Clinical efficacy of hydroxychloroquine in patients with covid-19 pneumonia who require oxygen: observational comparative study using routine care data

ObjectiveTo assess the effectiveness of hydroxychloroquine in patients admitted to hospital with coronavirus disease 2019 (covid-19) pneumonia who require oxygen.DesignComparative observational study using data collected from routine care.SettingFour French tertiary care centres providing care to patients with covid-19 pneumonia between 12 March and 31 March 2020.Participants181 patients aged 18-80 years with documented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia who required oxygen but not intensive care.InterventionsHydroxychloroquine at a dose of 600 mg/day within 48 hours of admission to hospital (treatment group) versus standard care without hydroxychloroquine (control group).Main outcome measuresThe primary outcome was survival without transfer to the intensive care unit at day 21. Secondary outcomes were overall survival, survival without acute respiratory distress syndrome, weaning from oxygen, and discharge from hospital to home or rehabilitation (all at day 21). Analyses were adjusted for confounding factors by inverse probability of treatment weighting.ResultsIn the main analysis, 84 patients who received hydroxychloroquine within 48 hours of admission to hospital (treatment group) were compared with 89 patients who did not receive hydroxychloroquine (control group). Eight additional patients received hydroxychloroquine more than 48 hours after admission. In the weighted analyses, the survival rate without transfer to the intensive care unit at day 21 was 76% in the treatment group and 75% in the control group (weighted hazard ratio 0.9, 95% confidence interval 0.4 to 2.1). Overall survival at day 21 was 89% in the treatment group and 91% in the control group (1.2, 0.4 to 3.3). Survival without acute respiratory distress syndrome at day 21 was 69% in the treatment group compared with 74% in the control group (1.3, 0.7 to 2.6). At day 21, 82% of patients in the treatment group had been weaned from oxygen compared with 76% in the control group (weighted risk ratio 1.1, 95% confidence interval 0.9 to 1.3). Eight patients in the treatment group (10%) experienced electrocardiographic modifications that required discontinuation of treatment.ConclusionsHydroxychloroquine has received worldwide attention as a potential treatment for covid-19 because of positive results from small studies. However, the results of this study do not support its use in patients admitted to hospital with covid-19 who require oxygen.

Trajectories of the evolution of post-COVID-19 condition, up to two years after symptoms onset.

OBJECTIVES: We aimed to identify trajectories of the evolution of post-COVID-19 condition, up to 2 years after symptom onset. METHODS: The ComPaRe long COVID e-cohort is a prospective cohort of patients with symptoms lasting at least 2 months after SARS-CoV2 infection. We used trajectory modeling to identify different trajectories in the evolution of post-COVID-19 condition, based on symptoms collected every 60 days using the long COVID Symptom Tool. RESULTS: A total of 2197 patients were enrolled in the cohort between December 2020 and July 2022 when the Omicron variant was not dominant. Three trajectories of the evolution of post-COVID-19 condition were identified: "high persistent symptoms" (4%), "rapidly decreasing symptoms" (5%), and "slowly decreasing symptoms" (91%). Participants with highly persistent symptoms were older and more likely to report a history of systemic diseases. They often reported tachycardia, bradycardia, palpitations, and arrhythmia. Participants with rapidly decreasing symptoms were younger and more likely to report a confirmed infection. They often reported diarrhea and back pain. Participants with slowly decreasing symptoms were more likely to have a history of functional diseases. CONCLUSION: Most patients with post-COVID-19 condition improve slowly over time, while 5% have rapid improvement in the 2 years after symptom onset and 4% have a persistent condition.

Outcome prediction model and prognostic biomarkers for COVID-19 patients in Vietnam.

Background: Accurate prognosis is important either after acute infection or during long-term follow-up of patients infected by severe acute respiratory syndrome coronavirus 2. This study aims to predict coronavirus disease 2019 (COVID-19) severity based on clinical and biological indicators, and to identify biomarkers for prognostic assessment. Methods: We included 261 Vietnamese COVID-19 patients, who were classified into moderate and severe groups. Disease severity prediction based on biomarkers and clinical parameters was performed by applying machine learning and statistical methods using the combination of clinical and biological data. Results: The random forest model could predict with 97% accuracy the likelihood of COVID-19 patients who subsequently worsened to the severe condition. The most important indicators were interleukin (IL)-6, ferritin and D-dimer. The model could still predict with 92% accuracy after removing IL-6 from the analysis to generalise the applicability of the model to hospitals with limited capacity for IL-6 testing. The five most effective indicators were C-reactive protein (CRP), D-dimer, IL-6, ferritin and dyspnoea. Two different sets of biomarkers (D-dimer, IL-6 and ferritin, and CRP, D-dimer and IL-6) are applicable for the assessment of disease severity and prognosis. The two biomarker sets were further tested through machine learning algorithms and relatively validated on two Danish COVID-19 patient groups (n=32 and n=100). The results indicated that various biomarker sets combined with clinical data can be used for detection of the potential to develop the severe condition. Conclusion: This study provided a simple and reliable model using two different sets of biomarkers to assess disease severity and predict clinical outcomes in COVID-19 patients in Vietnam.

The characteristics of SARS-CoV-2-positive children in Australian hospitals: a PREDICT network study.

OBJECTIVES: To examine the clinical characteristics and short term outcomes for children with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections who presented to Australian hospitals during 2020 and 2021. DESIGN, SETTING: Retrospective case review study in nineteen hospitals of the Paediatric Research in Emergency Departments International Collaborative (PREDICT) network from all Australian states and territories, including seven major paediatric tertiary centres and eight Victorian hospitals. PARTICIPANTS: SARS-CoV-2-positive people under 18 years of age who attended emergency departments or were admitted to hospital during 1 February 2020 - 31 December 2021. MAIN OUTCOME MEASURES: Epidemiological and clinical characteristics, by hospital care type (emergency department [ED] or inpatient care). RESULTS: A total of 1193 SARS-CoV-2-positive children and adolescents (527 girls, 44%) attended the participating hospitals (107 in 2020, 1086 in 2021). Their median age was 3.8 years (interquartile range [IQR], 0.8-11.4 years); 63 were Aboriginal or Torres Strait Islander people (5%). Other medical conditions were recorded for 293 children (25%), including asthma (86, 7%) and premature birth (68, 6%). Medical interventions were not required during 795 of 1181 ED presentations (67%); children were discharged directly home in 764 cases (65%) and admitted to hospital in 282 (24%; sixteen to intensive care units). The 384 admissions to hospital (including 102 direct admissions) of 341 children (25 infants under one month of age) included 23 to intensive care (6%); the median length of stay was three days (IQR, 1-9 days). Medical interventions were not required during 261 admissions (68%); 44 children received respiratory support (11%) and 21 COVID-19-specific treatments, including antiviral and biologic agents (5%). Being under three months of age (v one year to less than six years: odds ratio [OR], 2.6; 95% confidence interval [CI], 1.7-4.0) and pre-existing medical conditions (OR, 2.5; 95% CI, 1.9-3.2) were the major predictors of hospital admission. Two children died, including one without a known pre-existing medical condition. CONCLUSION: During 2020 and 2021, most SARS-CoV-2-positive children and adolescents who presented to participating hospitals could be managed as outpatients. Outcomes were generally good, including for those admitted to hospital.

Multiplex RT Real-Time PCR Based on Target Failure to Detect and Identify Different Variants of SARS-CoV-2: A Feasible Method That Can Be Applied in Clinical Laboratories.

Shortly after its emergence, Omicron and its sub-variants have quickly replaced the Delta variant during the current COVID-19 outbreaks in Vietnam and around the world. To enable the rapid and timely detection of existing and future variants for epidemiological surveillance and diagnostic applications, a robust, economical real-time PCR method that can specifically and sensitively detect and identify multiple different circulating variants is needed. The principle of target- failure (TF) real-time PCR is simple. If a target contains a deletion mutation, then there is a mismatch with the primer or probe, and the real-time PCR will fail to amplify the target. In this study, we designed and evaluated a novel multiplex RT real-time PCR (MPL RT-rPCR) based on the principle of target failure to detect and identify different variants of SARS-CoV-2 directly from the nasopharyngeal swabs collected from COVID-19 suspected cases. The primers and probes were designed based on the specific deletion mutations of current circulating variants. To evaluate the results from the MPL RT-rPCR, this study also designed nine pairs of primers for amplifying and sequencing of nine fragments from the S gene containing mutations of known variants. We demonstrated that (i) our MPL RT-rPCR was able to accurately detect multiple variants that existed in a single sample; (ii) the limit of detection of the MPL RT-rPCR in the detection of the variants ranged from 1 to 10 copies for Omicron BA.2 and BA.5, and from 10 to 100 copies for Delta, Omicron BA.1, recombination of BA.1 and BA.2, and BA.4; (iii) between January and September 2022, Omicron BA.1 emerged and co-existed with the Delta variant during the early period, both of which were rapidly replaced by Omicron BA.2, and this was followed by Omicron BA.5 as the dominant variant toward the later period. Our results showed that SARS-CoV-2 variants rapidly evolved within a short period of time, proving the importance of a robust, economical, and easy-to-access method not just for epidemiological surveillance but also for diagnoses around the world where SARS-CoV-2 variants remain the WHO's highest health concern. Our highly sensitive and specific MPL RT-rPCR is considered suitable for further implementation in many laboratories, especially in developing countries.

Efficacy of first dose of covid-19 vaccine versus no vaccination on symptoms of patients with long covid: target trial emulation based on ComPaRe e-cohort

Objective To evaluate the effect of covid-19 vaccination on the severity of symptoms in patients with long covid. Design Target trial emulation based on ComPaRe e-cohort. Data source ComPaRe long covid cohort, a nationwide e-cohort (ie, a cohort where recruitment and follow-up are performed online) of patients with long covid, in France. Methods Adult patients (aged ≥18 years) enrolled in the ComPaRe cohort before 1 May 2021 were included in the study if they reported a confirmed or suspected SARS-CoV-2 infection, symptoms persistent for >3 weeks after onset, and at least one symptom attributable to long covid at baseline. Patients who received a first covid-19 vaccine injection were matched with an unvaccinated control group in a 1:1 ratio according to their propensity scores. Number of long covid symptoms, rate of complete remission of long covid, and proportion of patients reporting an unacceptable symptom state at 120 days were recorded. Results 910 patients were included in the analyses (455 in the vaccinated group and 455 in the control group). By 120 days, vaccination had reduced the number of long covid symptoms (mean 13.0 (standard deviation 9.4) in the vaccinated group v 14.8 (9.8) in the control group;mean difference −1.8, 95% confidence interval −3.0 to −0.5) and doubled the rate of patients in remission (16.6% v 7.5%, hazard ratio 1.93, 95% confidence interval 1.18 to 3.14). Vaccination reduced the effect of long covid on patients' lives (mean score on the impact tool 24.3 (standard deviation 16.7) v 27.6 (16.7);mean difference −3.3, 95% confidence interval −5.7 to −1.0) and the proportion of patients with an unacceptable symptom state (38.9% v 46.4%, risk difference −7.4%, 95% confidence interval −14.5% to −0.3%). In the vaccinated group, two (0.4%) patients reported serious adverse events requiring admission to hospital. Conclusion In this study, covid-19 vaccination reduced the severity of symptoms and the effect of long covid on patients' social, professional, and family lives at 120 days in those with persistent symptoms of infection.

Efficacy of first dose of covid-19 vaccine versus no vaccination on symptoms of patients with long covid: target trial emulation based on ComPaRe e-cohort.

Objective: To evaluate the effect of covid-19 vaccination on the severity of symptoms in patients with long covid. Design: Target trial emulation based on ComPaRe e-cohort. Data source: ComPaRe long covid cohort, a nationwide e-cohort (ie, a cohort where recruitment and follow-up are performed online) of patients with long covid, in France. Methods: Adult patients (aged ≥18 years) enrolled in the ComPaRe cohort before 1 May 2021 were included in the study if they reported a confirmed or suspected SARS-CoV-2 infection, symptoms persistent for >3 weeks after onset, and at least one symptom attributable to long covid at baseline. Patients who received a first covid-19 vaccine injection were matched with an unvaccinated control group in a 1:1 ratio according to their propensity scores. Number of long covid symptoms, rate of complete remission of long covid, and proportion of patients reporting an unacceptable symptom state at 120 days were recorded. Results: 910 patients were included in the analyses (455 in the vaccinated group and 455 in the control group). By 120 days, vaccination had reduced the number of long covid symptoms (mean 13.0 (standard deviation 9.4) in the vaccinated group v 14.8 (9.8) in the control group; mean difference -1.8, 95% confidence interval -3.0 to -0.5) and doubled the rate of patients in remission (16.6% v 7.5%, hazard ratio 1.93, 95% confidence interval 1.18 to 3.14). Vaccination reduced the effect of long covid on patients' lives (mean score on the impact tool 24.3 (standard deviation 16.7) v 27.6 (16.7); mean difference -3.3, 95% confidence interval -5.7 to -1.0) and the proportion of patients with an unacceptable symptom state (38.9% v 46.4%, risk difference -7.4%, 95% confidence interval -14.5% to -0.3%). In the vaccinated group, two (0.4%) patients reported serious adverse events requiring admission to hospital. Conclusion: In this study, covid-19 vaccination reduced the severity of symptoms and the effect of long covid on patients' social, professional, and family lives at 120 days in those with persistent symptoms of infection.

Targeting Olokizumab-Interleukin 6 interaction interface to discover novel IL-6 inhibitors.

The IL-6/IL-6R or IL-6/GP130 protein-protein interactions play a significant role in controlling the development of chronic inflammatory diseases, such as rheumatoid arthritis, Castleman disease, psoriasis, and, most recently, COVID-19. Modulating or antagonizing protein-protein interactions of IL6 binding to its receptors by oral drugs promises similar efficacy to biological therapy in patients, namely monoclonal antibodies. In this study, we used a crystal structure of the Fab part of olokizumab in a complex with IL-6 (PDB ID: 4CNI) to uncover starting points for small molecule IL-6 antagonist discovery. Firstly, a structure­based pharmacophore model of the protein active site cavity was generated to identify possible candidates, followed by virtual screening with a significant database Drugbank. After the docking protocol validation, a virtual screening by molecular docking was carried out and a total of 11 top hits were reported. Detailed analysis of the best scoring molecules was performed with ADME/T analysis and molecular dynamics simulation. Furthermore, the Molecular Mechanics-Generalized Born Surface Area (MM/GBSA) technique has been utilized to evaluate the free binding energy. Based on the finding, one newly obtained compound in this study, namely DB15187, may serve as a lead compound for the discovery of IL-6 inhibitors.Communicated by Ramaswamy H. Sarma.

Outcome prediction model and prognostic biomarkers for COVID-19 patients in Vietnam

Introduction Accurate prognosis is important either after acute infection or during long-term follow-up of patients infected by SARS-CoV-2. This study aims to predict COVID-19 severity based on clinical and biological indicators, and to identify biomarkers for prognostic assessment. Methods We included 261 Vietnamese COVID-19 patients, who were classified into moderate and severe groups. Disease severity prediction based on biomarkers and clinical parameters was performed by applying machine learning and statistical methods using the combination of clinical and biological data. Results The random forest model could predict with 97% accuracy the likelihood of COVID-19 patients who subsequently worsened to severe condition. The most important indicators were IL-6, Ferritin, and D-dimer. The model could still predict with 92% accuracy after removing IL-6 from analysis to generalize applicability of the model to hospitals with limited capacity for IL-6 testing. The five most effective indicators were CRP, D-dimer, IL-6, Ferritin, and dyspnoea. Two different sets of biomarkers (D-dimer, IL-6, and Ferritin;and CRP, D-dimer, and IL-6) are applicable for the assessment of disease severity and prognosis. The two biomarker sets were further tested through the machine learning algorithms random forest;and relatively validated on two Danish COVID-19 patient groups (n=32;and n=100). The results indicated various biomarker sets combined with clinical data can be used for detection of potential develop severe conditions. Conclusion This study provided a simple and reliable model using two different sets of biomarkers to assess disease severity and predict clinical outcomes in COVID-19 patients in Vietnam.

COVID-19 in Vietnam and Its Impact on Road Trauma: Retrospective Study Based on National Data.

BACKGROUND: Despite significant improvement in the last decade, road trauma remains a substantial contributor to deaths in Vietnam. The COVID-19 pandemic necessitated public health measures that had an unforeseen benefit on road trauma in high-income countries. We investigate if this reduction was also seen in a low- to middle-income country like Vietnam. OBJECTIVE: Our aim was to investigate how the COVID-19 pandemic and the government policies implemented in response to it impacted road trauma fatalities in Vietnam. We also compared this impact to other government policies related to road trauma implemented in the preceding 14 years (2007-2020). METHODS: COVID-19 data were extracted from the Vietnamese Ministry of Health database. Road traffic deaths from 2007 to 2021 were derived from the Vietnamese General Statistical Office. We used Stata software (version 17; StataCorp) for statistical analysis. Poisson regression modeling was used to estimate trends in road fatality rates based on annual national mortality data for the 2007-2021 period. The actual change in road traffic mortality in 2021 was compared with calculated figures to demonstrate the effect of COVID-19 on road trauma fatalities. We also compared this impact to other government policies that aimed to reduce traffic-related fatalities from 2007 to 2020. RESULTS: Between 2007 and 2020, the number of annual road traffic deaths decreased by more than 50%, from 15.3 to 7 per 100,000 population, resulting in an average reduction of 5.4% per annum. We estimated that the road traffic mortality rate declined by 12.1% (95% CI 8.9-15.3%) in 2021 relative to this trend. The actual number of road trauma deaths fell by 16.4%. This reduction was largely seen from August to October 2021 when lockdown and social distancing measures were in force. CONCLUSIONS: In 2021, the road traffic-related death reduction in Vietnam was 3 times greater than the trend seen in the preceding 14 years. The public health response to the COVID-19 pandemic in Vietnam was associated with a third of this reduction. It can thus be concluded that government policies implemented to address the COVID-19 pandemic resulted in a 4.3% decrease in road traffic deaths in 2021. This has been observed in high-income countries, but we have demonstrated this for the first time in a low- and middle-income country.

Identification of small molecules as potential inhibitors of interleukin 6: a multi-computational investigation.

IL(interleukin)-6 is a multifunctional cytokine crucial for immunological, hematopoiesis, inflammation, and bone metabolism. Strikingly, IL-6 has been shown to significantly contribute to the initiation of cytokine storm-an acute systemic inflammatory syndrome in Covid-19 patients. Recent study has showed that blocking the IL-6 signaling pathway with an anti-IL-6 receptor monoclonal antibody (mAb) can reduce the severity of COVID-19 symptoms and enhance patient survival. However, the mAb has several drawbacks, such as high cost, potential immunogenicity, and invasive administration due to the large-molecule protein product. Instead, these issues could be mitigated using small molecule IL-6 inhibitors, but none are currently available. This study aimed to discover IL-6 inhibitors based on the PPI with a novel camelid Fab fragment, namely 68F2, in a crystal protein complex structure (PDB ID: 4ZS7). The pharmacophore models and molecular docking were used to screen compounds from DrugBank databases. The oral bioavailability of the top 24 ligands from the screening was predicted by the SwissAMDE tool. Subsequently, the selected molecules from docking and MD simulation illustrated a promising binding affinity in the formation of stable complexes at the active binding pocket of IL-6. Binding energies using the MM-PBSA technique were applied to the top 4 hit compounds. The result indicated that DB08402 and DB12903 could form strong interactions and build stable protein-ligand complexes with IL-6. These potential compounds may serve as a basis for further developing small molecule IL-6 inhibitors in the future.

Exploration of chalcones as 3-chymotrypsin-like protease (3CLpro) inhibitors of SARS-CoV-2 using computational approaches.

The main protease 3CLpro is one of the potential targets against coronavirus. Inhibiting this enzyme leads to the interruption of viral replication. Chalcone and its derivatives were reported to possess the ability to bind to 3CLpro protease in the binding pocket. This study explored an in-house database of 269 chalcones as 3CLpro inhibitors using in silico screening models, including molecular docking, molecular dynamics simulation, binding free energy calculation, and ADME prediction. C264 and C235 stand out as the two most potential structures. The top hit compound C264 was with the Jamda score of -2.8329 and the MM/GBSA binding energy mean value of -28.23 ± 3.53 kcal/mol, which was lower than the reference ligand. Despite the lower mean binding energy (-22.07 ± 3.39 kcal/mol), in-depth analysis of binding interaction suggested C235 could be another potential candidate. Further, in vitro and in vivo experiments are required to confirm the inhibitory ability. Supplementary Information: The online version contains supplementary material available at 10.1007/s11224-022-02000-3.

Temporal trends in calls for suicide attempts to poison control centers in France during the COVID-19 pandemic: a nationwide study.

Concerns have been raised about early vs. later impacts of the COVID-19 pandemic on suicidal behavior. However, data remain sparse to date. We investigated all calls for intentional drug or other toxic ingestions to the eight Poison Control Centers in France between 1st January 2018 and 31st May 2022. Data were extracted from the French National Database of Poisonings. Calls during the study period were analyzed using time trends and time series analyses with SARIMA models (based on the first two years). Breakpoints were determined using Chow test. These analyses were performed together with examination of age groups (≤ 11, 12-24, 25-64, ≥ 65 years) and gender effects when possible. Over the studied period, 66,589 calls for suicide attempts were received. Overall, there was a downward trend from 2018, which slowed down in October 2019 and was followed by an increase from November 2020. Number of calls observed during the COVID period were above what was expected. However, important differences were found according to age and gender. The increase in calls from mid-2020 was particularly observed in young females, while middle-aged adults showed a persisting decrease. An increase in older-aged people was observed from mid-2019 and persisted during the pandemic. The pandemic may therefore have exacerbated a pre-existing fragile situation in adolescents and old-aged people. This study emphasizes the rapidly evolving situation regarding suicidal behaviour during the pandemic, the possibility of age and gender differences in impact, and the value of having access to real-time information to monitor suicidal acts.

Course of post COVID-19 disease symptoms over time in the ComPaRe long COVID prospective e-cohort.

About 10% of people infected by severe acute respiratory syndrome coronavirus 2 experience post COVID-19 disease. We analysed data from 968 adult patients (5350 person-months) with a confirmed infection enroled in the ComPaRe long COVID cohort, a disease prevalent prospective e-cohort of such patients in France. Day-by-day prevalence of post COVID-19 symptoms was determined from patients' responses to the Long COVID Symptom Tool, a validated self-reported questionnaire assessing 53 symptoms. Among patients symptomatic after 2 months, 85% still reported symptoms one year after their symptom onset. Evolution of symptoms showed a decreasing prevalence over time for 27/53 symptoms (e.g., loss of taste/smell); a stable prevalence over time for 18/53 symptoms (e.g., dyspnoea), and an increasing prevalence over time for 8/53 symptoms (e.g., paraesthesia). The disease impact on patients' lives began increasing 6 months after onset. Our results are of importance to understand the natural history of post COVID-19 disease.

Development and Validation of the Long Coronavirus Disease (COVID) Symptom and Impact Tools: A Set of Patient-Reported Instruments Constructed From Patients' Lived Experience.

BACKGROUND: To develop and validate patient-reported instruments, based on patients' lived experiences, for monitoring the symptoms and impact of long coronavirus disease (covid). METHODS: The long covid Symptom and Impact Tools (ST and IT) were constructed from the answers to a survey with open-ended questions to 492 patients with long COVID. Validation of the tools involved adult patients with suspected or confirmed coronavirus disease 2019 (COVID-19) and symptoms extending over 3 weeks after onset. Construct validity was assessed by examining the relations of the ST and IT scores with health-related quality of life (EQ-5D-5L), function (PCFS, post-COVID functional scale), and perceived health (MYMOP2, Measure yourself medical outcome profile 2). Reliability was determined by a test-retest. The "patient acceptable symptomatic state" (PASS) was determined by the percentile method. RESULTS: Validation involved 1022 participants (55% with confirmed COVID-19, 79% female, and 12.5% hospitalized for COVID-19). The long COVID ST and IT scores were strongly correlated with the EQ-5D-5L (rs = -0.45 and rs = -0.59, respectively), the PCFS (rs = -0.39 and rs = -0.55), and the MYMOP2 (rs = -0.40 and rs = -0.59). Reproducibility was excellent with an interclass correlation coefficient of 0.83 (95% confidence interval .80 to .86) for the ST score and 0.84 (.80 to .87) for the IT score. In total, 793 (77.5%) patients reported an unacceptable symptomatic state, thereby setting the PASS for the long covid IT score at 30 (28 to 33). CONCLUSIONS: The long covid ST and IT tools, constructed from patients' lived experiences, provide the first validated and reliable instruments for monitoring the symptoms and impact of long covid.

Preferences for Alternative Care Modalities Among French Adults With Chronic Illness.

Importance: The COVID-19 pandemic led to the implementation of alternative care modalities (eg, teleconsultations and task shifting) that will continue to be implemented in parallel to traditional care after the pandemic. An ideal balance between alternative and traditional care modalities is unknown. Objectives: To quantify the ideal postpandemic balance between alternative and traditional care modalities among patients with chronic illness and to qualify the circumstances in which patients consider it appropriate to replace traditional care with alternative care. Design, Setting, and Participants: This survey study invited 5999 adults with chronic illness in ComPaRe, a French nationwide e-cohort of adults with chronic conditions who volunteer their time to participate in research projects, to participate in this study, which was performed from January 27 to February 23, 2021. Main Outcomes and Measures: Participants rated the ideal proportion at which they would use 3 alternative care modalities instead of the traditional care equivalent on a 0% to 100% scale (with 0% indicating using alternative care modalities for none of one's future care and 100% indicating using alternative care modalities for all of one's future care) of their overall future care: (1) teleconsultations, (2) online symptom-checkers to react to new symptoms, and (3) remote monitoring to adapt treatment outside consultations. The median ideal proportion of alternative care use was calculated. Perceived appropriate circumstances in which each alternative modality could replace traditional care were collected with open-ended questions. Analyses were performed on a weighted data set representative of patients with chronic illness in France. Results: Of the 5999 invited individuals, 1529 (mean [SD] age, 50.3 [14.7] years; 1072 [70.1%] female) agreed to participate (participation rate, 25.5%). Participants would choose teleconsultations for 50.0% of their future consultations (IQR, 11.0%-52.0%), online symptom-checkers over contacting their physician for 22.0% of new symptoms (IQR, 2.0%-50.0%), and remote monitoring instead of consultations for 52.3% of their treatment adaptations (IQR, 25.4%-85.4%). Participants reported 67 circumstances for which replacing traditional with alternative care modalities was considered appropriate, including 31 care activities (eg, prescription renewal and addressing acute or minor complaints), 25 patient characteristics (eg, stable chronic condition and established patient-physician relationship), and 11 required characteristics of the alternative care modalities (eg, quality assurance). Conclusions and Relevance: Results of this survey study suggest that after the pandemic, patients would choose alternative over traditional care for 22% to 52% of the time across different care needs. Participants proposed 67 criteria to guide clinicians in replacing traditional care with alternative care. These findings provide a guide for redesigning care in collaboration with patients after the pandemic.

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing-Part I: Fundamentals and Enabling Technologies.

Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community. This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In this Part I, we provide a comprehensive background of social distancing including basic concepts, measurements, models, and propose various practical social distancing scenarios. We then discuss enabling wireless technologies which are especially effect- in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. The companion paper Part II surveys other emerging and related technologies, such as machine learning, computer vision, thermal, ultrasound, etc., and discusses open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice.

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing-Part II: Emerging Technologies and Open Issues.

This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In Part I, an extensive background of social distancing is provided, and enabling wireless technologies are thoroughly surveyed. In this Part II, emerging technologies such as machine learning, computer vision, thermal, ultrasound, etc., are introduced. These technologies open many new solutions and directions to deal with problems in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. Finally, we discuss open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice. As an example, instead of reacting with ad-hoc responses to COVID-19-like pandemics in the future, smart infrastructures (e.g., next-generation wireless systems like 6G, smart home/building, smart city, intelligent transportation systems) should incorporate a pandemic mode in their standard architectures/designs.

Impact of an interactive web tool on patients' intention to receive COVID-19 vaccination: a before-and-after impact study among patients with chronic conditions in France.

OBJECTIVES: In France, about 30% of the population refuses COVID-19 vaccination outright, and 9 to 40% are hesitant. We developed and evaluated an interactive web tool providing transparent and reliable information on the benefits and risks of COVID-19 vaccination. METHODS: The most recent scientific data at the time of the study were implemented into an interactive web tool offering individualized information on the risks of COVID-19 infection-related events versus vaccination-related serious adverse events. The tool was evaluated during a before-and-after impact study nested in ComPaRe, a French e-cohort of adult patients with chronic conditions. Primary outcome was the proportion of patients intending to receive vaccination after using the tool, among those not intending to receive it at baseline. RESULTS: Between January 8 and 14, 2021, we enrolled 3152 patients in the study [mean age 55.2 (SD: 16.9), 52.9% women and 63% with ≥ 2 chronic conditions]. Before consulting the tool, 961 (30.5%) refused to be vaccinated until further data on efficacy/safety was obtained and 239 (7.5%) outright refused vaccination. Among these 1200 patients, 96 (8.0%, number needed to treat: 12.5) changed their mind after consulting the tool and would subsequently accept vaccination. CONCLUSIONS: Our interactive web tool represents a scalable method to help increase the intent to receive COVID-19 vaccination among patients with chronic conditions and address vaccine hesitancy. Since April 2021, our tool has been embedded on the official webpage of the French Government for COVID-19 information.