Abstract

Background Standard care in severe SARS-CoV-2 pneumonia complicated by severe dyspnea and respiratory failure, consists of symptom reduction, ultimately supported by mechanical ventilation. Patients with severe SARS-CoV-2, a prominent feature of COVID-19, show several similar symptoms to Critical Asthma Syndrome (CAS) patients, such as pulmonary edema, mucus plugging of distal airways, decreased tissue oxygenation, (emergent) exhaustion due to severe dyspnea and respiratory failure. Prior application of elective phosphodiesterase (PDE)3-inhibitors milrinone and enoximone in patients with CAS yielded rapid symptomatic relief and reverted the need for mechanical ventilation, due to their bronchodilator and anti-inflammatory properties. Based on these observations, we hypothesized that enoximone may be beneficial in the treatment of patients with severe SARS-CoV-2 pneumonia and prominent CAS-features. Methods In this case report enoximone was administered to four consecutive patients (1 M; 3 F; 46–70 y) with emergent respiratory failure due to SARS-CoV-2 pneumonia. Clinical outcome was compared with three controls who received standard care only. Results After an intravenous bolus of enoximone 20 mg followed by 10 mg/h via perfusor, a rapid symptomatic relief was observed: two out of four patients recovered within a few hours, the other two (with comorbid COPD GOLD II/III) responded within 24–36 h. Compared to the controls, in the enoximone-treated patients respiratory failure and further COVID-19-related deterioration was reverted and mechanical ventilation was prevented, leading to reduced hospital/ICU time. Discussion Our preliminary observations suggest that early intervention with the selective PDE3-inhibitor enoximone may help to revert respiratory failure as well as avert mechanical ventilation, and reduces ICU/hospital time in patients with severe SARS-CoV-2 pneumonia. Our findings warrant further research on the therapeutic potential of PDE3-inhibition, alone or in combination with other anti-COVID-19 strategies.

Highlights

  • Every day, doctors, hospitals, pharmaceutical companies, and others in healthcare face the complexities of the human body and the healthcare environment

  • That is, what E-Synthesis can provide for a better working of Artificial Intelligence (AI) and how AI itself can improve E-Synthesis

  • The methodological choice of a Bayesian network lends itself to further applications in AI, since Bayesian network algorithms are designed to be implemented within AI systems

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Summary

Introduction

Doctors, hospitals, pharmaceutical companies, and others in healthcare face the complexities of the human body and the healthcare environment. Given the challenge of interpreting such varieties of data, it is clear that AI has an important role to play in healthcare. It has already had a major impact. An AI system powered by Google LLC predicted hospital inpatient death risks with 95% accuracy.[1] In January 2020, the first AI-developed drug, DSP-1181 (a treatment for obsessive compulsive disorder) entered clinical trials.† AI can make a contribution to diagnostic procedures by doctors[2]

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