Search

Author(s): Tomás Formánek 1,2,*, Libor Potocár 1,3, Katrin Wolfova 4,5, Hana Melicharová 6, Karolína Mladá 1,7, Anna Wiedemann 2, Danni Chen 8, Pavel Mohr 9,10, Petr Winkler 1,11, Peter B. [...], Background Evidence suggests reduced survival rates following Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in people with preexisting mental disorders, especially psychotic disorders, before the broad introduction of vaccines. It remains unknown whether this elevated mortality risk persisted at later phases of the pandemic and when accounting for the confounding effect of vaccination uptake and clinically recorded physical comorbidities. Methods and findings We used data from Czech national health registers to identify first-ever serologically confirmed SARS-CoV-2 infections in 5 epochs related to different phases of the pandemic: 1st March 2020 to 30th September 2020, 1st October 2020 to 26th December 2020, 27th December 2020 to 31st March 2021, 1st April 2021 to 31st October 2021, and 1st November 2021 to 29th February 2022. In these people, we ascertained cases of mental disorders using 2 approaches: (1) per the International Classification of Diseases 10th Revision (ICD-10) diagnostic codes for substance use, psychotic, affective, and anxiety disorders; and (2) per ICD-10 diagnostic codes for the above mental disorders coupled with a prescription for anxiolytics/hypnotics/sedatives, antidepressants, antipsychotics, or stimulants per the Anatomical Therapeutic Chemical (ATC) classification codes. We matched individuals with preexisting mental disorders with counterparts who had no recorded mental disorders on age, sex, month and year of infection, vaccination status, and the Charlson Comorbidity Index (CCI). We assessed deaths with Coronavirus Disease 2019 (COVID-19) and from all-causes in the time period of 28 and 60 days following the infection using stratified Cox proportional hazards models, adjusting for matching variables and additional confounders. The number of individuals in matched-cohorts ranged from 1,328 in epoch 1 to 854,079 in epoch 5. The proportion of females ranged from 34.98% in people diagnosed with substance use disorders in epoch 3 to 71.16% in individuals diagnosed and treated with anxiety disorders in epoch 5. The mean age ranged from 40.97 years (standard deviation [SD] = 15.69 years) in individuals diagnosed with substance use disorders in epoch 5 to 56.04 years (SD = 18.37 years) in people diagnosed with psychotic disorders in epoch 2. People diagnosed with or diagnosed and treated for psychotic disorders had a consistently elevated risk of dying with COVID-19 in epochs 2, 3, 4, and 5, with adjusted hazard ratios (aHRs) ranging from 1.46 [95% confidence intervals (CIs), 1.18, 1.79] to 1.93 [95% CIs, 1.12, 3.32]. This patient group demonstrated also a consistently elevated risk of all-cause mortality in epochs 2, 3, 4, and 5 (aHR from 1.43 [95% CIs, 1.23, 1.66] to 1.99 [95% CIs, 1.25, 3.16]). The models could not be reliably fit for psychotic disorders in epoch 1. People diagnosed with substance use disorders had an increased risk of all-cause mortality 28 days postinfection in epoch 3, 4, and 5 (aHR from 1.30 [95% CIs, 1.14, 1.47] to 1.59 [95% CIs, 1.19, 2.12]) and 60 days postinfection in epoch 2, 3, 4, and 5 (aHR from 1.22 [95% CIs, 1.08, 1.38] to 1.52 [95% CIs, 1.16, 1.98]). Cases ascertained based on diagnosis of substance use disorders and treatment had increased risk of all-cause mortality in epoch 2, 3, 4, and 5 (aHR from 1.22 [95% CIs, 1.03, 1.43] to 1.91 [95% CIs, 1.25, 2.91]). The models could not be reliably fit for substance use disorders in epoch 1. In contrast to these, people diagnosed with anxiety disorders had a decreased risk of death with COVID-19 in epoch 2, 3, and 5 (aHR from 0.78 [95% CIs, 0.69, 0.88] to 0.89 [95% CIs, 0.81, 0.98]) and all-cause mortality in epoch 2, 3, 4, and 5 (aHR from 0.83 [95% CIs, 0.77, 0.90] to 0.88 [95% CIs, 0.83, 0.93]). People diagnosed and treated for affective disorders had a decreased risk of both death with COVID-19 and from all-causes in epoch 3 (aHR from 0.87 [95% CIs, 0.79, 0.96] to 0.90 [95% CIs, 0.83, 0.99]), but demonstrated broadly null effects in other epochs. Given the unavailability of data on a number of potentially influential confounders, particularly body mass index, tobacco smoking status, and socioeconomic status, part of the detected associations might be due to residual confounding. Conclusions People with preexisting psychotic, and, less robustly, substance use disorders demonstrated a persistently elevated risk of death following SARS-CoV-2 infection throughout the pandemic. While it cannot be ruled out that part of the detected associations is due to residual confounding, this excess mortality cannot be fully explained by lower vaccination uptake and more clinically recorded physical comorbidities in these patient groups.

Background: It remains unknown whether severe mental disorders contribute to fatally harmful effects of physical illness. Aims: To investigate the risk of all-cause death and loss of life-years following the onset of a wide range of physical health conditions in people with severe mental disorders compared with matched counterparts who had only these physical health conditions, and to assess whether these associations can be fully explained by this patient group having more clinically recorded physical illness. Method: Using Czech national in-patient register data, we identified individuals with 28 physical health conditions recorded between 1999 and 2017, separately for each condition. In these people, we identified individuals who had severe mental disorders recorded before the physical health condition and exactly matched them with up to five counterparts who had no recorded prior severe mental disorders. We estimated the risk of all-cause death and lost life-years following each of the physical health conditions in people with pre-existing severe mental disorders compared with matched counterparts without severe mental disorders. Results: People with severe mental disorders had an elevated risk of all-cause death following the onset of 7 out of 9 broadly defined and 14 out of 19 specific physical health conditions. People with severe mental disorders lost additional life-years following the onset of 8 out 9 broadly defined and 13 out of 19 specific physical health conditions. The vast majority of results remained robust after considering the potentially confounding role of somatic multimorbidity and other clinical and sociodemographic factors. Conclusions: A wide range of physical illnesses are more likely to result in all-cause death in people with pre-existing severe mental disorders. This premature mortality cannot be fully explained by having more clinically recorded physical illness, suggesting that physical disorders are more likely to be fatally harmful in this patient group. [ABSTRACT FROM AUTHOR]

Copyright of Ceská a Slovenská Psychiatrie is the property of Czech Medical Association of JE Purkyne and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Rehospitalization in a year after the first discharge for psychotic disorder is routinely considered as a principal health care outcome. However, there is a lack of data about the rehospitalization rate of people with first-episode psychosis in Central and Eastern Europe where the psychiatric care is predominantly based on inpatient care. Methods: Data from nationwide register of inpatient hospitalizations were analysed. A retrospective analysis of first-ever admitted patients with psychosis (F2 according to ICD-10) in 2014 and younger than 60 years of age was conducted. Descriptive statistics aiming to identify the rehospitalization rate were performed. Results: 1 963 patients with psychosis who were first admitted to psychiatric hospitalization in 2014 and discharged between 2014 and 2016 were identified. Of those, 480 (24,5 %) were readmitted in the first year after the first discharge. 101 (21,0%) of those were readmitted within 14 days, 144 (30,0%) within a month and 241 (50,2%) within a 3-month period after the first discharge. An average time between the first discharge and readmission was 124 days, the mean age of those readmitted was 33 years at the time of first admission. Discussion: This register-based study confirms the existence of the revolving door phenomenon in people with first-episode psychosis in the Czech Republic. Each rehospitalization is a burden not only for a patient, as each hospitalization significantly worsens the overall prognosis, but for the whole psychiatric care system as well. Considering the rehospitalization rate in people with first-episode psychosis, more attention should be paid to the development of services which have a potential to lower the risk of rehospitalization such as early detection and early intervention services. [ABSTRACT FROM AUTHOR]

Objectives: The Pittsburgh Sleep Quality Index (PSQI) is one of the widely used and recommended measures of assessing sleep quality in chronic insomnia; however certain psychometric properties of the questionnaire are still unknown in this group of patients. The present study aimed to examine the internal consistency, and structural and convergent validity of the Czech version of the PSQI in chronic insomnia patients. The usefulness of the standard and alternative scoring systems was also investigated in relation to symptoms of sleepiness, insomnia, depression, and anxiety., Methods: In our study, 105 participants filled out a series of questionnaires including PSQI, Insomnia Severity Index (ISI), Epworth Sleepiness Scale (ESS), and Beck Depression and Anxiety Inventories (BDI, BAI)., Results: The internal consistency of the questionnaire using Cronbach's alpha was 0.608. A series of confirmatory factor analyses revealed adequate fit for three structures. A three-factor model descriptively stood out among the rest but subsequent correlational analyses did not provide sufficient support for accepting an alternative scoring model., Conclusions: The results highlight the issue of structural variance of the PSQI and in chronic insomnia point to the important role of the PSQI components of daytime dysfunction and sleep disturbances in showing comorbid symptoms with daytime sleepiness and psychopathology.