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Introduction: Autism spectrum disorder (ASD) is characterized by deficits in social communication, repetitive behaviors, and can be accompanied by a spectrum of psychiatric symptoms, such as schizophrenia and catatonia. Rarely, these symptoms, if left untreated, can result in spinal deformities. Research question and case description: This case report details the treatment of a 16-year-old male ASD patient with catatonic schizophrenia and mutism, presenting with neck pain, left-rotated torticollis, and fever. MRI revealed atlantoaxial rotational instability and spinal cord compression from a dislocated dens axis. After inconclusive biopsies, empirical antibiotics, hard collar and halo fixation treatment, persistent instability necessitated C1/2 fusion. The ongoing catatonia was addressed with electroconvulsive therapy. Concurrently, he developed severe subaxial hyperkyphosis. The report examines the decision-making between conservative and surgical management for an adolescent with significant psychiatric comorbidity and progressive spinal symptoms against a backdrop of uncertain etiology. Materials and methods: A case report and review of the literature. Results: Posterior C1-C7 stabilization was successfully executed, effectively restoring cervical sagittal alignment, which was maintained throughout a two-year follow-up. Concurrently, the catatonia resolved. Discussion and conclusion: To our knowledge, this is the third reported case of severe cervical deformity associated with fixed posture in a psychiatric patient. This case report emphasizes the critical importance of multidisciplinary collaboration in managing the interplay between neuropsychiatric disorders and severe spinal deformities. It showcases the practicality and efficacy of surgical intervention for persistent cervical deformity in pediatric schizophrenia patients, highlighting the necessity for a comprehensive risk-benefit analysis.
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BACKGROUND: Severe courses and high hospitalization rates were ubiquitous during the first pandemic SARS-CoV-2 waves. Thus, we aimed to examine whether integrative diagnostics may aid in identifying vulnerable patients using crucial data and materials obtained from COVID-19 patients hospitalized between 2020 and 2021 (n = 52). Accordingly, we investigated the potential of laboratory biomarkers, specifically the dynamic cell decay marker cell-free DNA and radiomics features extracted from chest CT. METHODS: Separate forward and backward feature selection was conducted for linear regression with the Intensive-Care-Unit (ICU) period as the initial target. Three-fold cross-validation was performed, and collinear parameters were reduced. The model was adapted to a logistic regression approach and verified in a validation naïve subset to avoid overfitting. RESULTS: The adapted integrated model classifying patients into "ICU/no ICU demand" comprises six radiomics and seven laboratory biomarkers. The models' accuracy was 0.54 for radiomics, 0.47 for cfDNA, 0.74 for routine laboratory, and 0.87 for the combined model with an AUC of 0.91. CONCLUSION: The combined model performed superior to the individual models. Thus, integrating radiomics and laboratory data shows synergistic potential to aid clinic decision-making in COVID-19 patients. Under the need for evaluation in larger cohorts, including patients with other SARS-CoV-2 variants, the identified parameters might contribute to the triage of COVID-19 patients.
