Developing Treatment Guidelines During a Pandemic Health Crisis: Lessons Learned From COVID-19

Finding Long-COVID: Temporal Topic Modeling of Electronic Health Records from the N3C and RECOVER Programs

Post-Acute Sequelae of SARS-CoV-2 infection (PASC), also known as Long-COVID, encompasses a variety of complex and varied outcomes following COVID-19 infection that are still poorly understood. We clustered over 600 million condition diagnoses from 14 million patients available through the National COVID Cohort Collaborative (N3C), generating hundreds of highly detailed clinical phenotypes. Assessing patient clinical trajectories using these clusters allowed us to identify individual conditions and phenotypes strongly increased after acute infection. We found many conditions increased in COVID-19 patients compared to controls, and using a novel method to associate patients with clusters over time, we additionally found phenotypes specific to patient sex, age, wave of infection, and PASC diagnosis status. While many of these results reflect known PASC symptoms, the resolution provided by this unprecedented data scale suggests avenues for improved diagnostics and mechanistic understanding of this multifaceted disease.

Effectiveness of regdanvimab on mortality in COVID-19 infected patients on hemodialysis

BACKGROUND

Although several therapeutic agents have been evaluated for the treatment of coronavirus disease 2019 (COVID-19), there are lack of effective and proven treatments for end-stage renal disease (ESRD). The present study aims to evaluate the effectiveness of regdanvimab on mortality in COVID-19-infected patients on hemodialysis (HD).

METHODS

We conducted an observational retrospective study in 230 COVID-19-infected patients on HD, of whom 77 (33.5%) were administered regdanvimab alone or in combination with dexamethasone or remdesivir during hospitalization (regdanvimab group) and 153 patients (66.5%) were not (no regdanvimab group). The primary outcome was in-hospital mortality. We compared mortality rates according to the use of regdanvimab and investigated the factors associated with mortality.

RESULTS

Fifty-nine deaths occurred during hospitalization, 49 in the no regdanvimab group (32.0%) and 10 in the regdanvimab group (13.0%), and the mortality rate was significantly higher in the no regdanvimab group than that in the regdanvimab group (p = 0.001). Multivariate Cox regression analysis showed that malignancy (p = 0.001), SPO2 of <95% at admission (p = 0.003), and administration of antibiotics and regdanvimab (p = 0.007 and p = 0.002, respectively) were significantly associated factors with mortality.

CONCLUSION

Regdanvimab administration is beneficial in improving prognosis in hospitalized COVID-19 patients on HD. Considering the vulnerability to infection and high mortality of ESRD patients, regdanvimab may be considered as a therapeutic option in COVID-19 patients on HD.

Oral bemnifosbuvir (AT-527) vs placebo in patients with mild-to-moderate COVID-19 in an outpatient setting (MORNINGSKY)

Aim: This phase III study assessed the efficacy/safety/antiviral activity/pharmacokinetics of bemnifosbuvir, a novel, oral nucleotide analog to treat COVID-19. Patients & methods: Outpatient adults/adolescents with mild-to-moderate COVID-19 were randomized 2:1 to bemnifosbuvir/placebo. Time to symptom alleviation/improvement (primary outcome), risk of hospitalization/death, viral load and safety were evaluated. Results: Although the study was discontinued prematurely and did not meet its primary end point, bemnifosbuvir treatment resulted in fewer hospitalizations (71% relative risk reduction), COVID-19-related medically attended hospital visits, and COVID-19-related complications compared with placebo. No reduction in viral load was observed. The proportion of patients with adverse events was similar; no deaths occurred. Conclusion: Bemnifosbuvir showed hospitalization reduction in patients with variable disease progression risk and was well tolerated. Clinical Trial Registration: NCT04889040 (ClinicalTrials.gov).

Lessons Learned from the Lessons Learned in Public Health during the First Years of COVID-19 Pandemic

(1) Objectives: to investigate the main lessons learned from the public health (PH) response to COVID-19, using the global perspective endorsed by the WHO pillars, and understand what countries have learned from their practical actions. (2) Methods: we searched for articles in PubMed and CINAHL from 1 January 2020 to 31 January 2022. 455 articles were included. Inclusion criteria were PH themes and lessons learned from the COVID-19 pandemic. One hundred and forty-four articles were finally included in a detailed scoping review. (3) Findings: 78 lessons learned were available, cited 928 times in the 144 articles. Our review highlighted 5 main lessons learned among the WHO regions: need for continuous coordination between PH institutions and organisations (1); importance of assessment and evaluation of risk factors for the diffusion of COVID-19, identifying vulnerable populations (2); establishment of evaluation systems to assess the impact of planned PH measures (3); extensive application of digital technologies, telecommunications and electronic health records (4); need for periodic scientific reviews to provide regular updates on the most effective PH management strategies (5). (4) Conclusion: lessons found in this review could be essential for the future, providing recommendations for an increasingly flexible, fast and efficient PH response to a healthcare emergency such as the COVID-19 pandemic.

Prospective validation of a dynamic prognostic model for identifying COVID-19 patients at high risk of rapid deterioration

BACKGROUND

We sought to develop and prospectively validate a dynamic model that incorporates changes in biomarkers to predict rapid clinical deterioration in patients hospitalized for COVID-19.

METHODS

We established a retrospective cohort of hospitalized patients aged ≥18 years with laboratory-confirmed COVID-19 using electronic health records (EHR) from a large integrated care delivery network in Massachusetts including >40 facilities from March to November 2020. A total of 71 factors, including time-varying vital signs and laboratory findings during hospitalization were screened. We used elastic net regression and tree-based scan statistics for variable selection to predict rapid deterioration, defined as progression by two levels of a published severity scale in the next 24 h. The development cohort included the first 70% of patients identified chronologically in calendar time; the latter 30% served as the validation cohort. A cut-off point was estimated to alert clinicians of high risk of imminent clinical deterioration.

RESULTS

Overall, 3706 patients (2587 in the development and 1119 in the validation cohort) met the eligibility criteria with a median of 6 days of follow-up. Twenty-four variables were selected in the final model, including 16 dynamic changes of laboratory results or vital signs. Area under the ROC curve was 0.81 (95% CI, 0.79-0.82) in the development set and 0.74 (95% CI, 0.71-0.78) in the validation set. The model was well calibrated (slope = 0.84 and intercept = -0.07 on the calibration plot in the validation set). The estimated cut-off point, with a positive predictive value of 83%, was 0.78.

CONCLUSIONS

Our prospectively validated dynamic prognostic model demonstrated temporal generalizability in a rapidly evolving pandemic and can be used to inform day-to-day treatment and resource allocation decisions based on dynamic changes in biophysiological factors.

Predicting the outcome for COVID-19 patients by applying time series classification to electronic health records

Background

COVID-19 caused more than 622 thousand deaths in Brazil. The infection can be asymptomatic and cause mild symptoms, but it also can evolve into a severe disease and lead to death. It is difficult to predict which patients will develop severe disease. There are, in the literature, machine learning models capable of assisting diagnose and predicting outcomes for several diseases, but usually these models require laboratory tests and/or imaging.

Methods

We conducted a observational cohort study that evaluated vital signs and measurements from patients who were admitted to Hospital das Clínicas (São Paulo, Brazil) between March 2020 and October 2021 due to COVID-19. The data was then represented as univariate and multivariate time series, that were used to train and test machine learning models capable of predicting a patient’s outcome.

Results

Time series-based machine learning models are capable of predicting a COVID-19 patient’s outcome with up to 96% general accuracy and 81% accuracy considering only the first hospitalization day. The models can reach up to 99% sensitivity (discharge prediction) and up to 91% specificity (death prediction).

Conclusions

Results indicate that time series-based machine learning models combined with easily obtainable data can predict COVID-19 outcomes and support clinical decisions. With further research, these models can potentially help doctors diagnose other diseases.

Temporal Improvements in COVID-19 Outcomes for Hospitalized Adults: A Post Hoc Observational Study of Remdesivir Group Participants in the Adaptive COVID-19 Treatment Trial

BACKGROUND

The COVID-19 standard of care (SOC) evolved rapidly during 2020 and 2021, but its cumulative effect over time is unclear.

OBJECTIVE

To evaluate whether recovery and mortality improved as SOC evolved, using data from ACTT (Adaptive COVID-19 Treatment Trial).

DESIGN

ACTT is a series of phase 3, randomized, double-blind, placebo-controlled trials that evaluated COVID-19 therapeutics from February 2020 through May 2021. ACTT-1 compared remdesivir plus SOC to placebo plus SOC, and in ACTT-2 and ACTT-3, remdesivir plus SOC was the control group. This post hoc analysis compared recovery and mortality between these comparable sequential cohorts of patients who received remdesivir plus SOC, adjusting for baseline characteristics with propensity score weighting. The analysis was repeated for participants in ACTT-3 and ACTT-4 who received remdesivir plus dexamethasone plus SOC. Trends in SOC that could explain outcome improvements were analyzed. (ClinicalTrials.gov: NCT04280705 [ACTT-1], NCT04401579 [ACTT-2], NCT04492475 [ACTT-3], and NCT04640168 [ACTT-4]).

SETTING

94 hospitals in 10 countries (86% U.S. participants).

PARTICIPANTS

Adults hospitalized with COVID-19.

INTERVENTION

SOC.

MEASUREMENTS

28-day mortality and recovery.

RESULTS

Although outcomes were better in ACTT-2 than in ACTT-1, adjusted hazard ratios (HRs) were close to 1 (HR for recovery, 1.04 [95% CI, 0.92 to 1.17]; HR for mortality, 0.90 [CI, 0.56 to 1.40]). Comparable patients were less likely to be intubated in ACTT-2 than in ACTT-1 (odds ratio, 0.75 [CI, 0.53 to 0.97]), and hydroxychloroquine use decreased. Outcomes improved from ACTT-2 to ACTT-3 (HR for recovery, 1.43 [CI, 1.24 to 1.64]; HR for mortality, 0.45 [CI, 0.21 to 0.97]). Potential explanatory factors (SOC trends, case surges, and variant trends) were similar between ACTT-2 and ACTT-3, except for increased dexamethasone use (11% to 77%). Outcomes were similar in ACTT-3 and ACTT-4. Antibiotic use decreased gradually across all stages.

LIMITATION

Unmeasured confounding.

CONCLUSION

Changes in patient composition explained improved outcomes from ACTT-1 to ACTT-2 but not from ACTT-2 to ACTT-3, suggesting improved SOC. These results support excluding nonconcurrent controls from analysis of platform trials in rapidly changing therapeutic areas.

PRIMARY FUNDING SOURCE

National Institute of Allergy and Infectious Diseases.

Selective serotonin reuptake inhibitors: New hope in the fight against COVID-19

The emerging COVID-19 pandemic led to a dramatic increase in global mortality and morbidity rates. As in most infections, fatal complications of coronavirus affliction are triggered by an untrammeled host inflammatory response. Cytokine storms created by high levels of interleukin and other cytokines elucidate the pathology of severe COVID-19. In this respect, repurposing drugs that are already available and might exhibit anti-inflammatory effects have received significant attention. With the in vitro and clinical investigation of several studies on the effect of antidepressants on COVID-19 prognosis, previous data suggest that selective serotonin reuptake inhibitors (SSRIs) might be the new hope for the early treatment of severely afflicted patients. SSRIs' low cost and availability make them potentially eligible for COVID-19 repurposing. This review summarizes current achievements and literature about the connection between SSRIs administration and COVID-19 prognosis.

Preparing for pandemics: a systematic review of pandemic influenza clinical management guidelines

BACKGROUND

The COVID-19 pandemic has highlighted the importance of evidence-based clinical decision-making. Clinical management guidelines (CMGs) may help reduce morbidity and mortality by improving the quality of clinical decisions. This systematic review aims to evaluate the availability, inclusivity, and quality of pandemic influenza CMGs, to identify gaps that can be addressed to strengthen pandemic preparedness in this area.

METHODS

Ovid Medline, Ovid Embase, TRIP (Turning Research Into Practice), and Guideline Central were searched systematically from January 2008 to 23rd June 2022, complemented by a grey literature search till 16th June 2022. Pandemic influenza CMGs including supportive care or empirical treatment recommendations were included. Two reviewers independently extracted data from the included studies and assessed their quality using AGREE II (Appraisal of Guidelines for Research & Evaluation). The findings are presented narratively.

RESULTS

Forty-eight CMGs were included. They were produced in high- (42%, 20/48), upper-middle- (40%, 19/48), and lower-middle (8%, 4/48) income countries, or by international organisations (10%, 5/48). Most CMGs (81%, 39/48) were over 5 years old. Guidelines included treatment recommendations for children (75%, 36/48), pregnant women (54%, 26/48), people with immunosuppression (33%, 16/48), and older adults (29%, 14/48). Many CMGs were of low quality (median overall score: 3 out of 7 (range 1-7). All recommended oseltamivir; recommendations for other neuraminidase inhibitors and supportive care were limited and at times contradictory. Only 56% (27/48) and 27% (13/48) addressed oxygen and fluid therapy, respectively.

CONCLUSIONS

Our data highlights the limited availability of up-to-date pandemic influenza CMGs globally. Of those identified, many were limited in scope and quality and several lacked recommendations for specific at-risk populations. Recommendations on supportive care, the mainstay of treatment, were limited and heterogeneous. The most recent guideline highlighted that the evidence-base to support antiviral treatment recommendations is still limited. There is an urgent need for trials into treatment and supportive care strategies including for different risk populations. New evidence should be incorporated into globally accessible guidelines, to benefit patient outcomes. A 'living guideline' framework is recommended and further research into guideline implementation in different resourced settings, particularly low- and middle-income countries.

Most published systematic reviews of remdesivir for COVID-19 were redundant and lacked currency

Objective

To investigate the completeness and currency of published systematic reviews of remdesivir for COVID-19 and to compare this with a living guidelines approach.

Study Design and Setting

In this cross-sectional study, we searched Europe PMC on May 20, 2021 for systematic reviews of remdesivir (including preprints, living review updates). Completeness and currency were based on the inclusion of four major randomized trials of remdesivir available at the time of publication of the review (including as preliminary results and preprints).

Results

We included 38 reviews (45 reports), equivalent to a new publication every 9 days. 23 (51%) reports were out of date at the time of publication. Eleven reviews that were current on publication had a median survival time of 10 days (range 4–57). A third of reviews cited other systematic reviews, but only four provided justifications for why another review was necessary. Eight (21%) of the reviews were registered in PROSPERO. The Australian COVID-19 Clinical Evidence Taskforce living guidelines were updated within 14 days for three of the remdesivir trials, and within 28 days for the fourth.

Conclusion

There was considerable duplication of systematic reviews of remdesivir, and half were already out of date at the time of publication.

Ongoing Use of SSRIs Does Not Alter Outcome in Hospitalized COVID-19 Patients: A Retrospective Analysis

SARS-CoV-2 continues to have devastating consequences worldwide. Though vaccinations have helped reduce spread, new strains still pose a threat. Therefore, it is imperative to identify treatments that prevent severe COVID-19 infection. Recently, acute use of SSRI antidepressants in COVID+ patients was shown to reduce symptom severity. The aim of this retrospective observational study was to determine whether COVID+ patients already on SSRIs upon hospital admission had reduced mortality compared to COVID+ patients not on chronic SSRI treatment. Electronic medical records of 9044 patients with laboratory-confirmed COVID-19 from six hospitals were queried for demographic and clinical information. Using R, a logistic regression model was run with mortality as the outcome and SSRI status as the exposure. In this sample, no patients admitted on SSRIs had them discontinued. There was no significant difference in the odds of dying between COVID+ patients on chronic SSRIs vs. those not taking SSRIs, after controlling for age category, gender, and race. This study shows the utility of large clinical databases in determining what commonly prescribed drugs might be useful in treating COVID-19. During pandemics due to novel infectious agents, it is critical to evaluate safety and efficacy of drugs that might be repurposed for treatment.

Awareness, value and use of the Australian living guidelines for the clinical care of people with COVID-19: an impact evaluation

BACKGROUND AND OBJECTIVE

The Australian National COVID-19 Clinical Evidence Taskforce is developing living, evidence-based, national guidelines for treatment of people with COVID-19. These living guidelines are updated each week. We undertook an impact evaluation to understand the extent to which health professionals providing treatment to people with COVID 19 were aware of, valued and used the guidelines, and the factors that enabled or hampered this.

METHODS

A mixed methods approach was used for the evaluation. Surveys were conducted to collect both quantitative and qualitative data and were supplemented with qualitative interviews. Australian healthcare practitioners potentially providing care to individuals with suspected or confirmed COVID-19 were invited to participate. Data were collected on guideline awareness, relevance, ease of use, trustworthiness, value, importance of updating, use, and strengths and opportunities for improvement.

RESULTS

A total of 287 people completed the surveys and 10 interviews were conducted during November 2020. Awareness of the work of the Taskforce was high and the vast majority of respondents reported that the guidelines were very or extremely relevant, easy to use, trustworthy and valuable. More than 50% of respondents had used the guidelines to support their own clinical decision-making; and 30% were aware of other examples of the guidelines being used. Qualitative data revealed that amongst an overwhelming morass of evidence and opinions during the COVID-19 pandemic, the guidelines have been a reliable, united source of evidence-based advice; participants felt the guidelines built confidence and provided reassurance in clinical decision-making. Opportunities to improve awareness and accessibility to the guidelines were also explored.

CONCLUSIONS

As of June 2021, the guidelines have been published and updated more than 40 times, include more than 140 recommendations and are being used to inform clinical decisions. The findings of this impact evaluation will be used to improve processes and outputs of the Taskforce and guidelines project, and to inform future living guideline projects.

Selecting Treatments During an Infectious Disease Pandemic: Chasing the Evidence

In their article, Mehta and colleagues describe temporal trends in the use of hydroxychloroquine, remdesivir, and dexamethasone for the treatment of COVID-19 in patients hospitalized in the United States over a 13-month period beginning in February 2020. The editorialists discuss the findings and lessons learned from COVID-19 that will improve how we assess and disseminate emerging data leading to efficient, evidence-based implementation (or deimplementation) of treatment.