Machine learning predictive modeling of the persistence of post-Covid19 disorders: Loss of smell and taste as case studies.

The worldwide health crisis triggered by the novel coronavirus (COVID-19) epidemic has resulted in an extensive variety of symptoms in people who have been infected, the most prevalent disorders of which are loss of smell and taste senses. In some patients, these disorders might occasionally last for several months and can strongly affect patients' quality of life. The COVID-19-related loss of taste and smell does not presently have a particular therapy. However, with the help of an early prediction of these disorders, healthcare providers can direct the patients to control these symptoms and prevent complications by following special procedures. The purpose of this research is to develop a machine learning (ML) model that can predict the occurrence and persistence of post-COVID-19-related loss of smell and taste abnormalities. In this study, we used our dataset to describe the symptoms, functioning, and disability of 413 verified COVID-19 patients. In order to prepare accurate classification models, we combined several ML algorithms, including logistic regression, k-nearest neighbors, support vector machine, random forest, extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM). The accuracy of the loss of taste model was 91.5 % with an area-under-cure (AUC) of 0.94, and the accuracy of the loss of smell model was 95 % with an AUC of 0.97. Our proposed modelling framework can be utilized by hospitals experts to assess these post-COVID-19 disorders in the early stages, which supports the development of treatment strategies.

Acute and long COVID-19 symptoms and associated factors in the omicron-dominant period: a nationwide survey via the online platform Wenjuanxing in China.

BACKGROUNDS: To our knowledge, there is no available nationwide data on omicron symptom patterns in China mainland. We aim to determine the acute and long COVID-19 symptoms in the omicron-dominant period and to evaluate its association with risk factors. METHODS: We designed a cross-sectional nationwide study and data about self-reported symptoms were collected by an online platform named Wenjuanxing. Eligible participants were aged 25-65 years and were symptomatic. In this study, the ratios of the number of people of different ages and genders were weighted by the data from the Seventh National Census (2020 years), and validated by a published nationwide representative study through comparing smoking rates. Descriptive indicators were calculated for demographic characteristics, diagnosis ways, and duration time, acute symptoms, hospitalization, severity and long COVID-19 symptoms. And, the associations between risk factors and acute and long COVID-19 symptoms were analyzed by multivariable logistic regression models. RESULTS: A total of 32,528 individuals diagnosed as COVID-19 infection from October 1, 2022 to February 21, 2023 were included. The first three acute symptoms of COVID-19 infection were fever (69.90%), headache (62.63%), and sore throat (54.29%), respectively. The hospitalization rate within 7 days was 3.07% and symptoms disappearance rate within 21 days was 68.84%, respectively. Among 3983 COVID-19 patients with 3 months or more time difference between first infection and participation into the study, the long COVID-19 rate was 19.68% and the primary symptoms were muscle weakness (19.39%), headache (17.98%) and smell/taste disorder (15.18%). Age groups, smoking, marriage status and vaccination were risk factors for numbers of acute phase symptoms and long COVID-19 symptoms. Lastly, female and current smokers also showed more numbers of symptoms during acute infection period. CONCLUSIONS: In Chinese mainland, our respondent indicated that current smokers and women were associated with acute COVID-19 symptoms, which should be treated with caution due to the lack of representative.

Effects of vaccination on COVID-19 infection symptoms in multiple sclerosis patients.

Background: Patients with multiple sclerosis (MS) are at higher risk of having infections due to receiving disease modifying therapies. The current study was conducted among Iranian MS patients who had experienced at least one episode of COVID-19 infection in order to evaluate the effects of COVID-19 vaccination on symptoms of their infection. Data on demographic information, MS characteristics, COVID-19 infection details, and vaccination status were collected. Statistical analyses, were performed to evaluate the association between vaccination and symptoms of COVID-19 infection. Methods: This cross-sectional study was conducted on confirmed MS patients. Demographic data and COVID-19 related symptoms were gathered via an online questionnaire. Confirmation of patients' who declared to be vaccinated was checked by their COVID-19 vaccination card. Results: A total of 236 MS patients participated in the study. The majority were female (79.7%), with a mean age of 36.1 ± 7.9 years. Among the participants, 72.5% had received the COVID-19 vaccine before their first episode of COVID-19 infection. The analysis showed a significant difference in the incidence of respiratory symptoms (P-value: 0.01) and headache (P-value: 0.04) between vaccinated and non-vaccinated individuals. Logistic regression analysis revealed that vaccinated MS patients had lower odds of developing respiratory symptoms (OR:0.29, 95% CI: 0.16 to 0.53, P-value<0.001) or headache (OR: 0.50, 95% CI: 0.25 to 0.98, P-value: 0.04) during their next COVID-19 infection episode. Moreover, MS patients who were receiving immunosuppressive drugs were less likely to have respiratory symptoms (OR:0.35, 95% CI: 0.16 to 0.77, P-value:0.009) but not headache (OR: 0.69, 95% CI: 0.30 to 1.60, P-value: 0.39). Conclusion: COVID-19 vaccination can reduce the incidence of respiratory symptoms and headaches in MS patients during COVID-19 infection episodes. Additionally, patients who are receiving immunosuppressive drugs may benefit from COVID-19 vaccination.

Precision symptom phenotyping identifies early clinical and proteomic predictors of distinct COVID-19 sequelae.

BACKGROUND: Post-COVID conditions (PCC) are difficult to characterize, diagnose, predict, and treat due to overlapping symptoms and poorly understood pathology. Identifying inflammatory profiles may improve clinical prognostication and trial endpoints. METHODS: 1,988 SARS-CoV-2 positive U.S. Military Health System beneficiaries with quantitative post-COVID symptom scores were included in this analysis. Among participants who reported moderate-to-severe symptoms on surveys collected 6-months post-SARS-CoV-2 infection, principal component analysis (PCA) followed by K-means clustering identified distinct clusters of symptoms. RESULTS: Three symptom-based clusters were identified: a sensory cluster (loss of smell and/or taste), a fatigue/difficulty thinking cluster, and a difficulty breathing/exercise intolerance cluster. Individuals within the sensory cluster were all outpatients during their initial COVID-19 presentation. The difficulty breathing cluster had a higher likelihood of obesity and COVID-19 hospitalization compared to those with no/mild symptoms at 6-months post-infection. Multinomial regression linked early post-infection D-dimer and IL-1RA elevation to fatigue/difficulty thinking, and elevated ICAM-1 concentrations to sensory symptoms. CONCLUSIONS: We identified three distinct symptom-based PCC phenotypes with specific clinical risk factors and early post-infection inflammatory predictors. With further validation and characterization, this framework may allow more precise classification of PCC cases and potentially improve the diagnosis, prognostication, and treatment of PCC.

Impulse oscillometry in patients with persistent post-COVID-19 symptoms: A retrospective study.

Introduction: Impaired lung function has been observed in patients following COVID-19 infection, with studies reporting persistent lung volume and diffusing capacity impairments. Some studies have demonstrated significantly higher small airway resistance in COVID-19 positive cases. This retrospective study aims to examine impulse oscillometry (IOS) data of patients with persistent symptoms after COVID-19 infection, focusing on the relationship between time and symptoms. Material and Method: The study analyzed data from adult patients with persistent symptoms who underwent IOS testing within and after 84 days from the diagnosis date. Result: The results showed that patients within 84 days and those between 31 and 84 days had higher small airway resistance values, indicating peripheral airway disease. Patients with dyspnea exhibited higher IOS values compared to those with cough symptoms, suggesting more significant impairment in the peripheral airways. Conclusion: The study highlights the importance of using comprehensive diagnostic tools like IOS to assess respiratory impairments in post-COVID-19 patients, particularly in the small airways. Understanding the relationship between time and symptoms can provide valuable insights for the treatment of peripheral airway dysfunction in post-COVID-19 patients.

Persistence of COVID-19 Symptoms and Quality of Life at Three and Twelve Months after Hospital Discharge.

Background and Objectives: Medical and public recognition of "long-COVID or post-COVID syndrome", as well as its impact on the quality of life (QoL), is required to better address the disease burden. Objectives: We aimed to describe the persistence of COVID-19 symptoms and QoL among patients at three and twelve months after their discharge from the hospital. Materials and Methods: We conducted an observational, prospective, and longitudinal analytic study from September 2021 to April 2022. To measure QoL, we used a validated version of the 36-item Short-Form Health Survey (SF-36). Results: We included 68 patients in the study. A total of 54 (79.4%) patients reported at least one persistent symptom at three months vs. 52 (76.4%) at twelve months (p = 0.804). Some persistent symptoms (myalgia, alopecia, and cough) decreased significantly at twelve months (50% vs. 30.9%, 29.4% vs. 13.2%, and 23.5% vs. 7.4%; respectively, p = 0.007); in contrast, other persistent symptoms (sleep-wake and memory disorders) were more frequent (5.9% vs. 32.4% and 4.4% vs. 20.6%; respectively, p = ≤0.001). Regarding QoL, a statistically significant improvement was observed in some scores over time, p = ≤0.037. At twelve months, dyspnea, myalgia, and depression were risk factors associated with a poor physical component summary (PCS), p = ≤0.027, whereas anxiety, depression, and fatigue were associated with a poor mental component summary (MCS), p = ≤0.015. Conclusion: As the proportion of persistent symptoms at twelve months is high, we suggest that patients must continue under long-term follow up to reclassify, diagnose, and treat new onset symptoms/diseases.

The Assessment of Functional Status Among COVID-19 Patients at Three Months Using Pulmonary Function Tests.

Introduction The coronavirus disease 2019 (COVID-19) pandemic has impacted the lives of thousands of patients worldwide with many patients having residual symptoms months after the acute infection. The severity of lung involvement ranges from mild asymptomatic to severe acute respiratory distress syndrome (ARDS), which may lead to pulmonary fibrosis. Pulmonary fibrosis increases the long-term morbidity of post-COVID-19 patients in the form of restrictive lung disease. The six-minute walk test (6MWT), Borg scale, and spirometry are simple and low-cost tests used to evaluate a patient's exercise capacity and functional status. This study was conducted to assess the residual symptoms and functional status using spirometry and 6MWT in COVID-19 patients of moderate to severe category after three months of discharge. Methods This was an observational, prospective, and cross-sectional study conducted at a tertiary care center in North India, aiming to enroll a minimum of 50 patients who recovered from COVID-19 pneumonia. These patients were previously hospitalized with moderate to severe disease severity as defined by the Indian Council of Medical Research (ICMR) criteria, and the assessment occurred at least three months after their discharge. Individuals who were under 18 years of age or pregnant or had any respiratory or cardiac illness in the past were excluded from the study. Results A total of 50 patients were included in the study for final analysis. After a three-month follow-up, 40 (80%) patients were still symptomatic. The most commonly reported symptom was exertional dyspnea in 21 (42%), dyspnea at rest in 16 (32%), and fatigue in three (6%) patients. Of the total patients, 37 (74%) covered a distance less than expected in the six-minute walk test. The mean distance covered by patients was 426.1 ± 115.01 m, in contrast to the expected mean distance of 537.22 ± 37.61 m according to standard equations for Indian males and females. A fall in oxygen saturation by more than or equal to 3% was observed in approximately 24 (48%) patients after the six-minute walk test. The mean value of fatigue and dyspnea score was 3.2 ± 1.7 (moderate score). Among patients with moderate disease during their hospital stay, a higher proportion exhibited a normal pattern on pulmonary function tests (PFT) compared to those severely affected, 23 (69.70%) versus two (11.76%), respectively. Conclusion The persistence of symptoms and functional limitation of activities should be anticipated in patients with COVID-19. Spirometry and 6MWT can be a valuable tool in determining the prevalence of functional limitation in recovered patients of COVID-19. It can potentially help in determining and further planning the rehabilitative measures in the management of COVID-19 survivors. It can also be concluded that it is important to have a long-term follow-up in patients with moderate to severe COVID-19.

Long term follow-up of heart rate variability in healthcare workers with mild COVID-19.

Introduction: Prior investigations into post-COVID dysautonomia often lacked control groups or compared affected individuals solely to healthy volunteers. In addition, no data on the follow-up of patients with SARS-CoV-2-related autonomic imbalance are available. Methods: In this study, we conducted a comprehensive clinical and functional follow-up on healthcare workers (HCWs) with former mild COVID-19 (group 1, n = 67), to delineate the trajectory of post-acute autonomic imbalance, we previously detected in a case-control study. Additionally, we assessed HCWs for which a test before SARS-CoV-2 infection was available (group 2, n = 29), who later contracted SARS-CoV-2, aiming to validate findings from our prior case-control investigation. We evaluated autonomic nervous system heart modulation by means of time and frequency domain heart rate variability analysis (HRV) in HCWs during health surveillance visits. Short-term electrocardiogram (ECG) recordings, were obtained at about 6, 13 months and both at 6 and 13 months from the negative SARS-CoV-2 naso-pharyngeal swab (NPS) for group 1 and at about 1-month from the negative NPS for group 2. HCWs who used drugs, had comorbidities that affected HRV, or were hospitalized with severe COVID-19 were excluded. Results: Group 1 was split into three subgroups clinically and functionally followed at, about 6 months (subgroup-A, n = 17), 13 months (subgroup-B, n = 37) and both at 6 and 13 months (subgroup-C, n = 13) from the negative SARS-CoV-2 NPS. In subgroup-A, at 6-month follow-up compared with baseline, the spectral components in the frequency domain HRV parameters, showed an increase in normalized high frequency power (nHF) (t = 2.99, p = 0.009), a decrease in the normalized low frequency power (nLF) (t = 2.98, p = 0.009) and in the LF/HF ratio (t = 3.13, p = 0.006). In subgroup B, the comparison of the spectral components in the frequency domain HRV parameters, at 13-month follow-up compared with baseline, showed an increase in nHF (t = 2.54, p = 0.02); a decrease in nLF (t = 2.62, p = 0.01) and in the LF/HF ratio (t = 4.00, p = 0.0003). In subgroup-C, at both 6 and 13-month follow-ups, the spectral components in the frequency domain HRV parameters were higher than baseline in nHF (t = 2.64, p = 0.02 and (t = 2.13, p = 0.05, respectively); lower in nLF (t = 2.64, p = 0.02 and (t = 2.13, p = 0.05, respectively), and in LF/HF (t = 1.92, p = 0.08 and (t = 2.43, p = 0.03, respectively). A significant proportion of HCWs reported persistent COVID-19 symptoms at both the 6 and 13-month follow-ups, seemingly unrelated to cardiac autonomic balance. In group 2 HCWs, at 1-month follow-up compared with baseline, the spectral components in the frequency domain HRV parameters, showed a decrease in nHF (t = 2.19, p = 0.04); an increase in nLF (t = 2.15, p = 0.04) and in LF/HF (t = 3.49, p = 0.002). Conclusion: These results are consistent with epidemiological data suggesting a higher risk of acute cardiovascular complications during the first 30 days after COVID-19. The SARS-CoV-2 associated autonomic imbalance in the post-acute phase after recovery of mild COVID-19 resolved 6 months after the first negative SARS-CoV-2 NPS. However, a significant proportion of HCWs reported long-term COVID-19 symptoms, which dot not seems to be related to cardiac autonomic balance. Future research should certainly further test whether autonomic imbalance has a role in the mechanisms of long-COVID syndrome.

The severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) omicron sub-variants in Bangladesh cause mild COVID-19 and associate with similar antibody responses irrespective of natural infection or vaccination history.

Objective: Genomic surveillance and seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) in Bangladesh is paramount for COVID-19 pandemic preparedness yet lagging the high-income countries due to limited resources. Methods: SARS-CoV-2 variants, COVID-19 symptoms, and serology were prospectively evaluated in a cross-sectional study of Bangladeshi adults testing RT-PCR positive in 2021 and 2022. Results: SARS CoV-2 Omicron variants of asymptomatic or mild COVID-19 in 2022 replaced Delta variant infections requiring hospitalization and oxygen support. The omicron XBB became predominant in July 2022 and associated with cough, headache or body ache and loss of smell; 47 of 68 (69 %), 30 of 68 (44 %) and 27 of 68 (40 %) respectively at higher frequency than BA.1/BA.2; 16 of 88 (18 %), 13 of 88 (15 %) and 0 of 88 (0 %) p < 0.01, p < 0.01 and p < 0.0001. Linear regression analysis reveals no associations between the number of previous infections and the number of symptoms, r = -0.084, p = 0.68. The anti-nucleoprotein (N)-protein IgG post COVID-19 and anti-Spike (S) protein IgG post-COVID-19 vaccination were similar between BA.2, BA.4/BA.5 and XBB and significantly lower than the levels in delta variant infections (p < 0.001). Conclusions: Omicron XBB subvariants emerged in Bangladesh two months prior to previous reports and include unique patterns of S-protein mutations not assigned in PANGO lineage. The SARS CoV-2 omicron break-through infections persist in the presence of sustained antibody responses and vaccinations, underscoring the importance of molecular surveillance in low-income countries.

Elevated Troponins after COVID-19 Hospitalization and Long-Term COVID-19 Symptoms: Incidence, Prognosis, and Clinical Outcomes-Results from a Multi-Center International Prospective Registry (HOPE-2).

Background: Acute cardiac injury (ACI) after COVID-19 has been linked with unfavorable clinical outcomes, but data on the clinical impact of elevated cardiac troponin on discharge during follow-up are scarce. Our objective is to elucidate the clinical outcome of patients with elevated troponin on discharge after surviving a COVID-19 hospitalization. Methods: We conducted an analysis in the prospective registry HOPE-2 (NCT04778020). Only patients discharged alive were selected for analysis, and all-cause death on follow-up was considered as the primary endpoint. As a secondary endpoint, we established any long-term COVID-19 symptoms. HOPE-2 stopped enrolling patients on 31 December 2021, with 9299 patients hospitalized with COVID-19, of which 1805 were deceased during the acute phase. Finally, 2382 patients alive on discharge underwent propensity score matching by relevant baseline variables in a 1:3 fashion, from 56 centers in 8 countries. Results: Patients with elevated troponin experienced significantly higher all-cause death during follow-up (log-rank = 27.23, p < 0.001), and had a higher chance of experiencing long-term COVID-19 cardiovascular symptoms. Specifically, fatigue and dyspnea (57.7% and 62.8%, with p-values of 0.009 and <0.001, respectively) are among the most common. Conclusions: After surviving the acute phase, patients with elevated troponin on discharge present increased mortality and long-term COVID-19 symptoms over time, which is clinically relevant in follow-up visits.

Post-acute sequelae of SARS-CoV-2 infection in health care workers from South Africa.

Health care workers (HCWs) are primary health providers therefore ensuring their protection and recovery from Covid-19 is of high interest. We investigated post-acute sequelae of SARS-CoV-2 infection (PASC) in HCWs who had previously been infected with SARS-CoV-2. Overall, 68 HCWs were classified as PASC according to duration of persisting symptoms. The 68 HCWs with PASC were split into two groups according to the mean duration of their symptoms, which were (8 PASC) 122 and (60 PASC) 641 days. The frequencies of common symptoms reported by HWCs with PASC were continuous headaches (45), mild cough (41), fatigue (37), myalgia (25) and shortness of breath (14). When using the Medical Research Council (MRC) dyspnoea scale to examine the degree of breathlessness in relations to activity we found that 4 reported having difficulty breathing after strenuous exercise, 19 were identified with shortness of breath when walking fast or when walking up a slight hill, 2 reported walking slower than most people on level or stopping after 15 minutes walking at own pace, 1 reported stopping to breath after walking 91 meters, or after a few minutes on level ground and 1 reported being too breathless to leave the house, or breathless when dressing/undressing. Our results highlight concern for HCWs with long-term persisting symptoms which may negatively impact their health this represents an emerging public health priority. HCWs with prolonged Covid-19 symptoms especially breathing difficulties need better diagnostic tests and treatments.

The Impact of Resistance Training on Equilibrium Abilities and Quality of Life in Older Adults after SARS-CoV-2 Survival.

Background: The scientific literature on COVID-19 and its long-term impacts on all-body systems and their treatments is still limited. The aim of the study was to create a safe protocol-based intervention to improve functional and equilibrium abilities in older adults impacted by COVID-19. Methods: This study used a sample of 46 people (intervention group: n = 26; control group: n = 20). Resistance training (RT) was held twice a week, with 60 min per session for 8 weeks. The postural stability and quality of life questionnaire (WHQOOL) was completed during pre- and post-testing. Results: The results indicated significant differences in overall stability index (OSI) with eyes open (EO), anterior-posterior stability index (APSI) EO, fall-risk index 6-2 (FRI6-2) values in males (p < 0.05), and APSI EO (p < 0.05) values in females compared to control groups, respectively. In the training, a significant improvement was reported in OSI EO and APSI EO (p < 0.05) female groups compared to baseline results and in FRI6-2 values in both gender groups (p < 0.01-men, p < 0.05-women). The effect of the intervention was recorded in the intervention group in the OSI EO (Z = -3.12, p < 0.01, R = 0.533) and FRI6-2 (Z = -2.06, p < 0.05, R = 0.354). Additionally, significantly different reactions between the groups were observed in the psychological domain (DOM2) (Z = 2.194, p < 0.028, R = 0.389), social relationship domain (DOM3) (Z = 2.051, p < 0.0403, R = 0.361), and in question 2 concerning general health (Z = 3.309, p < 0.0009, R = 0.535). Conclusions: The findings indicate that RT had a positive effect on older adults affected by COVID-19, led to a significant improvement in their postural stability, and had a significant impact on elements of psychological well-being and quality of life.

Comparison of COVID-19 Symptoms in Correctional Health Care Workers During the Initial and Omicron Surges.

There is a dearth of medical literature that characterizes the experience of correctional health care workers (HCWs) during the COVID-19 pandemic. We performed a retrospective chart review of the results of an ongoing universal SARS-CoV-2 testing program for New Jersey correctional system HCWs and describe their presenting symptoms, perceived exposure, and demographic characteristics during the initial (March 15, 2020, to August 31, 2020) and Omicron (March 1, 2022, to August 31, 2022) COVID-19 surges. Analysis included 123 eligible records. In both surges, nurses had a high proportion of infections and cough was the most commonly reported symptom. Fever was more than twice as commonly reported in the initial surge. During the Omicron surge, nasal symptoms predominated (39.5% [95% CI: 28.4-51.4]) compared with the initial surge (8.5% [95% CI: 2.4-20.4]). Perceived exposure source was predominantly work related during the initial surge and multiple other sources of exposure were identified during the Omicron surge. Ninety-six percent of HCWs received a COVID-19 booster shot by February 2022. The reinfection rate was less than 10% for our initial cohort. Presenting symptoms correlated with the circulating variant. Mass vaccination of staff, the lower virulence of the Omicron variant, and possibly prior infection likely contributed to the milder illness experienced during the Omicron surge.

Association of the medication protocols and longitudinal change of COVID-19 symptoms: a hospital-based mixed-statistical methods study.

The objective of this study was to identify the relationship between hospitalization treatment strategies leading to change in symptoms during 12-week follow-up among hospitalized patients during the COVID-19 outbreak. In this article, data from a prospective cohort study on COVID-19 patients admitted to Khorshid Hospital, Isfahan, Iran, from February 2020 to February 2021, were analyzed and reported. Patient characteristics, including socio-demographics, comorbidities, signs and symptoms, and treatments during hospitalization, were investigated. Also, to investigate the treatment effects adjusted by other confounding factors that lead to symptom change during follow-up, the binary classification trees, generalized linear mixed model, machine learning, and joint generalized estimating equation methods were applied. This research scrutinized the effects of various medications on COVID-19 patients in a prospective hospital-based cohort study, and found that heparin, methylprednisolone, ceftriaxone, and hydroxychloroquine were the most frequently prescribed medications. The results indicate that of patients under 65 years of age, 76% had a cough at the time of admission, while of patients with Cr levels of 1.1 or more, 80% had not lost weight at the time of admission. The results of fitted models showed that, during the follow-up, women are more likely to have shortness of breath (OR = 1.25; P-value: 0.039), fatigue (OR = 1.31; P-value: 0.013) and cough (OR = 1.29; P-value: 0.019) compared to men. Additionally, patients with symptoms of chest pain, fatigue and decreased appetite during admission are at a higher risk of experiencing fatigue during follow-up. Each day increase in the duration of ceftriaxone multiplies the odds of shortness of breath by 1.15 (P-value: 0.012). With each passing week, the odds of losing weight increase by 1.41 (P-value: 0.038), while the odds of shortness of breath and cough decrease by 0.84 (P-value: 0.005) and 0.56 (P-value: 0.000), respectively. In addition, each day increase in the duration of meropenem or methylprednisolone decreased the odds of weight loss at follow-up by 0.88 (P-value: 0.026) and 0.91 (P-value: 0.023), respectively (among those who took these medications). Identified prognostic factors can help clinicians and policymakers adapt management strategies for patients in any pandemic like COVID-19, which ultimately leads to better hospital decision-making and improved patient quality of life outcomes.

Effectiveness of Online and Remote Interventions for Mental Health in Children, Adolescents, and Young Adults After the Onset of the COVID-19 Pandemic: Systematic Review and Meta-Analysis.

BACKGROUND: The prevalence of mental illness increased in children, adolescents, and young adults during the COVID-19 pandemic, while at the same time, access to treatment facilities has been restricted, resulting in a need for the quick implementation of remote or online interventions. OBJECTIVE: This study aimed to give an overview of randomized controlled studies examining remote or online interventions for mental health in children, adolescents, and young adults and to explore the overall effectiveness of these interventions regarding different symptoms. METHODS: A systematic literature search was conducted according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines using PubMed, PsycInfo, Psyndex, Embase, and Google Scholar. A meta-analysis was conducted using a random effects model to calculate overall effect sizes for interventions using standardized mean differences (SMDs) for postintervention scores. RESULTS: We identified 17 articles with 8732 participants in the final sample, and 13 were included in the quantitative analysis. The studies examined different digital interventions for several outcomes, showing better outcomes than the control in some studies. Meta-analyses revealed significant medium overall effects for anxiety (SMD=0.44, 95% CI 0.20 to 0.67) and social functioning (SMD=0.42, 95% CI -0.68 to -0.17) and a large significant effect for depression (SMD=1.31, 95% CI 0.34 to 2.95). In contrast, no significant overall treatment effects for well-being, psychological distress, disordered eating, and COVID-19-related symptoms were found. CONCLUSIONS: The qualitative and quantitative analyses of the included studies show promising results regarding the effectiveness of online interventions, especially for symptoms of anxiety and depression and for training of social functioning. However, the effectiveness needs to be further investigated for other groups of symptoms in the future. All in all, more research with high-quality studies is required.

Effectiveness of BNT162b2 BA.4/5 Bivalent COVID-19 Vaccine against Long COVID Symptoms: A US Nationwide Study.

BACKGROUND: Long COVID has become a central public health concern. This study characterized the effectiveness of BNT162b2 BA.4/5 bivalent COVID-19 vaccine (bivalent) against long COVID symptoms. METHODS: Symptomatic US adult outpatients testing positive for SARS-CoV-2 were recruited between 2 March and 18 May 2023. Symptoms were assessed longitudinally using a CDC-based symptom questionnaire at Week 4, Month 3, and Month 6 following infection. The odds ratio (OR) of long COVID between vaccination groups was assessed by using mixed-effects logistic models, adjusting for multiple covariates. RESULTS: At Week 4, among 505 participants, 260 (51%) were vaccinated with bivalent and 245 (49%) were unvaccinated. Mean age was 46.3 years, 70.7% were female, 25.1% had ≥1 comorbidity, 43.0% prior infection, 23.0% reported Nirmatrelvir/Ritonavir use. At Month 6, the bivalent cohort had 41% lower risk of long COVID with ≥3 symptoms (OR: 0.59, 95% CI, 0.36-0.96, p = 0.034) and 37% lower risk of ≥2 symptoms (OR: 0.63, 95% CI, 0.41-0.96, p = 0.030). The bivalent cohort reported fewer and less durable symptoms throughout the six-month follow-up, driven by neurologic and general symptoms, especially fatigue. CONCLUSIONS: Compared with unvaccinated participants, participants vaccinated with the bivalent were associated with approximately 40% lower risk of long COVID and less symptom burden over the six-month study duration.

The Bittersweet Symphony of COVID-19: Associations between TAS1Rs and TAS2R38 Genetic Variations and COVID-19 Symptoms.

The innate immune system is crucial in fighting SARS-CoV-2 infection, which is responsible for coronavirus disease 2019 (COVID-19). Therefore, deepening our understanding of the underlying immune response mechanisms is fundamental for the development of novel therapeutic strategies. The role of extra-oral bitter (TAS2Rs) and sweet (TAS1Rs) taste receptors in immune response regulation has yet to be fully understood. However, a few studies have investigated the association between taste receptor genes and COVID-19 symptom severity, with controversial results. Therefore, this study aims to deepen the relationship between COVID-19 symptom presence/severity and TAS1R and TAS2R38 (TAS2Rs member) genetic variations in a cohort of 196 COVID-19 patients. Statistical analyses detected significant associations between rs307355 of the TAS1R3 gene and the following COVID-19-related symptoms: chest pain and shortness of breath. Specifically, homozygous C/C patients are exposed to an increased risk of manifesting severe forms of chest pain (OR 8.11, 95% CI 2.26-51.99) and shortness of breath (OR 4.83, 95% CI 1.71-17.32) in comparison with T/C carriers. Finally, no significant associations between the TAS2R38 haplotype and the presence/severity of COVID-19 symptoms were detected. This study, taking advantage of a clinically and genetically characterised cohort of COVID-19 patients, revealed TAS1R3 gene involvement in determining COVID-19 symptom severity independently of TAS2R38 activity, thus providing novel insights into the role of TAS1Rs in regulating the immune response to viral infections.

Answering List-Type Questions in Health Domain with Pretrained Large Language Model: A Case for COVID-19 Symptoms.

List-type questions, which can have a varying number of answers, are more common in the health domain where people seek for health-related information from a passage or passages. An example of this type of question answering task is to find COVID-19 symptoms from a Twitter post. However, due to the lack of annotated instances for supervised learning, automatic identification of COVID-19 symptoms from Twitter posts is challenging. We investigated detection of symptom mentions in Twitter posts using GPT-3, a pre-trained large language model, along with few-shot learning. Our results of 5-shot and 10-shot learning on a corpus of 655 annotated tweets demonstrate that few-shot learning with pre-trained large language model is a promising approach to answering list-type questions with a minimal amount of effort of annotation.

First trans-diagnostic experiences with a novel micro-choice based concentrated group rehabilitation for patients with low back pain, long COVID, and type 2 diabetes: a pilot study.

BACKGROUND: The health care is likely to break down unless we are able to increase the level of functioning for the growing number of patients with complex, chronic illnesses. Hence, novel high-capacity and cost-effective treatments with trans-diagnostic effects are warranted. In accordance with the protocol paper, we aimed to examine the acceptability, satisfaction, and effectiveness of an interdisciplinary micro-choice based concentrated group rehabilitation for patients with chronic low back pain, long COVID, and type 2 diabetes. METHODS: Patients with low back pain > 4 months sick-leave, long COVID, or type 2 diabetes were included in this clinical trial with pre-post design and 3-month follow-up. The treatment consisted of three phases: (1) preparing for change, (2) the concentrated intervention for 3-4 days, and (3) integrating change into everyday life. Patients were taught and practiced how to monitor and target seemingly insignificant everyday micro-choices, in order to break the patterns where symptoms or habits contributed to decreased levels of functioning or increased health problems. The treatment was delivered to groups (max 10 people) with similar illnesses. Client Satisfaction Questionnaire (CSQ-8)) (1 week), Work and Social Adjustment Scale (WSAS), Brief Illness Perception Questionnaire (BIPQ), and self-rated health status (EQ-5D-5L) were registered at baseline and 3-month follow-up. RESULTS: Of the 241 included participants (57% women, mean age 48 years, range 19-84), 99% completed the concentrated treatment. Treatment satisfaction was high with a 28.9 (3.2) mean CSQ-8-score. WSAS improved significantly from baseline to follow-up across diagnoses 20.59 (0.56) to 15.76 (0.56). BIPQ improved from: 22.30 (0.43) to 14.88 (0.47) and EQ-5D-5L: 0.715 (0.01) to 0.779 (0.01)), all P<0.001. CONCLUSIONS: Across disorders, the novel approach was associated with high acceptability and clinically important improvements in functional levels, illness perception, and health status. As the concentrated micro-choice based treatment format might have the potential to change the way we deliver rehabilitation across diagnoses, we suggest to proceed with a controlled trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT05234281.

Prevalence and risk factors for persistent symptoms after COVID-19: a systematic review and meta-analysis.

BACKGROUND: Long-term physical and mental persistent symptoms after COVID-19 represent a growing global public health concern. However, there remains a substantial knowledge gap regarding their prevalence and risk factors. OBJECTIVES: To estimate the prevalence and risk factors for persistent symptoms after COVID-19. METHODS OF DATA SYNTHESIS: We used a random-effects model to pool persistent symptom prevalence and risk ratios comparing COVID-19 patients with non-COVID-19 individuals. DATA SOURCES: Electronic databases were searched for studies published from December 2019 to January 2023. STUDY ELIGIBILITY CRITERIA: Eligible studies that reported the prevalence and risk factors for persistent symptoms after COVID-19 were included. PARTICIPANTS: Patients who recovered from COVID-19. ASSESSMENT OF RISK OF BIAS: The Joanna Briggs Institute critical appraisal tool was used to assess the risk of bias in prevalence studies, whereas the risk of bias in cohort studies was evaluated with the Newcastle-Ottawa Scale. RESULTS: After screening 4359 studies, a total of 211 eligible studies were included, covering a population of 13 368 074 individuals. Fatigue, dyspnoea, post-traumatic stress disorder, anxiety, and depression were the most frequently reported persistent symptoms after COVID-19. Subgroup analyses revealed that individuals with more severe illness in the acute phase or from Europe exhibited a higher prevalence of certain symptoms, whereas children demonstrated a lower prevalence. Furthermore, COVID-19 patients had a significantly higher prevalence of most persistent symptoms compared with non-COVID-19 individuals. Factors frequently associated with a higher prevalence of persistent symptoms included female gender, advanced age, severe illness during the acute phase of COVID-19, multiple comorbidities, an extended duration of hospital stay, and a high body mass index. CONCLUSION: This meta-analysis provides a thorough review of the prevalence and risk factors for persistent symptoms following COVID-19. The findings underscore the importance of long-term monitoring and support for individuals recovering from COVID-19.