0.012), and school score (60 [15-100] versus 70 [15-95], p=0.028) were significantly lower in pediatric patients with COVID-19 at the longitudinal follow-up visit than in controls. Pediatric patients with COVID-19 showed a longitudinal impact on HRQoL parameters, particularly in physical/school domains, reinforcing the need for a prospective multidisciplinary approach for these patients. These data highlight the importance of closer monitoring of children and adolescents by the clinical team after COVID-19.

To evaluate physical and mental health indicators in adolescents with preexisting chronic immunocompromised conditions during coronavirus disease 2019 (COVID-19) quarantine. A cross-sectional study included 355 adolescents with chronic conditions and 111 healthy adolescents. An online self-rated survey was used to investigate socio-demographic features, healthcare routine, and the quarantine impact on physical and mental health. The validated self-reported version of the Strengths and Difficulties Questionnaire (SDQ) was also applied. The median of age [14 (10–18) vs. 15 (10–18) years, p = 0.733] and frequencies of female (61% vs. 60%, p = 0.970) were similar between adolescents with preexisting chronic conditions and healthy adolescents during quarantine of COVID-19 pandemic. The frequencies of abnormal total difficulties score of SDQ were similar in patients and controls (30% vs. 31%, p = 0.775). Logistic regression analysis showed that being female (OR = 1.965; 95% CI = 1.091–3.541, p = 0.024), fear of underlying disease activity/complication (OR = 1.009; 95%CI = 1.001–1.018, p = 0.030) were associated with severe psychosocial dysfunction in adolescents with chronic conditions, whereas school homework (OR = 0.449; 95% CI = 0.206–0.981, p = 0.045) and physical activity (OR = 0.990; 95% CI = 0.981–0.999, p = 0.030) were protective factors. Further analysis of patients with chronic immunocompromised conditions and previous diagnosis of mental disorders (9%) compared with patients without diagnosis showed higher median of total difficulties score (p = 0.001), emotional (p = 0.005), conduct (p = 0.007), peer problems (p = 0.001) and hyperactivity (p = 0.034) in the former group. Adolescents with preexisting chronic immunocompromised conditions during COVID-19 quarantine were not at higher risk of adverse health indicators. Being female, fear of underlying disease activity/complication, and household members working outside of the home were relevant issues for adolescents with preexisting chronic conditions. This study reinforces the need to establish mental health strategies for teens with chronic conditions, particularly during the pandemic.

To assess the possible factors that influence sleep quality in adolescents with and without chronic immunosuppressive conditions quarantined during the coronavirus disease 2019 (COVID-19) pandemic. This cross-sectional study included 305 adolescents with chronic immunocompromised conditions and 82 healthy adolescents. Online surveys were completed, which included questions on socio-demographic data and self-rated healthcare routine during COVID-19 quarantine and the following validated questionnaires: the Pittsburgh Sleep Quality Index (PSQI), Pediatric Quality of Life Inventory 4.0 (PedsQL4.0), and Pediatric Outcome Data Collection Instrument (PODCI). The median current age [14 (10-18) vs. 15 (10-18) years, p=0.847] and frequency of female sex (62% vs. 58%, p=0.571) were similar in adolescents with chronic conditions compared with healthy adolescents. The frequency of poor sleep quality was similar in both groups (38% vs. 48%, p=0.118). Logistic regression analysis, including both healthy adolescents and adolescents with chronic conditions (n=387), demonstrated that self-reported increase in screen time (odds ratio [OR] 3.0; 95% confidence interval [CI] 1.3-6.8; p=0.008) and intrafamilial violence report (OR 2.1; 95% CI 1.2-3.5; p=0.008) were independently associated with poor sleep quality in these adolescents. However, the PODCI global function score was associated with a lower OR for poor sleep quality (OR 0.97; 95% CI 0.94-0.99; p=0.001). Further logistic regression, including only adolescents with chronic conditions (n=305), demonstrated that self-reported increase in screen time (OR 3.1; 95% CI 1.4-6.8; p=0.006) and intrafamilial violence report (OR 2.0; 95% CI 1.2-3.4; p=0.011) remained independently associated with poor quality of sleep, whereas a lower PODCI global function score was associated with a lower OR for sleep quality (OR 0.96; 95% CI 0.94-0.98; p<0.001). Self-reported increases in screen time and intrafamilial violence report impacted sleep quality in both healthy adolescents and those with chronic conditions. Decreased health-related quality of life was observed in adolescents with poor sleep quality.

Objective The Athlete Psychological Strain Questionnaire (APSQ) is a 10-item mental health screen in the International Olympic Committee Sport Mental Health Assessment Tool 1. This study evaluated its accuracy compared to six validated mental health screening tools in collegiate athletes. Methods Division I collegiate athletes (n=2758) completed the APSQ alongside validated screening tools for anxiety (Generalised Anxiety Disorder-7 (GAD-7)), depression (Patient Health Questionnaire-9 (PHQ-9)), sleep disturbance (Athlete Sleep Screening Questionnaire-Sleep Difficulty Score (ASSQ-SDS)), alcohol use (Alcohol Use Disorders Identification Test-Consumption (AUDIT-C)), substance use (Cutting down, Annoyance by Criticism, Guilty feelings and Eye openers Adapted to Include Drugs (CAGE-AID) and disordered eating (Eating Disorder Examination—Questionnaire Short (EDE-QS)) between June 2020 and June 2023. The APSQ’s performance was assessed using sensitivity, specificity and area under the curve (AUC). Results Of 2758 completed APSQ, 720 (26.1%) screened positive. The rates of positive screens for other measures were GAD-7=7.7%, PHQ-9=11.6% (3.1% reported suicidal ideation on item 9), ASSQ-SDS=21.0%, AUDIT-C=14.5%, CAGE-AID=2.9% and EDE-QS=4.8%. Compared with the APSQ, we observed high accuracy for anxiety (GAD-7: AUC=0.92, sensitivity=90%, specificity=83%) and depression (PHQ-9: AUC=0.91, sensitivity=82%, specificity=84%). There was moderate accuracy for disordered eating (EDE-QS: AUC=0.85, sensitivity=82%, specificity=81%), while accuracy was lower for sleep disturbance (ASSQ-SDS: AUC=0.72, sensitivity=52%, specificity=84%), substance use (CAGE-AID: AUC=0.69, sensitivity=61%, specificity=79%) and alcohol use (AUDIT-C: AUC=0.64, sensitivity=46%, specificity=81%). False-negative rates ranged from 9.9% (GAD-7) to 55% (AUDIT-C). Conclusion The APSQ accurately identifies athletes at risk for anxiety and depression but is less accurate for detecting other mental health issues. Adding more specific questions on sleep disturbance and alcohol use to the APSQ could further improve its accuracy.