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Objective: To analyze and compare the effects of different clinical characteristics on the negative conversion time of nucleic acid detection after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant infection, and to provide a scientific basis for the isolation and treatment of coronavirus disease 2019 (COVID-19). Methods: The epidemiological and clinical data of 228 mild SARS-CoV-2 Omicron variant infected patients diagnosed in Shanghai were retrospectively collected from April 27, 2022 to June 8, 2022 in Wujiaochang designated Hospital, Yangpu District, Shanghai. The negative conversion time of nucleic acid detection was used as the outcome variable, and the patients were divided into A (18 days) and B (>18 days). Univariate and multivariate logistic regression analysis were used to analyze the influencing factors of the negative conversion time of nucleic acid detection. Results: The mean nucleic acid conversion time of 228 patients was (18.7+or-12.1) d, with the median time of 18 (2-46) d. Among them, 120 patients in group A had an average nucleic acid conversion time of (13.2+or-2.0) d, and 108 cases in group B had an average nucleic acid conversion time of (20.8+or-1.3) d. Univariate analysis showed that there were no statistically significant differences in the effects of hypertension, coronary heart disease, diabetes, hypokalemia, malignant tumors, neuropsychiatric diseases, chronic digestive diseases on the negative nucleic acid conversion time (P > 0.05);however, there were significant differences in the effects of combined cerebrovascular disease, leukopenia, chronic respiratory system diseases and vaccination on the negative nucleic acid conversion time (P < 0.05). Further multivariate logistic regression analysis revealed that the combination of chronic respiratory diseases and non-vaccination were significant risk factors for prolongation of negative nucleic acid conversion time (P < 0.05). Conclusions: The results of this study show that gender, age and whether hypertension, coronary heart disease, diabetes mellitus, hypokalemia, malignant tumor, neuropsychiatric disease and chronic digestive disease have no significant effect on the nucleic acid conversion time, whereas chronic respiratory disease and no vaccination are significantly correlated with the prolongation of nucleic acid conversion time in SARS-CoV-2 Omicron-infected patients.
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BackgroundComprehensive and large-scale assessment of health-related quality of life in patients with idiopathic inflammatory myopathies (IIMs) worldwide is lacking. The second COVID-19 vaccination in autoimmune disease (COVAD-2) study [1] is an international, multicentre, self-reported e-survey assessing several aspects of COVID-19 infection and vaccination as well as validated patient-reported outcome measures (PROMs) to outline patient experience in various autoimmune diseases (AIDs), with a particular focus on IIMs.ObjectivesTo investigate physical and mental health in a global cohort of IIM patients compared to those with non-IIM autoimmune inflammatory rheumatic diseases (AIRDs), non-rheumatic AIDs (NRAIDs), and those without AIDs (controls), using Patient-Reported Outcome Measurement Information System (PROMIS) global health data obtained from the COVAD-2 survey.MethodsDemographics, AID diagnoses, comorbidities, disease activity, treatments, and PROMs were extracted from the COVAD-2 database. The primary outcomes were PROMIS Global Physical Health (GPH) and Global Mental Health (GMH) scores. Secondary outcomes included PROMIS physical function short form-10a (PROMIS PF-10a), pain visual analogue scale (VAS), and PROMIS Fatigue-4a scores. Each outcome was compared between IIMs, non-IIM AIRDs, NRAIDs, and controls. Factors affecting GPH and GMH scores in IIMs were identified using multivariable regression analysis.ResultsA total of 10,502 complete responses from 1582 IIMs, 4700 non-IIM AIRDs, 545 NRAIDs, and 3675 controls, which accrued as of May 2022, were analysed. Patients with IIMs were older [59±14 (IIMs) vs. 48±14 (non-IIM AIRDs) vs. 45±14 (NRAIDs) vs. 40±14 (controls) years, p<0.001] and more likely to be Caucasian [82.7% (IIMs) vs. 53.2% (non-IIM AIRDs) vs. 62.4% (NRAIDs) vs. 34.5% (controls), p<0.001]. Among IIMs, dermatomyositis (DM) and juvenile DM were the most common (31.4%), followed by inclusion body myositis (IBM) (24.9%). Patients with IIMs were more likely to have comorbidities [68.1% (IIMs) vs. 45.7% (non-IIM AIRDs) vs. 45.1% (NRAIDs) vs. 26.3% (controls), p<0.001] including mental disorders [33.4% (IIMs) vs. 28.2% (non-IIM AIRDs) vs. 28.4% (NRAIDs) vs. 17.9% (controls), p<0.001].GPH median scores were lower in IIMs compared to NRAIDs or controls [13 (interquartile range 10–15) IIMs vs. 13 (11–15) non-IIM AIRDs vs. 15 (13–17) NRAIDs vs. 17 (15–18) controls, p<0.001] and PROMIS PF-10a median scores were the lowest in IIMs [34 (25–43) IIMs vs. 40 (34–46) non-IIM AIRDs vs. 47 (40–50) NRAIDs vs. 49 (45–50) controls, p<0.001]. GMH median scores were lower in AIDs including IIMs compared to controls [13 (10–15) IIMs vs. 13 (10–15) non-IIM AIRDs vs. 13 (11–16) NRAIDs vs. 15 (13–17) controls, p<0.001]. Pain VAS median scores were higher in AIDs compared to controls [3 (1–5) IIMs vs. 4 (2–6) non-IIM AIRDs vs. 2 (0–4) NRAIDs vs. 0 (0–2) controls, p<0.001]. Of note, PROMIS Fatigue-4a median scores were the highest in IIMs [11 (8–14) IIMs vs. 8 (10–14) non-IIM AIRDs vs. 9 (7–13) NRAIDs vs. 7 (4–10) controls, p<0.001].Multivariable regression analysis in IIMs identified older age, male sex, IBM, comorbidities including hypertension and diabetes, active disease, glucocorticoid use, increased pain and fatigue as the independent factors for lower GPH scores, whereas coexistence of interstitial lung disease, mental disorders including anxiety disorder and depression, active disease, increased pain and fatigue were the independent factors for lower GMH scores.ConclusionBoth physical and mental health are significantly impaired in patients with IIMs compared to those with non-IIM AIDs or those without AIDs. Our results call for greater attention to patient-reported experience and comorbidities including mental disorders to provide targeted approaches and optimise global well-being in patients with IIMs.Reference[1]Fazal ZZ, Sen P, Joshi M, et al. COVAD survey 2 long-term outcomes: unmet need and protocol. Rheumatol Int. 2022;42:2151–58.AcknowledgementsThe authors a e grateful to all respondents for completing the questionnaire. The authors also thank The Myositis Association, Myositis India, Myositis UK, the Myositis Global Network, Cure JM, Cure IBM, Sjögren's India Foundation, EULAR PARE for their contribution to the dissemination of the survey. Finally, the authors wish to thank all members of the COVAD study group for their invaluable role in the data collection.Disclosure of InterestsAkira Yoshida: None declared, Yuan Li: None declared, Vahed Maroufy: None declared, Masataka Kuwana Speakers bureau: Boehringer Ingelheim, Ono Pharmaceuticals, AbbVie, Janssen, Astellas, Bayer, Asahi Kasei Pharma, Chugai, Eisai, Mitsubishi Tanabe, Nippon Shinyaku, Pfizer, Consultant of: Corbus, Mochida, Grant/research support from: Boehringer Ingelheim, Ono Pharmaceuticals, Naveen Ravichandran: None declared, Ashima Makol Consultant of: Boehringer-Ingelheim, Parikshit Sen: None declared, James B. Lilleker: None declared, Vishwesh Agarwal: None declared, Sinan Kardes: None declared, Jessica Day Grant/research support from: CSL Limited, Marcin Milchert: None declared, Mrudula Joshi: None declared, Tamer A Gheita: None declared, Babur Salim: None declared, Tsvetelina Velikova: None declared, Abraham Edgar Gracia-Ramos: None declared, Ioannis Parodis Grant/research support from: Amgen, AstraZeneca, Aurinia Pharmaceuticals, Eli Lilly, Gilead Sciences, GlaxoSmithKline, Janssen Pharmaceuticals, Novartis, and F. Hoffmann-La Roche, Elena Nikiphorou Speakers bureau: Celltrion, Pfizer, Sanofi, Gilead, Galapagos, AbbVie, Eli Lilly, Consultant of: Celltrion, Pfizer, Sanofi, Gilead, Galapagos, AbbVie, Eli Lilly, Grant/research support from: Pfizer, Eli Lilly, Ai Lyn Tan Speakers bureau: AbbVie, Gilead, Janssen, Eli Lilly, Novartis, Pfizer, UCB, Consultant of: AbbVie, Gilead, Janssen, Eli Lilly, Novartis, Pfizer, UCB, Arvind Nune: None declared, Lorenzo Cavagna: None declared, Miguel A Saavedra Consultant of: AbbVie, GlaxoSmithKline, Samuel Katsuyuki Shinjo: None declared, Nelly Ziade Speakers bureau: AbbVie, Boehringer-Ingelheim, Eli Lilly, Janssen, Pfizer, Roche, Consultant of: AbbVie, Boehringer-Ingelheim, Eli Lilly, Janssen, Pfizer, Roche, Grant/research support from: AbbVie, Boehringer-Ingelheim, Eli Lilly, Janssen, Pfizer, Roche, Johannes Knitza: None declared, Oliver Distler Speakers bureau: AbbVie, Amgen, Bayer, Boehringer Ingelheim, Janssen, Medscape, Novartis, Consultant of: 4P-Pharma, AbbVie, Acceleron, Alcimed, Altavant, Amgen, AnaMar, Arxx, AstraZeneca, Baecon, Blade, Bayer, Boehringer Ingelheim, Corbus, CSL Behring, Galderma, Galapagos, Glenmark, Gossamer, iQvia, Horizon, Inventiva, Janssen, Kymera, Lupin, Medscape, Merck, Miltenyi Biotec, Mitsubishi Tanabe, Novartis, Prometheus, Redxpharma, Roivant, Sanofi, Topadur, Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Kymera, Mitsubishi Tanabe, Novartis, Roche, Hector Chinoy Grant/research support from: Eli Lilly, UCB, Vikas Agarwal: None declared, Rohit Aggarwal Consultant of: Mallinckrodt, Octapharma, CSL Behring, Bristol Myers-Squibb, EMD Serono, Kezar, Pfizer, AstraZeneca, Alexion, Argenx, Boehringer Ingelheim (BI), Corbus, Janssen, Kyverna, Roivant, Merck, Galapagos, Actigraph, Abbvie, Scipher, Horizontal Therapeutics, Teva, Biogen, Beigene, ANI Pharmaceutical, Nuvig, Capella, CabalettaBio, Grant/research support from: Bristol Myers-Squibb, Pfizer, Mallinckrodt, Janssen, Q32, EMD Serono, Boehringer Ingelheim, Latika Gupta: None declared.
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BackgroundThe second COVID-19 vaccination in autoimmune disease (COVAD-2) study [1] is an international, multicentre, self-reported e-survey designed to evaluate several facets covering COVID-19 infection and vaccination as well as validated patient-reported outcome measures (PROMs) in a variety of autoimmune diseases (AIDs), including systemic sclerosis (SSc). Detailed assessment of the health-related quality of life (HRQOL) and its drivers in patients with SSc is lacking.ObjectivesTo assess physical and mental health in a global cohort of SSc patients in comparison with non-SSc autoimmune inflammatory rheumatic diseases (AIRDs), non-rheumatic AIDs (NRAIDs), and those without AIDs (controls) using Patient-Reported Outcome Measurement Information System (PROMIS) global health data from the COVAD-2 survey.MethodsThe COVAD-2 database was used to extract demographics, AID diagnosis, comorbidities, disease activity, current therapies, and PROMs. PROMIS global physical health (GPH), global mental health (GMH) scores, PROMIS physical function short form-10a (PROMIS PF-10a), pain visual analogue scale (VAS), and PROMIS Fatigue-4a scores were compared between SSc, non-SSc AIRDs, NRAIDs, and controls. Outcomes were also compared between diffuse cutaneous SSc (dcSSc) vs limited cutaneous SSc (lcSSc). Multivariable regression analysis was performed to identify factors influencing GPH and GMH scores in SSc.ResultsA total of 10,502 complete responses from 276 SSc, 6006 non-SSc AIRDs, 545 NRAIDs, and 3675 controls as of May 2022 were included in the analysis. Respondents with SSc were older [SSc vs. non-SSc AIRDs vs. NRAIDs vs. controls: 55 (14) vs. 51 (15) vs. 45 (14) vs. 40 (14) years old, mean (SD), p < 0.001]. Among patients with SSc, 129 (47%) had dcSSc and 147 (53%) had lcSSc. SSc patients reported a significantly higher prevalence of ILD [SSc vs. non-SSc AIRDs vs. NRAIDs vs. controls: 30.4% vs. 5.5% vs. 1.5% vs. 0.2%, p < 0.001], and treatment with MMF [SSc vs. non-SSc AIRDs vs. NRAIDs vs. controls: 26.4% vs. 9.5% vs. 1.1% vs. 0%, p < 0.001].Patients with SSc had lower GPH and PROMIS PF-10a scores [SSc vs. non-SSc AIRDs vs. NRAIDs vs. controls: 13 (11–15) vs. 13 (11–15) vs. 15 (13–17) vs. 17 (15–18), median (IQR), p < 0.001;39 (33–46) vs. 39 (32–45) vs. 47 (40–50) vs. 49 (45–50), p < 0.001, respectively] and higher Pain VAS and PROMIS Fatigue-4a scores compared to those with NRAIDs or controls [SSc vs. non-SSc AIRDs vs. NRAIDs vs. controls: 3 (2–5) vs. 3 (1–6) vs. 2 (0–4) vs. 0 (0–2), p < 0.001;11 (8–14) vs. 11 (8–14) vs. 9 (7–13) vs. 7 (4–10), p < 0.001, respectively]. Patients with AIDs including SSc had lower GMH scores compared to controls [SSc vs. non-SSc AIRDs vs. NRAIDs vs. controls: 12.5 (10–15) vs. 13 (10–15) vs. 13 (11–16) vs. 15 (13–17), p < 0.001].Among SSc patients, GPH, GMH, and PROMIS PF-10a scores were lower in dcSSc compared to lcSSc [dcSSc vs. lcSSc: 12 (10–14) vs. 14 (11–15), p < 0.001;12 (10-14) vs. 13 (10-15), p<0.001;38 (30–43) vs. 41 (34–47), p < 0.001, respectively]. Pain VAS and PROMIS Fatigue-4a scores were higher in dcSSc compared to lcSSc [4 (2–6) vs. 3 (1–5), p < 0.001;12 (8–15) vs. 9 (8–13), p < 0.001, respectively].The independent factors for lower GPH scores in SSc were older age, Asian ethnicity, glucocorticoid use, and higher pain and fatigue scales, while mental health disorders and higher pain and fatigue scales were independently associated with lower GMH scores.ConclusionIn a global cohort, patient-reported physical and mental health were significantly worse in patients with SSc in comparison to those with non-SSc AIDs and without AIDs. Our findings support the critical need for more attention to patient's subjective experiences including pain and fatigue to improve the HRQOL in patients with SSc.Reference[1]Fazal ZZ, Sen P, Joshi M, et al. COVAD survey 2 long-term outcomes: unmet need and protocol. Rheumatol Int. 2022;42: 2151–58.Acknowledgements:NIL.Disclosure of InterestsKeina Yomono: None declared, Yuan Li: None dec ared, Vahed Maroufy: None declared, Naveen Ravichandran: None declared, Akira Yoshida: None declared, Kshitij Jagtap: None declared, Tsvetelina Velikova Speakers bureau: Pfizer and AstraZeneca, Parikshit Sen: None declared, Lorenzo Cavagna: None declared, Vishwesh Agarwal: None declared, Johannes Knitza: None declared, Ashima Makol: None declared, Dey Dzifa: None declared, Carlos Enrique Toro Gutierrez: None declared, Tulika Chatterjee: None declared, Aarat Patel: None declared, Rohit Aggarwal Consultant of: Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, Abbvie, Janssen, Kyverna Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, Roivant, Merck, Galapagos, Actigraph, Scipher, Horizon Therepeutics, Teva, Beigene, ANI Pharmaceuticals, Biogen, Nuvig, Capella Bioscience, and CabalettaBio, Grant/research support from: Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, Abbvie, Janssen, Kyverna Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, Roivant, Merck, Galapagos, Actigraph, Scipher, Horizon Therepeutics, Teva, Beigene, ANI Pharmaceuticals, Biogen, Nuvig, Capella Bioscience, and CabalettaBio, Latika Gupta: None declared, Masataka Kuwana Speakers bureau: Abbvie, Asahi-Kasei, Astellas, Boehringer-Ingelheim, Chugai, Eisai, MBL, Mochida, Nippon Shinyaku, Ono Pharmaceuticals, Tanabe-Mitsubishi, Consultant of: Astra Zeneka, Boehringer-Ingelheim, Chugai, Corbus, GSK, Horizon, Tanabe-Mitsubishi, Grant/research support from: Boehringer-Ingelheim, Vikas Agarwal: None declared.
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BackgroundThis study was aimed to investigate whether patients with epilepsy (PWE) have higher depression and anxiety levels than the normal population in low-risk areas for coronavirus disease 2019 (COVID-19) in the northern part of Guizhou Province, China, during the COVID-19 epidemic, to evaluate their knowledge on COVID-19, and to analyze related factors for the psychological distress of PWE at this special time.MethodsThe survey was conducted online from February 28, 2020 to March 7, 2020 via a questionnaire. PWE from the outpatient clinic of epilepsy of the Affiliated Hospital of Zunyi Medical University, and healthy people matched for age and sex, participated in this study. Mental health was assessed via a generalized anxiety self-rating scale (GAD-7) and the self-rating depression scale (PHQ-9). The knowledge of COVID-19 in both groups was investigated.ResultsThere were no significant differences in the general demographics between the PWE and healthy control groups. The scores of PHQ-9 (P < 0.01) and GAD-7 (P < 0.001) were higher in the PWE group than in the healthy group. There was a significant difference in the proportions of respondents with different severities of depression and anxiety, between the two groups, which revealed significantly higher degree of depression and anxiety in PWE than in healthy people (P = 0, P = 0). Overwhelming awareness and stressful concerns for the pandemic and female patients with epilepsy were key factors that affect the level of anxiety and depression in PWE. Further, the PWE had less accurate knowledge of COVID-19 than healthy people (P < 0.001). There was no statistically significant difference between the two groups in the knowledge of virus transmission route, incubation period, susceptible population, transmission speed, clinical characteristics, and isolation measures on COVID-19 (P > 0.05). PWE knew less about some of the prevention and control measures of COVID-19 than healthy people.ConclusionsDuring the COVID-19 epidemic, excessive attention to the epidemic and the female sex are factors associated with anxiety and depression in PWE, even in low-risk areas.
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Objective: to study the causes and predictors of mental disorders during the COVID-19 epidemic in those who turned to psychiatrist for the first time, as well as in patients with already diagnosed mental illness. Patients and methods. We examined 100 patients who turned to a psychiatrist due to a deterioration in their mental state during the pandemic, 50 patients were newly diagnosed (Group 1) and 50 with previously diagnosed mental disorders (Group 2). The study was carried out by a clinical method using a specially designed map, followed by statistical processing of the obtained data. Results and discussion. Mental disorders caused by the COVID-19 pandemic more often occurred at a young age, in patients with higher and secondary specialized education, and in single patients. In the 1st group, as a result of exposure to psychogenic factors (the influence of the media, quarantine, economic changes), anxiety (36.8%) and depressive (21.1%) disorders occurred more often, and after the coronavirus infection, depressive disorders were in the first place (54.2%). The 2nd group mostly included patients with endogenous disorders (bipolar affective disorder - 24%, recurrent depressive disorder - 20%, schizophrenia - 20%), which were exacerbated more often as a result of COVID-19, to a lesser extent - psychogenic (experiences associated with a change in material status and illness of relatives). Obsessive-compulsive disorder, generalized anxiety disorder, somatoform disorders have been associated with epidemic factors. Conclusion. The results obtained indicate that there are differences between the mental disorders that first appeared during the pandemic and the exacerbations of the condition in mentally ill patients, which relate to the predictors, causes and clinical manifestations of these disorders.Copyright © 2022 Ima-Press Publishing House. All rights reserved.
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Background The COVID-19 pandemic has had marked effects on mental health, including in pediatric populations. Pediatric patients have faced mental health concerns at increased rates including anxiety and depression. Furthermore, patients with eating disorders represent a vulnerable group who have been negatively impacted as well, as a result of lack of support, loss of in-person follow-up and increased relapse. In our centre, and nationally, clinicians have noted a trend towards increased eating disorder referrals and increased hospitalizations during the pandemic. Objectives The objective of this study was to determine the incidence, severity and triggers for eating disorders in the adolescent population during the COVID-19 pandemic and how it compares to the year prior. As well, the subset of patients who were hospitalized for medical stabilization were further analyzed to determine severity of illness. Design/Methods A retrospective chart review compared the first year of the COVID-19 pandemic (March 2020-March 2021), to the previous 12 months. Inclusion criteria included referrals to an eating disorder clinic and inpatient admissions to pediatrics or mental health services during the specified time frame. Data collected included age of onset, triggers, comorbid mental health conditions, and weight measures. Among hospitalized patients, orthostatic vital changes, need for NG feeds, length of medical stabilization and length of mental health hospitalization were included. Results Overall, 76 patients were included in the study. 44 (57.9%) were referred after COVID, which was significantly increased from the prior year (p=0.05). On average, patients presented at a younger age (14.2 ± 2.3 vs. 14.9 ± 1.9;p=0.08). Pre-COVID, approximately 44% of referrals were from family physicians and 19% from pediatrics. During COVID, approximately 39% were from family doctors and 25% from pediatricians. There was an increase in the number of patients requiring hospitalization for treatment (16 vs. 3), with 50% of the post-COVID admissions being direct from the ED Clinic on initial assessment. The reason for hospitalization was unstable vitals/ bradycardia in 68.7% of admissions;self-harm comprised the majority of the other admissions. Conclusion Our results support national and international reports that eating disorder incidence has increased during COVID-19. Patients described loss of routine, anxiety, and isolation as triggers related to the pandemic. Disruptions to daily life including school, sports, recreation, and relationships had profound effects on the mental health of children. The effect of social media on body image has also contributed. It is important for clinicians to screen for mental health conditions, including eating disorders at all available opportunities. Furthermore, this study demonstrates the need for increased services at our centre. Limitations for this study include that it is a single-centre study with a relatively small patient population. As well, it does not capture patients who may have been referred only to psychiatry.
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This study examined psychological health and coping strategies among faculty and staff at a Saudi Arabian university. A web-based self-administered survey was used to assess probable anxiety, depression, post-traumatic stress disorder (PTSD), and coping strategies by using the Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), Impact of Event Scale-Revised (IES-R), and Brief-COPE scale, respectively. Of 502 participants (mean age 36.04 ± 10.32 years, male: 66.3%), 24.1% (GAD-7 ≥ 10) had probable anxiety. Anxiety score was significantly higher in females (p < 0.001), those with a history of COVID-19 infection (p = 0.036), and participants with less work experience (p = 0.019). Approximately 40% of participants met the criteria of probable depression, with females (p < 0.001) and participants with less experience having more depressive symptoms. Around one-fourth (27.7%) of study participants indicated probable PTSD (score ≥ 33), with higher symptoms in females (p <0.001), less experienced staff (p < 0.001), and academic staff (p = 0.006). Correlation analysis indicated a significant positive correlation between anxiety and depression (r = 0.844, p < 0.001), anxiety and PTSD (r = 0.650, p < 0.001), and depression and PTSD (r = 0.676, p < 0.001). Active coping, religious/spiritual coping, and acceptance were common coping strategies, while substance use was the least adopted coping method among the study participants. This study indicated a high prevalence of probable psychological ailments among university staff.
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Objective To investigate the characteristics of post-traumatic stress disorder (PTSD) in college students during the outbreak of COVID-19, and to explore the mediating role of psychological resilience between social support and PTSD. Methods By using direct selection method, 572 college students in Anhui and Shanghai were selected and administered with General Characteristics Questionnaire, the PTSD Checklist-Civilian Version(PCL-C), Psychological Resilience Scale(PRS) and Social Support Rating Scale(SSRS). Results Among the participants, 25.0% had moderate PTSD symptoms, 11.7% had obvious PTSD symptoms, and the positive rate of PTSD was 36.7%. The prevalence of PTSD in college students was higher in males than in females (X2=4.31, P < 0.05). The junior students were higher than other students (X2=16.81, P < 0.01). The scores of social support, psychological resilience and PTSD were (33.79+or-4.83), (92.17+or-13.39) and (35.50+or-11.39), respectively. The correlations of all variables were statistically significant(r=-0.49-0.76, P < 0.05);The mediation test showed that social support could not only negatively predict PTSD directly(direct effect was -0.35), but also indirectly affect PTSD through psychological resilience(indirect effect was -0.32). Conclusion More than one third of college students have PTSD symptoms, and psychological resilience plays a partial mediating role in the relationship between social support and PTSD, social support can both directly and negatively predict PTSD and indirectly affect PTSD by increasing an individual's psychological resilience.
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The novel coronavirus SARS-CoV-2 is associated with a significant incidence of neuropsychiatric disorders, which tend to have a long course in the post-COVID period. Objective(s): to study post-COVID mental disorders in clinical psychiatric practice. Patients and methods. 30 patients aged 37.75+/-14.07 years with anamnesis of SARS-CoV-2 infection were examined. Clinical scale assessment was carried out using the Hamilton Depression and Anxiety Scale. The Symptom-Checklist (SCL-90-R) was used to assess the psychopathological status of the patient. Patients' cognitive functioning was assessed using the Mini-Cog Cognitive Assessment Questionnaire. Patients' sleep quality was assessed by the Pittsburgh Sleep Quality Index (PSQI). Results and discussion. Mental disorders associated with a previous coronavirus infection are observed in a wide time range from less than 1 month to a year after the previous disease, and in no case did the coronavirus infection have a severe course. Sleep disorders, anxiety and depressive disorders, which did not exceed a moderate degree of severity, and asthenia dominated in the structure of the post-COVID syndrome. The level of mental distress in patients with post-COVID syndrome increased 2 times. Post-COVID mental disorders are interrelated with female gender, age, and psychotraumatic factors associated with the pandemic. Cognitive impairment mediated by mental disorders was observed in approximately 60% of patients and did not reach the degree of dementia. Conclusion. The clinical picture of the post-COVID syndrome is represented by a wide range of mental disorders, the development of which involves not only biological, but also psychosocial factors associated with the COVID-19 pandemic, which determines the specifics of diagnostic approaches and the feasibility of complex treatment of the post-COVID syndrome.Copyright © 2022 Ima-Press Publishing House. All rights reserved.
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With an aging population, health professionals will face a growing cohort of older patients presenting with neurological and psychiatric disorders. The aging process is associated with an increase in chronic medical conditions, sensory impairments, cognitive and functional decline, and bereavement, all of which can impact psychological wellbeing. The COVID-19 pandemic has presented further, unique challenges for vulnerable older people, although preliminary findings have indicated that older adults have actually been more resilient than younger people in terms of developing mental health conditions during the pandemic. In the present chapter, an overview of common psychiatric disorders in late adulthood is provided, in addition to recommendations for assessment and treatment planning. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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The coronavirus pandemic is a global health emergency which has had widespread unforeseen mental health consequences. Those with borderline personality disorder are predisposed to poor coping strategies to manage such stress and require intense psychological input which was not widely available during the peak of the pandemic. It is likely that the coronavirus outbreak has had a significant impact on the mental stability of such patients aggravating deliberate self-harm behaviours. A 20-year old psychiatric in-patient with borderline personality disorder, held under Section III of the mental health act, presented to the adult plastic surgery team in Bristol with localised infection of her right forearm. Foreign bodies were easily palpable and imaging revealed linear metal objects. The patient reported that she had removed metal strips from her collection of face masks and inserted them into her forearm as an act of deliberate self-harm. The patient was taken to operating theatre for removal of these foreign bodies under general anaesthetic. After twenty-four hours of antibiotics she was discharged safely back to the psychiatric ward. Despite the epilogue of the COVID-19 pandemic facemasks are still mandatory within the hospital setting. Clinicians need to be aware of these unusual circumstances where a form of protective equipment was deconstructed to cause actual bodily harm. The purpose of this report is to promote awareness of this type of injury especially in those suffering from mental illness. The authors would suggest an alternative mask without any form of metal.
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Pregnancy and the entire mothering process is always a very big challenge, which involves physical and emotional changes in women. Currently, with the numbers of cases confirmed by COVID-19 growing every day in our city, everything is uncertain. This whole scenario brought many anxieties, concerns and ques- tions. This is no different with pregnant women, on the contrary, their fears and anxieties have multiplied during this period. The project, through a field study, aimed to assess the emotional state of the pregnant woman in relation to the pandemic COVID-19. A quantitative research was carried out, with the application of a virtual questionnaire prepared by the author herself. 39 pregnant women who are monitoring their prenatal care at a clinic in the city of Tres Coracoes - MG were interviewed. The research appli- cation was released with an opinion embodied under the number of CAAE 39410820.9.0000.5158 and authorization from the res- ponsible nurse, where the contact phones of the pregnant women were noted so that the questionnaire could be applied in a virtual way, through the Google Forms platform, after the term agree- ment. It was found that psychological disorders appeared in 51.3% of the study population and 48.7% who already had some disorder such as anxiety and depression stated that their clinical condition worsened with the pandemic. This target audience is a group considered at risk by the World Health Organization. It should be given full support and support, through guidance on preventive measures and complete assistance by a multidiscipli- nary team.
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In the new millennium, humanity has faced with a global challenge in the form of the novel coronavirus infection (COVID-19). In addition to systemic and respiratory symptoms, SARS-CoV-2 causes neurological disorders, as it is a neurotropic virus. Many scientists assume that SARS-CoV-2 can enter the nervous system through the functional receptor of angiotensin-converting enzyme 2, which is present in glial cells, neurons, skeletal muscles, and other organs. Neurological complications are manifested by damage to the central nervous system, peripheral nervous system, and cranial nerves, as well as by mental disorders. Mental illnesses develop due to neuroinflammation and neuronal death after brain infection with SARS-CoV-2. The article describes a clinical case of a 63-year-old man with the co-occurring novel coronavirus infection and obvious mental disorder who has never had any mental illnesses before. The given clinical example demonstrates the importance of studying the cause-and-effect relationship between COVID-19 and mental illness. In the medium- and long-term perspective, COVID-19 is expected to result in mental health disorders during COVID-19 recovery. Besides, an increase in the number of patients with mental disorders who were mentally healthy before COVID-19 infection is also expected. © 2023 Authors. All rights reserved.
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The World Health Organization defines Mental Health as "a state of well-being in which every individual realizes (their) own potential, can cope with the normal stresses of life, can work productively and fruitfully, and is able to make a contribution to (their) community." [8,9] According to a study conducted by National Council for Mental Health in India, at least 6.5% of the nation's population are suffering from some form of mental disorder, with no detectable urbanrural differences. Overall mental distress of medical students is significantly higher than that of general population and it may impact their academic performance/14,15 In a study titled "Stress, anxiety, and depression among medical undergraduate students and their socio-demographic correlates" published in Indian journal of medical research, VoL 141, March, 2015, more than 50% of the respondents, who were the MBBS students from Institute of Medical Sciences at Bhubaneswar, Odisha, India, were affected by depression (51.3%), anxiety (66.9%) and stress (53%). With this background, we undertook this study among the undergraduate students of Medical College, Kolkata with the objectives of finding out socio-demographic, behavioral and academic profile of the undergraduate medical students of Medical College, Kolkata, to estimate the proportion of different types of mental distress among them, and to examine relationship of mental distress with sociodemographic, behavioral, and academic profile.
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Objective: To investigate the relationship between negative attentional bias and post-traumatic stress disorder(PTSD) in the context of higher depression and anxiety symptoms after the outbreak of COVID-19, so as to provide scientific basis for mental health education in primary and secondary schools. Methods: From March to April 2021, a total of 708 students from primary school and junior high school (grade 6 through grade 9) in Beijing, Shanxi, Hunan, Shandong, Hebei, Hubei of China were selected. The Children's Revised Impact of Event Scale(CRIES), the Attention to Positive and Negative Information Scale (APNI)and Depression, Anxiety and Stress Scale-21(DASS-21) were used in a questionnaire survey. Results: A total of 242 students were diagnosed with PTSD, and the detection rate was 34.2%. The scores of intrusion and high arousal of boys(7.92+or-5.33, 8.60+or-5.41) were lower than those of girls(8.72+or-4.85, 9.50+or-4.76), and the difference was statistically significant (t=-2.04, -2.32, P < 0.05). There were statistically significant differences of negative attention bias, CRIES score, intrusion, debarb and high arousal among primary and middle school students of different grades (F=3.57, 5.99, 4.45, 4.60, 7.40, P < 0.05). Negative attention bias, anxiety, depression and post-traumatic stress symptoms were significantly positively correlated (r=0.27-0.84, P < 0.05). Logistic regression analysis showed that anxiety (OR=1.13, 95%CI=1.06-1.20) and negative attention bias (OR=1.10, 95%CI=1.07-1.12) were positively associated with PTSD symptoms in primary and middle school students(P < 0.01). Conclusion: Anxiety and depressive symptoms show impacts on negative attention bias and might exacerbate the symptoms of post-traumatic stress disorder. Therefore, emotional adjustments can help reduce the post-traumatic stress response in the post-epidemic period.
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Background. Nurses' high workload can result in depressive symptoms. However, the research has underexplored the internal and external variables, such as organisational support, career identity, and burnout, which may predict depressive symptoms among Chinese nurses via machine learning (ML). Aim. To predict nurses' depressive symptoms and identify the relevant factors by machine learning (ML) algorithms. Methods. A self-administered smartphone questionnaire was delivered to nurses to evaluate their depressive symptoms;1,431 questionnaires and 28 internal and external features were collected. In the training set, the use of maximum relevance minimum redundancy ranked the features' importance. Five ML algorithms were used to establish models to identify nurses' depressive symptoms using different feature subsets, and the area under the curve (AUC) determined the optimal feature subset. Demographic characteristics were added to the optimal feature subset to establish the combined models. Each model's performance was evaluated using the test set. Results. The prevalence rate of depressive symptoms among Chinese nurses was 31.86%. The optimal feature subset comprised of sleep disturbance, chronic fatigue, physical fatigue, exhaustion, and perceived organisation support. The five models based on the optimal feature subset had good prediction performance on the test set (AUC: 0.871–0.895 and accuracy: 0.798–0.815). After adding the significant demographic characteristics, the performance of the five combined models slightly improved;the AUC and accuracy increased to 0.904 and 0.826 on the test set, respectively. The logistic regression analysis results showed the best and most stable performance while the univariate analysis results showed that external and internal personal features (AUC: 0.739–0.841) were more effective than demographic characteristics (AUC: 0.572–0.588) for predicting nurses' depressive symptoms. Conclusions. ML could effectively predict nurses' depressive symptoms. Interventions to manage physical fatigue, sleep disorders, burnout, and organisational support may prevent depressive symptoms.
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The COVID-19 epidemic has caused serious and long-lasting health and social harm. Vaccination is considered as the most effective way to prevent the COVID-19 epidemic. Patients with mental disorders are at high risk of COVID-19 infection who are in urgent need to get protection. However, due to the particularity of their conditions, whether these patients should be vaccinated has become a tough issue that obsesses doctors, patients with mental disorders, and their families. In light of this issue, this article provides expert advice on the safety, legal and ethical issues of vaccination for patients with mental disorders to regulate the vaccination of these vulnerable populations against COVID-19.Copyright © 2022 Chinese Journal of Psychiatry. All rights reserved.
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Introduction: Confinement has had a great emotional impact on the population, especially in terms of stress. Factors such as the presence of previous mental or physical illness, resilience or emotional intelligence may influence the occurrence or increase of stress. The aim was to assess predictors of stress by comparing two statistical methodologies (one linear and one non-linear). Method: 802 Spaniards (65.50% women) who completed the questionnaires autonomously after signing the informed consent form participated. Stress (PSPP), COVID-19 threat perception (BIPQ-5), resilience (CD-RISC-10) and emotional intelligence (TMMS-24) were assessed. Descriptive statistics, hierarchical regression (HRM) and fuzzy set comparative qualitative analysis (fsQCA) were conducted. Results: Data obtained by HRM showed that the presence of previous mental illness, low resilience and emotional clarity, high emotional alertness and COVID-19 threat perception predicted 51% of the variance in stress. On the other hand, the results of the QCA showed that different combinations of these variables explained 71% of high stress and 56% of low stress. Pointing out how the presence of previous mental illness, high resilience, high emotional clarity and repair, low emotional alertness and low COVID-19 threat perception play a key role in explaining stress. Conclusions: These aspects will help to promote personal resources to buffer stress in confinement situations. (PsycInfo Database Record (c) 2023 APA, all rights reserved) (Spanish) Introduccion: El confinamiento ha supuesto un gran impacto emocional en la poblacion observandose, especialmente, el padecimiento de estres. Factores como la presencia de enfermedades mentales o fisicas previas, la resiliencia o la inteligencia emocional, pueden influir en la aparicion o el aumento del estres. El objetivo fue evaluar los predictores del estres mediante la comparacion de dos metodologias estadisticas (una lineal y otra no lineal). Metodo: Participaron 802 espanoles (65,50% mujeres), que rellenaron de manera autonoma los cuestionarios tras la firma del consentimiento informado. Se valoro el estres (PSPP), la percepcion de amenaza del COVID-19 (BIPQ- 5), la resiliencia (CD-RISC-10) y la inteligencia emocional (TMMS-24). Se llevaron a cabo estadisticos descriptivos, regresiones jerarquicas (MRJ) y analisis cualitativos comparativos de conjuntos difusos (fsQCA). Resultados: Los datos obtenidos por MRJ evidenciaron que la presencia de una enfermedad mental previa, una baja resiliencia y claridad emocional, una alta atencion emocional y percepcion de amenaza del COVID-19, predijeron el 51% de la varianza del estres. Por su parte, los resultados del QCA mostraron que las diferentes combinaciones de estas variables explicaron el 71% de los casos de altos niveles de estres y, el 56%, de los bajos niveles de estres, senalando como la presencia de una enfermedad mental previa, la alta resiliencia, la alta claridad y reparacion emocional, la baja atencion emocional y la baja percepcion de amenaza del COVID-19, juegan un papel fundamental en la explicacion del estres. Conclusiones: Estos aspectos ayudaran a promover los recursos personales para amortiguar el estres en situaciones de confinamiento. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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Objective: The study aimed at identifying the influence of socio-demographic factors on perceived stress during the first and the second "waves" of the COVID-19 pandemic among patients with depression and anxiety in remission compared to controls. Method: The study was designed as case-control, cross-sectional and non-interventional, and included 60 outpatients with depressive and anxiety disorders in remission and 60 controls with or without family history of affective disorder. A self-assessment scale (Perceived Stress Scale, PSS-10) was used to evaluate perceived stress. The remission was objectified by the Clinical Global Impression scale (CGI-S 2) and a questionnaire about the socio-demographic features and clinical characteristics of the disorders was completed. Results: By using multiple logistic regression, it was found that the diagnostic category and/or the relevant family history did not predict higher levels of perceived stress during the COVID-19 pandemic (p > 0.05). Females were associated with higher risk of moderate or high stress (OR=2.613, p=0.017), as well as those working from home during the pandemic (OR=4.00, p=0.026). Conclusions: Addressing the COVID-19 effects on mental health in a biopsychosocial manner, the study shows the impact of socio-demographic factors such as gender and work environment in times of a psychosocial crisis. The lack of differences in stress perception by the patients in remission and healthy controls implicates the importance of adequate maintenance treatment and easy access to mental health services in times of crisis.
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In the new millennium, humanity has faced with a global challenge in the form of the novel coronavirus infection (COVID-19). In addition to systemic and respiratory symptoms, SARS-CoV-2 causes neurological disorders, as it is a neurotropic virus. Many scientists assume that SARS-CoV-2 can enter the nervous system through the functional receptor of angiotensin-converting enzyme 2, which is present in glial cells, neurons, skeletal muscles, and other organs. Neurological complications are manifested by damage to the central nervous system, peripheral nervous system, and cranial nerves, as well as by mental disorders. Mental illnesses develop due to neuroinflammation and neuronal death after brain infection with SARS-CoV-2. The article describes a clinical case of a 63-year-old man with the co-occurring novel coronavirus infection and obvious mental disorder who has never had any mental illnesses before. The given clinical example demonstrates the importance of studying the cause-and-effect relationship between COVID-19 and mental illness. In the medium- and long-term perspective, COVID-19 is expected to result in mental health disorders during COVID-19 recovery. Besides, an increase in the number of patients with mental disorders who were mentally healthy before COVID-19 infection is also expected.