Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Strategy for Disease Diagnosis, Progression Prediction, Risk Group Stratification and Treatment – Case of COVID-19

Version 1 : Received: 24 March 2020 / Approved: 24 March 2020 / Online: 24 March 2020 (14:43:24 CET)

How to cite: Vihinen, M. Strategy for Disease Diagnosis, Progression Prediction, Risk Group Stratification and Treatment – Case of COVID-19. Preprints 2020, 2020030361 (doi: 10.20944/preprints202003.0361.v1). Vihinen, M. Strategy for Disease Diagnosis, Progression Prediction, Risk Group Stratification and Treatment – Case of COVID-19. Preprints 2020, 2020030361 (doi: 10.20944/preprints202003.0361.v1).

Abstract

A novel strategy is presented for reliable diagnosis and progression prediction of diseases with special attention to COVID-19 pandemy. A plan is presented for how the model can be implemented worldwide in healthcare and how novel treatments and targets can be detected. The idea is based on poikilosis, pervasive heterogeneity and variation at all levels, systems and mechanisms. Poikilosis in diseases can be taken account in pathogenicity model, which is based on distribution of three independent condition measures – extent, modulation and severity. Pathogenicity model is a population or cohort-based description of disease components. Evidence-based thresholds can be applied to the pathogenicity model and used for diagnosis as well as for early detection of patients in risk of developing the most severe forms of the disease. Analysis of patients with differential course of disease can help in detecting biomarkers of diagnostic and prognostic significance. A practical and feasible plan is presented how the concepts can be implemented in practice. Collaboration of many actors, including the World Health Organization and national health authorities, will be essential for success.

Subject Areas

COVID-19; SARS-CoV-2; pathogenicity model; diagnosis; progression prediction; poikilosis

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