Clinical characteristics and outcomes of patients with mpox during the 2022 mpox outbreak compared with those before the outbreak: A systematic review and meta-analysis.

On 23 July 2022, the World Health Organization declared the global mpox outbreak as a public health emergency of international significance. The mpox virus (MPXV) that caused the outbreak was classified as clade IIb, which belongs to the West African clade. However, the relationship between MPXV clades and symptoms, as well as the severity of mpox outcomes, is not fully understood. Thus, we aimed to investigate the global mpox prevalence and the differences in clinical manifestations and outcomes among patients with mpox between pre-outbreak (2003-2021) and the current mpox outbreak. In this systematic review and meta-analysis, PubMed/MEDLINE, Web of Science, Embase, Cumulative Index to Nursing and Allied Health Literature, and Google Scholar were searched using the keyword "monkeypox" and "mpox" up to 13 October 2022. A random effects model was used to obtain the pooled prevalence and 95% confidence intervals. This study included 27 articles, and 5698 patients with mpox with 19 distinctive features from 19 countries across five continents were assessed. Patients with mpox during the 2022 mpox outbreak showed mild clinical manifestations and outcomes compared with those before the 2022 mpox outbreak: mild rash (relative ratio [RR]: 5.09, 95% confidence interval [CI]: 1.52-17.08), fever (0.68, 0.49-0.94), pruritus (0.25, 0.19-0.32), myalgia (0.50, 0.31-0.81), headache (0.56, 0.35-0.88), skin ulcer (0.32, 0.17-0.59), abdominal symptom (0.29, 0.20-0.42), pharyngitis (0.32, 0.18-0.58), nausea or vomiting (0.15, 0.02-0.93), conjunctivitis (0.11, 0.03-0.38), concomitant infection with HIV (1.70, 0.95-3 0.04), and death (0.02, 0.001-0.31). MPXV clade IIb exhibited higher infectivity but may cause mild disease symptoms and low mortality rate. It is important to consider MPXV infection in patients with mpox-related features and/or a history of sexual transmission to prevent the spread of the disease and recognise the current pandemic threat.

Long-Term Autoimmune Inflammatory Rheumatic Outcomes of COVID-19 : A Binational Cohort Study.

BACKGROUND: Some data suggest a higher incidence of diagnosis of autoimmune inflammatory rheumatic diseases (AIRDs) among patients with a history of COVID-19 compared with uninfected patients. However, these studies had methodological shortcomings. OBJECTIVE: To investigate the effect of COVID-19 on long-term risk for incident AIRD over various follow-up periods. DESIGN: Binational, longitudinal, propensity-matched cohort study. SETTING: Nationwide claims-based databases in South Korea (K-COV-N cohort) and Japan (JMDC cohort). PARTICIPANTS: 10 027 506 Korean and 12 218 680 Japanese patients aged 20 years or older, including those with COVID-19 between 1 January 2020 and 31 December 2021, matched to patients with influenza infection and to uninfected control patients. MEASUREMENTS: The primary outcome was onset of AIRD (per appropriate codes from the International Classification of Diseases, 10th Revision) 1, 6, and 12 months after COVID-19 or influenza infection or the respective matched index date of uninfected control patients. RESULTS: Between 2020 and 2021, among the 10 027 506 Korean participants (mean age, 48.4 years [SD, 13.4]; 50.1% men), 394 274 (3.9%) and 98 596 (0.98%) had a history of COVID-19 or influenza, respectively. After propensity score matching, beyond the first 30 days after infection, patients with COVID-19 were at increased risk for incident AIRD compared with uninfected patients (adjusted hazard ratio, 1.25 [95% CI, 1.18 to 1.31]) and influenza-infected control patients (adjusted hazard ratio, 1.30 [CI, 1.02 to 1.59]). The risk for incident AIRD was higher with more severe acute COVID-19. Similar patterns were observed in the Japanese cohort. LIMITATIONS: Referral bias due to the pandemic; residual confounding. CONCLUSION: SARS-CoV-2 infection was associated with increased risk for incident AIRD compared with matched patients without SARS-CoV-2 infection or with influenza infection. The risk for incident AIRD was higher with greater severity of acute COVID-19. PRIMARY FUNDING SOURCE: National Research Foundation of Korea.

Systematic review of fatigue severity in ME/CFS patients: insights from randomized controlled trials.

BACKGROUND: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating illness medically unexplained, affecting approximately 1% of the global population. Due to the subjective complaint, assessing the exact severity of fatigue is a clinical challenge, thus, this study aimed to produce comprehensive features of fatigue severity in ME/CFS patients. METHODS: We systematically extracted the data for fatigue levels of participants in randomized controlled trials (RCTs) targeting ME/CFS from PubMed, Cochrane Library, Web of Science, and CINAHL throughout January 31, 2024. We normalized each different measurement to a maximum 100-point scale and performed a meta-analysis to assess fatigue severity by subgroups of age, fatigue domain, intervention, case definition, and assessment tool, respectively. RESULTS: Among the total of 497 relevant studies, 60 RCTs finally met our eligibility criteria, which included a total of 7088 ME/CFS patients (males 1815, females 4532, and no information 741). The fatigue severity of the whole 7,088 patients was 77.9 (95% CI 74.7-81.0), showing 77.7 (95% CI 74.3-81.0) from 54 RCTs in 6,706 adults and 79.6 (95% CI 69.8-89.3) from 6 RCTs in 382 adolescents. Regarding the domain of fatigue, 'cognitive' (74.2, 95% CI 65.4-83.0) and 'physical' fatigue (74.3, 95% CI 68.3-80.3) were a little higher than 'mental' fatigue (70.1, 95% CI 64.4-75.8). The ME/CFS participants for non-pharmacological intervention (79.1, 95% CI 75.2-83.0) showed a higher fatigue level than those for pharmacological intervention (75.5, 95% CI 70.0-81.0). The fatigue levels of ME/CFS patients varied according to diagnostic criteria and assessment tools adapted in RCTs, likely from 54.2 by ICC (International Consensus Criteria) to 83.6 by Canadian criteria and 54.2 by MFS (Mental Fatigue Scale) to 88.6 by CIS (Checklist Individual Strength), respectively. CONCLUSIONS: This systematic review firstly produced comprehensive features of fatigue severity in patients with ME/CFS. Our data will provide insights for clinicians in diagnosis, therapeutic assessment, and patient management, as well as for researchers in fatigue-related investigations.

Central 5-HTergic hyperactivity induces myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)-like pathophysiology.

OBJECTIVES: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a significant medical challenge, with no indisputable pathophysiological mechanism identified to date. METHODS: Based on clinical clues, we hypothesized that 5-hydroxytryptamine (5-HT) hyperactivation is implicated in the pathogenic causes of ME/CFS and the associated symptoms. We experimentally evaluated this hypothesis in a series of mouse models. RESULTS: High-dose selective serotonin reuptake inhibitor (SSRI) treatment induced intra- and extracellular serotonin spillover in the dorsal raphe nuclei of mice. This condition resulted in severe fatigue (rota-rod, fatigue rotating wheel and home-cage activity tests) and ME/CFS-associated symptoms (nest building, plantar and open field test), along with dysfunction in the hypothalamic-pituitary-adrenal (HPA) axis response to exercise challenge. These ME/CFS-like features induced by excess serotonin were additionally verified using both a 5-HT synthesis inhibitor and viral vector for Htr1a (5-HT1A receptor) gene knockdown. CONCLUSIONS: Our findings support the involvement of 5-HTergic hyperactivity in the pathophysiology of ME/CFS. This ME/CFS-mimicking animal model would be useful for understanding ME/CFS biology and its therapeutic approaches.

Global burden of vaccine-associated multiple sclerosis, 1967-2022: A comprehensive analysis of the international pharmacovigilance database.

Vaccine-associated multiple sclerosis (MS) is rare, with insufficient evidence from case reports. Given the scarcity of large-scale data investigating the association between vaccine administration and adverse events, we investigated the global burden of vaccine-associated MS and potential related vaccines from 1967 to 2022. Reports on vaccine-associated MS between 1967 and 2022 were obtained from the World Health Organization International Pharmacovigilance Database (total number of reports = 120 715 116). We evaluated global reports, reporting odds ratio (ROR), and information components (IC) to investigate associations between 19 vaccines and vaccine-associated MS across 156 countries and territories. We identified 8288 reports of vaccine-associated MS among 132 980 cases of all-cause MS. The cumulative number of reports on vaccine-associated MS gradually increased over time, with a substantial increase after 2020, owing to COVID-19 mRNA vaccine-associated MS. Vaccine-associated MS develops more frequently in males and adolescents. Nine vaccines were significantly associated with higher MS reporting, and the highest disproportional associations were observed for hepatitis B vaccines (ROR 19.82; IC025 4.18), followed by encephalitis (ROR 7.42; IC025 2.59), hepatitis A (ROR 4.46; IC025 1.95), and papillomavirus vaccines (ROR 4.45; IC025 2.01). Additionally, MS showed a significantly disproportionate signal for COVID-19 mRNA vaccines (ROR 1.55; IC025 0.52). Fatal clinical outcomes were reported in only 0.3% (21/8288) of all cases of vaccine-associated MS. Although various vaccines are potentially associated with increased risk of MS, we should be cautious about the increased risk of MS following vaccination, particularly hepatitis B and COVID-19 mRNA vaccines, and should consider the risk factors associated with vaccine-associated MS.

Global estimates on the reports of vaccine-associated myocarditis and pericarditis from 1969 to 2023: Findings with critical reanalysis from the WHO pharmacovigilance database.

Due to the limitation of previous studies examining adverse reports of myocarditis and pericarditis associated with vaccines other than the COVID-19 vaccine, there are challenges in establishing a comprehensive understanding of vaccine safety on a global scale. Hence, the objective of this study was to examine the worldwide burden of vaccine-associated pericarditis and myocarditis and the vaccines associated with these indications. This study utilized the World Health Organization international pharmacovigilance database, from which records of vaccine-associated pericarditis and myocarditis between 1969 and 2023 were extracted (over 130 million reports). We calculated global reporting counts, reported odds ratios (RORs), and information components (ICs) to discern the association between 19 vaccines and the occurrence of pericarditis and myocarditis across 156 countries and territories. We identified 49 096 reports (male, n = 30 013) of vaccine-associated pericarditis and myocarditis among 73 590 reports of all-cause pericarditis and myocarditis. There has been a significant increase in reports of vaccine-related cardiac adverse events over time, with a noteworthy surge observed after 2020, attributed to cases of pericarditis associated with COVID-19 mRNA vaccines. Smallpox vaccines were associated with most pericarditis and myocarditis reports (ROR: 73.68 [95% CI, 67.79-80.10]; IC [IC0.25]: 6.05 [5.91]), followed by COVID-19 mRNA vaccine (37.77 [37.00-38.56]; 3.07 [3.05]), anthrax vaccine (25.54 [22.37-29.16]; 4.58 [4.35]), typhoid vaccine (6.17 [5.16-7.38]; 2.59 [2.29]), encephalitis vaccine (2.00 [1.48-2.71]; 0.99 [0.47]), influenza vaccine (1.87 [1.71-2.04]; 0.90 [0.75]), and Ad5-vectored COVID-19 vaccine (1.40 [1.34-1.46]; 0.46 [0.39]). Concerning age and sex-specific risks, reports of vaccine-associated pericarditis and myocarditis were more prevalent among males and in older age groups. The age group between 12 and 17 years exhibited significant sex disproportion. Most of these adverse events had a short time to onset (median time: 1 day) and fatality rate was 0.44%. Our analysis of global data revealed an increase in pericarditis and myocarditis reports associated with vaccines, particularly live vaccines like smallpox and anthrax, notably in young males. While these adverse events are generally rare and mild, caution is warranted, especially for healthcare workers, due to potential myocardial injury-related in-hospital mortality. Further study with validated reporting is crucial to enhance accuracy in evaluating the correlation between vaccines and cardiac conditions for preventive measures.

Risks of cutaneous immune-related adverse events in long COVID: Multinational cohort studies in South Korea, Japan, and the UK.

Previous research has not investigated the persistent cutaneous immune-related adverse events (cirAEs) related to long COVID to investigate the long-term sequelae. This multinational study, using a propensity-matched overlap weighting method, utilizes large national claims-based cohorts, using ICD-10 code diagnosis, focusing on patients aged ≥20 years from three countries: South Korean, Japanese, and the British cohorts. To estimate the risk of cirAEs in long COVID, the persistence or emergence of cirAEs occurring 4 weeks after the initial SARS-CoV-2 infection, we employed a Cox proportional hazard regression model. The Korean cohort (n = 5,937,373; mean age 49.2 years [SD: 13.2]), the Japanese cohort (n = 4,307,587; 42.5 years [13.6]), and the UK cohort (n = 395,435; 71.0 years [8.07]) were presented. An increased risk of cirAEs in long COVID was observed (HR, 1.10; 95% CI, 1.06-1.14) in Korean cohort, while a similar association was observed in Japanese and UK cohorts. The long-term risk of cirAEs in long COVID was higher in more severe COVID-19 cases (1.31; 1.22-1.39). Unlike the increased risk of cirAEs in long COVID, COVID-19 vaccination attenuated the risk, especially with two or more doses (1.03; 0.95-1.11) or heterologous regimens (0.98; 0.76-1.27). The time attenuation effect indicated a sustained risk for up to 6 months postinfection (<3 months: 1.13 [1.07-1.19]; 3-6 months: 1.14 [1.06-1.22]). SARS-CoV-2 infection is associated with an increased risk of cirAEs in the aspect of long COVID. Vaccination might reduce this risk, highlighting the need for preventive strategies in long COVID management.

Global and regional burden of vaccine-associated facial paralysis, 1967-2023: Findings from the WHO international pharmacovigilance database.

The scarce and conflicting data on vaccine-associated facial paralysis limit our understanding of vaccine safety on a global scale. Therefore, this study aims to evaluate the global burden of vaccine-associated facial paralysis and to identify the extent of its association with individual vaccines, thereby contributing to the development of a more effective vaccination program. We used data on vaccine-associated facial paralysis from 1967 to 2023 (total reports, n = 131 255 418 418) from the World Health Organization International Pharmacovigilance Database. Global reporting counts, reported odds ratios (ROR), and information components (ICs) were computed to elucidate the association between the 16 vaccines and the occurrence of vaccine-associated facial paralysis across 156 countries. We identified 26 197 reports (men, n = 10 507 [40.11%]) of vaccine-associated facial paralysis from 49 537 reports of all-cause facial paralysis. Vaccine-associated facial paralysis has been consistently reported; however, a pronounced increase in reported incidence has emerged after the onset of the coronavirus disease 2019 (COVID-19) pandemic, which is attributable to the COVID-19 mRNA vaccine. Most vaccines were associated with facial paralysis, with differing levels of association, except for tuberculosis vaccines. COVID-19 mRNA vaccines had the highest association with facial paralysis reports (ROR, 28.31 [95% confidence interval, 27.60-29.03]; IC, 3.37 [IC0.25, 3.35]), followed by encephalitis, influenza, hepatitis A, papillomavirus, hepatitis B, typhoid, varicella-zoster, meningococcal, Ad-5 vectored COVID-19, measles, mumps and rubella, diphtheria, tetanus toxoids, pertussis, polio, and Hemophilus influenza type b, pneumococcal, rotavirus diarrhea, and inactivated whole-virus COVID-19 vaccines. Concerning age- and sex-specific risks, vaccine-associated facial paralysis was more strongly associated with older age groups and males. The serious adverse outcome and death rate of vaccine-associated facial paralysis were extremely low (0.07% and 0.00%, respectively). An increase in vaccine-induced facial paralysis, primarily owing to COVID-19 mRNA vaccines, was observed with most vaccines, except tuberculosis vaccines. Given the higher association observed in the older and male groups with vaccine-associated facial paralysis, close monitoring of these demographics when administering vaccines that are significantly associated with adverse reactions is crucial.

Global burden of vaccine-associated anaphylaxis and their related vaccines, 1967-2023: A comprehensive analysis of the international pharmacovigilance database.

BACKGROUND: Vaccine-associated anaphylaxis is a rare but life-threatening reaction that occurs within minutes to hours of exposure to allergens. As studies utilizing large-scale data to investigate this topic are limited, further research is needed to assess its burden, long-term trends, and associated risk factors so as to gain a comprehensive understanding of vaccine-associated anaphylaxis globally. Therefore, this study aimed to investigate the global burden of vaccine-associated anaphylaxis and related vaccines. METHOD: This study utilized the World Health Organization International Pharmacovigilance Database, in which reports of vaccine-associated anaphylaxis between 1967 and 2023 were obtained (total reports = 131,255,418). We estimated the global reporting counts, reported odds ratio (ROR), and information component (IC) to identify the relationship between 19 vaccines and associated anaphylaxis in 156 countries and territories. RESULTS: We identified 31,676 reports of vaccine-associated anaphylaxis among 363,290 reports of all-cause anaphylaxis. The cumulative number of reports on vaccine-associated anaphylaxis has gradually increased over time, with a dramatic increase after 2020, owing to reports of COVID-19 mRNA vaccine-associated anaphylaxis. The typhoid vaccines were associated with the most anaphylactic reports (ROR: 4.35; IC0.25 : 1.86), followed by encephalitis (3.27; 1.45), hepatitis B (2.69; 1.30), cholera (2.65; 0.54), hepatitis A (2.44; 1.12), influenza (2.36; 1.16), inactivated whole-virus COVID-19 (2.21; 1.02), and COVID-19 mRNA vaccines (1.89; 0.79). In terms of age- and sex-specific risks, vaccine-associated anaphylaxis reports develop more frequently in females and at young ages. The Ad5-vectored COVID-19 vaccine anaphylaxis reports were associated with the highest fatality rate (15.0%). CONCLUSIONS: Although multiple vaccines are associated with various spectra and risks of anaphylaxis, clinicians should recognize the possibility of anaphylaxis occurring with all vaccines, particularly the COVID-19 mRNA and inactivated whole-virus COVID-19 vaccines, and consider the risk factors associated with vaccine anaphylaxis reports. Further studies are warranted to identify better ways of preventing vaccine-associated anaphylaxis.

Global and regional burden of vaccine-induced thrombotic thrombocytopenia, 1969-2023: Comprehensive findings with critical analysis of the international pharmacovigilance database.

OBJECTIVE: The scarcity of studies on vaccine-induced thrombosis and thrombocytopenia syndrome (TTS) limits the comprehensive understanding of vaccine safety on a global scale. Therefore, the objective of this study is to assess the global burden of vaccine-induced TTS, identify the vaccines most associated with it, and suggest clinical implications regarding vaccination. METHODS: This study employed the World Health Organization international pharmacovigilance database, extracting records of vaccine-induced immune thrombotic thrombocytopenia from 1969 to 2023 (total reports, n > 130 million). Global reporting counts, reported odds ratios (ROR), and information components (IC) were calculated to identify the association between 19 vaccines and the occurrence of vaccine-induced TTS across 156 countries. RESULTS: We identified 24 233 cases (male, n = 11 559 [47.7%]) of vaccine-induced TTS among 404 388 reports of all-cause TTS. There has been a significant increase in reports of vaccine-induced TTS events over time, with a noteworthy surge observed after 2020, attributed to cases of TTS associated with COVID-19 vaccines. Measles, mumps, and rubella (MMR) vaccines were associated with most TTS reports (ROR [95% confidence interval], 2.87 [2.75-3.00]; IC [IC0.25], 1.51 [1.43]), followed by hepatitis B (HBV, 2.23 [2.07-2.39]; 1.15 [1.03]), rotavirus diarrhea (1.95 [1.78-2.13]; 0.81 [0.53]), encephalitis (1.80 [1.50-2.16]; 0.84 [0.53]), hepatitis A (1.67 [1.50-1.86]; 0.73 [0.55]), adenovirus Type 5 vector-based (Ad5-vectored) COVID-19 (1.64 [1.59-1.68]; 0.69 [0.64]), pneumococcal (1.57 [1.49-1.66]; 0.65 [0.56]), and typhoid vaccines (1.41 [1.12-1.78]; 0.49 [0.11]). Concerning age and sex-specific risks, reports of vaccine-induced TTS were more associated with females and younger age groups. The age group between 12 and 17 years exhibited significant sex disproportion. Most of these adverse events had a short time to onset (days; mean [SD], 4.99 [40.30]) and the fatality rate was 2.20%, the highest rate observed in the age group over 65 years (3.79%) and lowest in the age group between 0 and 11 years (0.31%). CONCLUSION: A rise in vaccine-induced TTS reports, notably MMR, HBV, and rotavirus diarrhea vaccines, was particularly related to young females. Ad5-vectored COVID-19 vaccines showed comparable or lower association with TTS compared to other vaccines. Despite the rarity of these adverse events, vigilance is essential as rare complications can be fatal, especially in older groups. Further studies with validated reporting are imperative to improve the accuracy of assessing the vaccine-induced TTS for preventive interventions and early diagnosis.

Clinical manifestations of human Mpox infection: A systematic review and meta-analysis.

Little is known about the ongoing monkeypox (mpox) outbreak, and the clinical features of mpox in patients worldwide have not been rigorously analysed. Thus, we aimed to investigate the clinical features associated with mpox infection and understand the pathophysiology and characteristics of the disease. For this systematic review and meta-analysis, we searched PubMed/MEDLINE, Embase, CINAHL, Google Scholar, and the Cochrane Database of Systematic Reviews for articles published till 16 September 2022. We used a random effects model to calculate the pooled prevalence and 95% confidence interval (CI). We used the I2 statistic to assess heterogeneity, Egger's test to assess publication bias, 95% prediction interval to determine the level of uncertainty, and the Newcastle-Ottawa Scale and Joanna Briggs Institute quality assessment tool to assess the risk of bias. Twenty-six relevant articles from 19 countries across 5 continents were included, and data on 5472 mpox patients with 18 unique features were analysed. The pooled prevalence of clinical features of mpox were rash (85.7%, 95% CI: 68.3-94.3; k = 21), chills (77.8%, 95% CI: 70.5-83.7; k = 3), and fever (62.3%, 95% CI: 51.3-71.6; k = 25), lymphadenopathy (58.6%, 95% CI: 47.2-69.2; k = 21), lethargy or exhaustion (46.8%, 95% CI: 30.7-63.5; k = 14), pruritus (40.6%, 95% CI: 28.5-54.0; k = 5), myalgia (36.0%, 95% CI: 24.3-49.7; k = 16), headache (34.6%, 95% CI: 23.4-47.8; k = 17), skin ulcer (31.1%, 95% CI: 18.6-47.1; k = 7), abdomen symptom (24.2%, 95% CI: 17.9-31.9; k = 11), pharyngitis (23.0%, 95% CI: 12.7-37.9; k = 14), respiratory symptom (19.5%, 95% CI: 6.8-44.6; k = 6), nausea or vomiting (13.0%, 95% CI: 4.6-31.9; k = 3), scrotal or penile oedema (10.7%, 95% CI: 6.3-17.7; k = 4), conjunctivitis (7.1%, 95% CI: 2.4-18.9; k = 6), and death (0.9%, 95% CI: 0.4-2.0; k = 26). This is the first international and comprehensive study to examine all clinical presentations of human mpox infection. Our systematic review proposes a comprehensive understanding of the current mpox outbreak and may serve as key data for future studies on the pathological mechanisms and epidemiology of mpox infections.

Limitations of the Cough Sound-Based COVID-19 Diagnosis Artificial Intelligence Model and its Future Direction: Longitudinal Observation Study.

BACKGROUND: The outbreak of SARS-CoV-2 in 2019 has necessitated the rapid and accurate detection of COVID-19 to manage patients effectively and implement public health measures. Artificial intelligence (AI) models analyzing cough sounds have emerged as promising tools for large-scale screening and early identification of potential cases. OBJECTIVE: This study aimed to investigate the efficacy of using cough sounds as a diagnostic tool for COVID-19, considering the unique acoustic features that differentiate positive and negative cases. We investigated whether an AI model trained on cough sound recordings from specific periods, especially the early stages of the COVID-19 pandemic, were applicable to the ongoing situation with persistent variants. METHODS: We used cough sound recordings from 3 data sets (Cambridge, Coswara, and Virufy) representing different stages of the pandemic and variants. Our AI model was trained using the Cambridge data set with subsequent evaluation against all data sets. The performance was analyzed based on the area under the receiver operating curve (AUC) across different data measurement periods and COVID-19 variants. RESULTS: The AI model demonstrated a high AUC when tested with the Cambridge data set, indicative of its initial effectiveness. However, the performance varied significantly with other data sets, particularly in detecting later variants such as Delta and Omicron, with a marked decline in AUC observed for the latter. These results highlight the challenges in maintaining the efficacy of AI models against the backdrop of an evolving virus. CONCLUSIONS: While AI models analyzing cough sounds offer a promising noninvasive and rapid screening method for COVID-19, their effectiveness is challenged by the emergence of new virus variants. Ongoing research and adaptations in AI methodologies are crucial to address these limitations. The adaptability of AI models to evolve with the virus underscores their potential as a foundational technology for not only the current pandemic but also future outbreaks, contributing to a more agile and resilient global health infrastructure.

Machine Learning-Based Prediction of Suicidality in Adolescents With Allergic Rhinitis: Derivation and Validation in 2 Independent Nationwide Cohorts.

BACKGROUND: Given the additional risk of suicide-related behaviors in adolescents with allergic rhinitis (AR), it is important to use the growing field of machine learning (ML) to evaluate this risk. OBJECTIVE: This study aims to evaluate the validity and usefulness of an ML model for predicting suicide risk in patients with AR. METHODS: We used data from 2 independent survey studies, Korea Youth Risk Behavior Web-based Survey (KYRBS; n=299,468) for the original data set and Korea National Health and Nutrition Examination Survey (KNHANES; n=833) for the external validation data set, to predict suicide risks of AR in adolescents aged 13 to 18 years, with 3.45% (10,341/299,468) and 1.4% (12/833) of the patients attempting suicide in the KYRBS and KNHANES studies, respectively. The outcome of interest was the suicide attempt risks. We selected various ML-based models with hyperparameter tuning in the discovery and performed an area under the receiver operating characteristic curve (AUROC) analysis in the train, test, and external validation data. RESULTS: The study data set included 299,468 (KYRBS; original data set) and 833 (KNHANES; external validation data set) patients with AR recruited between 2005 and 2022. The best-performing ML model was the random forest model with a mean AUROC of 84.12% (95% CI 83.98%-84.27%) in the original data set. Applying this result to the external validation data set revealed the best performance among the models, with an AUROC of 89.87% (sensitivity 83.33%, specificity 82.58%, accuracy 82.59%, and balanced accuracy 82.96%). While looking at feature importance, the 5 most important features in predicting suicide attempts in adolescent patients with AR are depression, stress status, academic achievement, age, and alcohol consumption. CONCLUSIONS: This study emphasizes the potential of ML models in predicting suicide risks in patients with AR, encouraging further application of these models in other conditions to enhance adolescent health and decrease suicide rates.

Factors Affecting the Preference for Hospitals Over Clinics in Primary Care in Korea.

BACKGROUND: While the effect of gatekeeping was extensively studied, few efforts have been made to explain why the measures to strengthen gatekeeping do not work well in some countries. This study examined the patient factors related to the choice of level of health care facilities for outpatient care in Korea. METHODS: We examined a population-based sample representative of the population of Korea aged 15 and over in the healthcare experience survey of 2021. A logistic regression model examined the factors associated with choosing hospitals or clinics for outpatient care. RESULTS: Easy accessibility, kindness of medical staff, and recommendations from acquaintances were considered more important for those who chose clinics over hospitals. While those who chose clinics were more likely to feel that physicians and nurses more readily communicated with patients, those who chose hospitals were more likely to feel that the facility was comfortable. Whereas those who chose hospitals were more likely to trust the current health care system in Korea, those who chose clinics were more likely to think that the health care system needed to be reformed. The tendency was similar when analyzed only among those with good perceived health conditions and without chronic diseases. CONCLUSION: This study demonstrates that the preference for hospitals over clinics is mainly based on desire rather than medical need and is not likely to be affected by measures intended to induce a voluntary change of behavior.

Evaluation of viral infection as an etiology of ME/CFS: a systematic review and meta-analysis.

BACKGROUND: Myalgic encephalitis/chronic fatigue syndrome (ME/CFS) is a long-term disabling illness without a medically explained cause. Recently during COVID-19 pandemic, many studies have confirmed the symptoms similar to ME/CFS in the recovered individuals. To investigate the virus-related etiopathogenesis of ME/CFS, we conducted a systematic assessment of viral infection frequency in ME/CFS patients. METHODS: We conducted a comprehensive search of PubMed and the Cochrane Library from their inception through December 31, 2022, using selection criteria of viral infection prevalence in ME/CFS patients and controls. Subsequently, we performed a meta-analysis to assess the extent of viral infections' contribution to ME/CFS by comparing the odds ratio between ME/CFS patients and controls (healthy and/or diseased). RESULTS: Finally, 64 studies met our eligibility criteria regarding 18 species of viruses, including a total of 4971 ME/CFS patients and 9221 control subjects. The participants included healthy subjects and individuals with one of 10 diseases, such as multiple sclerosis or fibromyalgia. Two DNA viruses (human herpes virus (HHV)-7 and parvovirus B19, including their co-infection) and 3 RNA viruses (borna disease virus (BDV), enterovirus and coxsackie B virus) showed odds ratios greater than 2.0 compared with healthy and/or diseased subjects. Specifically, BDV exceeded the cutoff with an odds ratio of ≥ 3.47 (indicating a "moderate association" by Cohen's d test) compared to both healthy and diseased controls. CONCLUSION: This study comprehensively evaluated the risk of viral infections associated with ME/CFS, and identified BDV. These results provide valuable reference data for future studies investigating the role of viruses in the causation of ME/CFS.

Development and validation of a deep learning model to diagnose COVID-19 using time-series heart rate values before the onset of symptoms.

One of the effective ways to minimize the spread of COVID-19 infection is to diagnose it as early as possible before the onset of symptoms. In addition, if the infection can be simply diagnosed using a smartwatch, the effectiveness of preventing the spread will be greatly increased. In this study, we aimed to develop a deep learning model to diagnose COVID-19 before the onset of symptoms using heart rate (HR) data obtained from a smartwatch. In the deep learning model for the diagnosis, we proposed a transformer model that learns HR variability patterns in presymptom by tracking relationships in sequential HR data. In the cross-validation (CV) results from the COVID-19 unvaccinated patients, our proposed deep learning model exhibited high accuracy metrics: sensitivity of 84.38%, specificity of 85.25%, accuracy of 84.85%, balanced accuracy of 84.81%, and area under the receiver operating characteristics (AUROC) of 0.8778. Furthermore, we validated our model using external multiple datasets including healthy subjects, COVID-19 patients, as well as vaccinated patients. In the external healthy subject group, our model also achieved high specificity of 77.80%. In the external COVID-19 unvaccinated patient group, our model also provided similar accuracy metrics to those from the CV: balanced accuracy of 87.23% and AUROC of 0.8897. In the COVID-19 vaccinated patients, the balanced accuracy and AUROC dropped by 66.67% and 0.8072, respectively. The first finding in this study is that our proposed deep learning model can simply and accurately diagnose COVID-19 patients using HRs obtained from a smartwatch before the onset of symptoms. The second finding is that the model trained from unvaccinated patients may provide less accurate diagnosis performance compared with the vaccinated patients. The last finding is that the model trained in a certain period of time may provide degraded diagnosis performances as the virus continues to mutate.

National trends in physical activity among adolescents in South Korea before and during the COVID-19 pandemic, 2009-2021.

With the ongoing COVID-19 pandemic, several previous studies from different countries showed that physical activity (PA) decreased during the COVID-19 outbreak. However, few studies have examined the recent tendency of PA in the adolescent population. Thus, we aimed to investigate the long-term trend of PA in Korean youth and the prevalence changes between before and during the COVID-19 pandemic. Data from Korea Youth Risk Behavior Web-Based Survey (KYRBS) was collected for consecutive years between 2009 and 2021. The period was separated into prepandemic (2009-2019), early-pandemic (2020), and mid-pandemic (2021). Self-reported amount of PA was categorized into four groups (insufficient, aerobic, muscle strengthening, and both physical activities) according to World Health Organization (WHO) PA guidelines. A total of 840 488 adolescents aged 12-18 who fully responded to the survey were selected (response rate: 95.2%). The 13-year trends in the proportion of adolescents who reported aerobic and muscle-strengthening activities met or exceeded 2020 WHO exercise guidelines for adolescents plateaued (11.9% from 2009 to 2011, 14.2% from 2018 to 2019, 14.4% from 2020, and 14.0% from 2021); however, the slope decreased during the pandemic (ßdiff , -0.076; 95% confidence interval [CI], -0.123 to -0.029). Proportion of sufficient aerobic exercise among adolescents sharply decreased midst the pandemic (28.0% from 2009 to 2011, 29.4% from 2018 to 2019, and 23.8% from 2020; ßdiff , -0.266; 95% CI, -0.306 to -0.226) but increased again in 2021 (26.0% from mid-COVID 19; 95% CI, 25.4-26.7). Similar patterns were observed in Metabolic Equivalent Task (MET) score (MET-min/week; 804.1 from 2018 to 2019, 720.9 from 2020, and 779.6 from 2021). The mean difference in MET score between pre-COVID and post-COVID was -55.4 MET-min/week (95% CI, -70.5 to -40.3). Through a nationwide representative study, there was no significant difference with regard to the number of Korean adolescents who achieved the PA guidelines (pre and postpandemic); however, the prevalence of recommended levels of PA needs to increase more based on the trend before the COVID-19 outbreak. The findings of this study suggest reinforcement of the importance of public health policies for Korean youths to be more physically active, especially during and after the pandemic.

Experimental Investigation of Cavitation Bulk Nanobubbles Characteristics: Effects of pH and Surface-Active Agents.

Nanobubbles (NBs) have a widespread application in antimicrobial activity, wastewater treatment, and ecological restoration due to numerous peculiar characteristics, such as small diameter, long-term stability, and ability to produce hydroxyl radicals. Despite significant applications, only limited comprehensive investigations are available on the role of surfactants and pH in NBs characteristics. Therefore, this study examines the effects of different surfactants (i.e., anionic, cationic, and nonionic) and pH medium on bulk NB formation, diameter, concentration, bubble size distribution (BSD), ζ-potential, and stability. The effect of surfactant at concentrations above and below the critical micelle concentration was investigated. NBs were generated in deionized (DI) water using a piezoelectric transducer. The stability of NBs was assessed by tracking the variation in diameter and concentration over time. In a neutral medium, the diameter of NBs is smaller than in other surfactant or pH mediums. The diameter, concentration, BSD, and stability of NBs are strongly influenced by the ζ-potential rather than the solution medium. BSD curve shifts to a smaller bubble diameter when the magnitude of ζ-potential is high in any solution. In pure water, surfactant, and pH mediums, NBs have existed for a long time. NBs have a shorter life span in environments with a pH ≤ 3. Surfactant adsorption on the surface of NBs increases with increasing surfactant concentration up to a certain limit, beyond which it declines substantially. The Derjaguin-Landau-Verwey-Overbeek (DLVO) theory was used to interpret the NBs stability, resulting in a total potential energy barrier that is positive and greater than 45.55 kBT for 6 ≤ pH ≤ 11, whereas for pH < 6, the potential energy barrier essentially vanishes. Moreover, an effort has also been made to explicate the plausible prospect of ion distribution and its alignment surrounding NBs in cationic and anionic surfactants. This study will extend the in-depth investigation of NBs for industrial applications involving NBs.

An Artificial Intelligence Model for Predicting Trauma Mortality Among Emergency Department Patients in South Korea: Retrospective Cohort Study.

BACKGROUND: Within the trauma system, the emergency department (ED) is the hospital's first contact and is vital for allocating medical resources. However, there is generally limited information about patients that die in the ED. OBJECTIVE: The aim of this study was to develop an artificial intelligence (AI) model to predict trauma mortality and analyze pertinent mortality factors for all patients visiting the ED. METHODS: We used the Korean National Emergency Department Information System (NEDIS) data set (N=6,536,306), incorporating over 400 hospitals between 2016 and 2019. We included the International Classification of Disease 10th Revision (ICD-10) codes and chose the following input features to predict ED patient mortality: age, sex, intentionality, injury, emergent symptom, Alert/Verbal/Painful/Unresponsive (AVPU) scale, Korean Triage and Acuity Scale (KTAS), and vital signs. We compared three different feature set performances for AI input: all features (n=921), ICD-10 features (n=878), and features excluding ICD-10 codes (n=43). We devised various machine learning models with an ensemble approach via 5-fold cross-validation and compared the performance of each model with that of traditional prediction models. Lastly, we investigated explainable AI feature effects and deployed our final AI model on a public website, providing access to our mortality prediction results among patients visiting the ED. RESULTS: Our proposed AI model with the all-feature set achieved the highest area under the receiver operating characteristic curve (AUROC) of 0.9974 (adaptive boosting [AdaBoost], AdaBoost + light gradient boosting machine [LightGBM]: Ensemble), outperforming other state-of-the-art machine learning and traditional prediction models, including extreme gradient boosting (AUROC=0.9972), LightGBM (AUROC=0.9973), ICD-based injury severity scores (AUC=0.9328 for the inclusive model and AUROC=0.9567 for the exclusive model), and KTAS (AUROC=0.9405). In addition, our proposed AI model outperformed a cutting-edge AI model designed for in-hospital mortality prediction (AUROC=0.7675) for all ED visitors. From the AI model, we also discovered that age and unresponsiveness (coma) were the top two mortality predictors among patients visiting the ED, followed by oxygen saturation, multiple rib fractures (ICD-10 code S224), painful response (stupor, semicoma), and lumbar vertebra fracture (ICD-10 code S320). CONCLUSIONS: Our proposed AI model exhibits remarkable accuracy in predicting ED mortality. Including the necessity for external validation, a large nationwide data set would provide a more accurate model and minimize overfitting. We anticipate that our AI-based risk calculator tool will substantially aid health care providers, particularly regarding triage and early diagnosis for trauma patients.

Artificial Intelligence-Driven Respiratory Distress Syndrome Prediction for Very Low Birth Weight Infants: Korean Multicenter Prospective Cohort Study.

BACKGROUND: Respiratory distress syndrome (RDS) is a disease that commonly affects premature infants whose lungs are not fully developed. RDS results from a lack of surfactant in the lungs. The more premature the infant is, the greater is the likelihood of having RDS. However, even though not all premature infants have RDS, preemptive treatment with artificial pulmonary surfactant is administered in most cases. OBJECTIVE: We aimed to develop an artificial intelligence model to predict RDS in premature infants to avoid unnecessary treatment. METHODS: In this study, 13,087 very low birth weight infants who were newborns weighing less than 1500 grams were assessed in 76 hospitals of the Korean Neonatal Network. To predict RDS in very low birth weight infants, we used basic infant information, maternity history, pregnancy/birth process, family history, resuscitation procedure, and test results at birth such as blood gas analysis and Apgar score. The prediction performances of 7 different machine learning models were compared, and a 5-layer deep neural network was proposed in order to enhance the prediction performance from the selected features. An ensemble approach combining multiple models from the 5-fold cross-validation was subsequently developed. RESULTS: Our proposed ensemble 5-layer deep neural network consisting of the top 20 features provided high sensitivity (83.03%), specificity (87.50%), accuracy (84.07%), balanced accuracy (85.26%), and area under the curve (0.9187). Based on the model that we developed, a public web application that enables easy access for the prediction of RDS in premature infants was deployed. CONCLUSIONS: Our artificial intelligence model may be useful for preparations for neonatal resuscitation, particularly in cases involving the delivery of very low birth weight infants, as it can aid in predicting the likelihood of RDS and inform decisions regarding the administration of surfactant.