Transcutaneous auricular vagus nerve stimulation effects on inflammatory markers and clinical evolution of patients with COVID-19: a pilot randomized clinical trial.

OBJECTIVE: To evaluate the effects of transcutaneous auricular vagus nerve stimulation (taVNS) on inflammatory markers and clinical outcomes in patients with COVID-19. METHODS: A randomized blinded pilot study was carried out with 21 individuals hospitalized with COVID-19 who received 14 sessions of active (a-taVNS) or sham taVNS (s-taVNS). The level of interleukin-6 (IL-6), interleukin-10 (IL-10), cortisol, and C-reactive protein (CRP) in plasma and clinical evolution pre- and post-intervention were evaluated. The memory and attention levels were evaluated 14 days after the end of the treatment. RESULTS: After treatment, significant intragroup differences were found in the CRP (p = 0.01), IL-6 (p = 0.01), and cortisol (p = 0.01) levels; however, in the comparison between the groups, only the CRP level was statistically lower for the a-taVNS (p = 0.04). The impression of improvement in memory and attention was greater in the a-taVNS than in the s-taVNS (p = 0.01, p = 0.04, respectively). There was no difference between the other clinical outcomes. CONCLUSIONS: taVNS is a viable and safe intervention in the acute care of patients with COVID-19, which can modulate their inflammatory profile and improve cognitive symptoms. However, improvements in overall clinical outcomes were not detected. Larger sample sizes and longer follow-ups are needed to confirm the anti-inflammatory and clinical effects of taVNS in patients with COVID-19. TRIALS REGISTRY: The Brazilian Registry of Clinical Trials (RBR-399t4g5).

Establishment of CORONET, COVID-19 Risk in Oncology Evaluation Tool, to Identify Patients With Cancer at Low Versus High Risk of Severe Complications of COVID-19 Disease On Presentation to Hospital.

PURPOSE: Patients with cancer are at increased risk of severe COVID-19 disease, but have heterogeneous presentations and outcomes. Decision-making tools for hospital admission, severity prediction, and increased monitoring for early intervention are critical. We sought to identify features of COVID-19 disease in patients with cancer predicting severe disease and build a decision support online tool, COVID-19 Risk in Oncology Evaluation Tool (CORONET). METHODS: Patients with active cancer (stage I-IV) and laboratory-confirmed COVID-19 disease presenting to hospitals worldwide were included. Discharge (within 24 hours), admission (≥ 24 hours inpatient), oxygen (O2) requirement, and death were combined in a 0-3 point severity scale. Association of features with outcomes were investigated using Lasso regression and Random Forest combined with Shapley Additive Explanations. The CORONET model was then examined in the entire cohort to build an online CORONET decision support tool. Admission and severe disease thresholds were established through pragmatically defined cost functions. Finally, the CORONET model was validated on an external cohort. RESULTS: The model development data set comprised 920 patients, with median age 70 (range 5-99) years, 56% males, 44% females, and 81% solid versus 19% hematologic cancers. In derivation, Random Forest demonstrated superior performance over Lasso with lower mean squared error (0.801 v 0.807) and was selected for development. During validation (n = 282 patients), the performance of CORONET varied depending on the country cohort. CORONET cutoffs for admission and mortality of 1.0 and 2.3 were established. The CORONET decision support tool recommended admission for 95% of patients eventually requiring oxygen and 97% of those who died (94% and 98% in validation, respectively). The specificity for mortality prediction was 92% and 83% in derivation and validation, respectively. Shapley Additive Explanations revealed that National Early Warning Score 2, C-reactive protein, and albumin were the most important features contributing to COVID-19 severity prediction in patients with cancer at time of hospital presentation. CONCLUSION: CORONET, a decision support tool validated in health care systems worldwide, can aid admission decisions and predict COVID-19 severity in patients with cancer.

Immune checkpoint inhibitor therapy and outcomes from SARS-CoV-2 infection in patients with cancer: a joint analysis of OnCovid and ESMO-CoCARE registries.

BACKGROUND: As management and prevention strategies against COVID-19 evolve, it is still uncertain whether prior exposure to immune checkpoint inhibitors (ICIs) affects COVID-19 severity in patients with cancer. METHODS: In a joint analysis of ICI recipients from OnCovid (NCT04393974) and European Society for Medical Oncology (ESMO) CoCARE registries, we assessed severity and mortality from SARS-CoV-2 in vaccinated and unvaccinated patients with cancer and explored whether prior immune-related adverse events (irAEs) influenced outcome from COVID-19. FINDINGS: The study population consisted of 240 patients diagnosed with COVID-19 between January 2020 and February 2022 exposed to ICI within 3 months prior to COVID-19 diagnosis, with a 30-day case fatality rate (CFR30) of 23.6% (95% CI 17.8 to 30.7%). Overall, 42 (17.5%) were fully vaccinated prior to COVID-19 and experienced decreased CFR30 (4.8% vs 28.1%, p=0.0009), hospitalization rate (27.5% vs 63.2%, p<0.0001), requirement of oxygen therapy (15.8% vs 41.5%, p=0.0030), COVID-19 complication rate (11.9% vs 34.6%, p=0.0040), with a reduced need for COVID-19-specific therapy (26.3% vs 57.9%, p=0.0004) compared with unvaccinated patients. Inverse probability of treatment weighting (IPTW)-fitted multivariable analysis, following a clustered-robust correction for the data source (OnCovid vs ESMO CoCARE), confirmed that vaccinated patients experienced a decreased risk of death at 30 days (adjusted OR, aOR 0.08, 95% CI 0.01 to 0.69).Overall, 38 patients (15.8%) experienced at least one irAE of any grade at any time prior to COVID-19, at a median time of 3.2 months (range 0.13-48.7) from COVID-19 diagnosis. IrAEs occurred independently of baseline characteristics except for primary tumor (p=0.0373) and were associated with a significantly decreased CFR30 (10.8% vs 26.0%, p=0.0462) additionally confirmed by the IPTW-fitted multivariable analysis (aOR 0.47, 95% CI 0.33 to 0.67). Patients who experienced irAEs also presented a higher median absolute lymphocyte count at COVID-19 (1.4 vs 0.8 109 cells/L, p=0.0098). CONCLUSION: Anti-SARS-CoV-2 vaccination reduces morbidity and mortality from COVID-19 in ICI recipients. History of irAEs might identify patients with pre-existing protection from COVID-19, warranting further investigation of adaptive immune determinants of protection from SARS-CoV-2.

An International Comparison of Presentation, Outcomes and CORONET Predictive Score Performance in Patients with Cancer Presenting with COVID-19 across Different Pandemic Waves.

Patients with cancer have been shown to have increased risk of COVID-19 severity. We previously built and validated the COVID-19 Risk in Oncology Evaluation Tool (CORONET) to predict the likely severity of COVID-19 in patients with active cancer who present to hospital. We assessed the differences in presentation and outcomes of patients with cancer and COVID-19, depending on the wave of the pandemic. We examined differences in features at presentation and outcomes in patients worldwide, depending on the waves of the pandemic: wave 1 D614G (n = 1430), wave 2 Alpha (n = 475), and wave 4 Omicron variant (n = 63, UK and Spain only). The performance of CORONET was evaluated on 258, 48, and 54 patients for each wave, respectively. We found that mortality rates were reduced in subsequent waves. The majority of patients were vaccinated in wave 4, and 94% were treated with steroids if they required oxygen. The stages of cancer and the median ages of patients significantly differed, but features associated with worse COVID-19 outcomes remained predictive and did not differ between waves. The CORONET tool performed well in all waves, with scores in an area under the curve (AUC) of >0.72. We concluded that patients with cancer who present to hospital with COVID-19 have similar features of severity, which remain discriminatory despite differences in variants and vaccination status. Survival improved following the first wave of the pandemic, which may be associated with vaccination and the increased steroid use in those patients requiring oxygen. The CORONET model demonstrated good performance, independent of the SARS-CoV-2 variants.

Barriers and facilitators for clinical trial participation of underrepresented and non-underrepresented fibromyalgia patients: A cross-sectional internet survey.

BACKGROUND: There is a need of well-powered randomized clinical trials in fibromyalgia. However, challenges for recruitment are presented. This study aims to describe and assess the perception of barriers and facilitators and the associated factors for the participation of underrepresented and non-underrepresented fibromyalgia patients. METHODS: We performed an online survey through REDCap (Research Electronic Data Capture) targeting fibromyalgia patients from April 7 to July 3, 2020 during the COVID-19 stay home mandate and it was restricted to the United States of America. We described and compared the survey characteristics between underrepresented and non-underrepresented participants, and we performed logistic regression models to assess the associated factors with clinical trial participation. RESULTS: In total, 481 completed the survey including 168 underrepresented fibromyalgia patients. Only (1) 11.09 % reported previous participation in clinical trials and the significant perceived barriers were investigator-related (lack of friendliness of research staff and the opportunity to receive the results) and center-related (privacy and confidentiality policies, and the institution's reputation); (2) the participation rate and perceived barriers and facilitators were similar between underrepresented and non-underrepresented patients; and was positively associated with low income, higher age, and clinical trial awareness from their physician; and negatively associated with the perception of investigator-related barriers; and (4) for the underrepresented population, the presence of emotional support. CONCLUSION: Our findings suggest low rates of participation, regardless of underrepresented population status. Strategies as involving their physician as liaison to increase the awareness of clinical trials, as well as improving patient-researcher communication should be considered in this population.