Ομιλία – Παρουσίαση:“Artificial intelligence and personalised medicine for patients at high risk of severe COVID-19” Γρηγόριος Γεροτζιάφας, Καθηγητής Αιματολογίας, Ιατρική σχολή της Σορβόνης, Υπεύθυνος, Τμήμα Θρόμβωσης, Νοσοκομείο Tenon, Παρίσι & Διευθυντής, Ερευνητική Ομάδα Καρκίνος και Θρόμβωση INSERM U938

1. Artificial intelligence and
personalised medicine for
patients at high risk of severe
COVID-19
Grigoris T. Gerotziafas
Directeur de Recherche Cancer-Hémostasis-Angiogenesis
CRSA, INSERM UMRS-938
Hémostase-Thrombose en Hématologie
Hôpital Saint Antoine-Tenon
Sorbonne Université

2. COVID-19
actual health policies

3. Artificial intelligence and control of COVID-19
Artificial intelligence (AI) is being used as a tool to support the fight against the viral
pandemic that has affected the entire world since the beginning of 2020. The press
and the scientific community are echoing the high hopes that data science and AI can
be used to confront the coronavirus and "fill in the blanks" still left by science
Artificial Intelligence (AI) has greatly facilitated exchanges of views and information
between the scientific community. What we have not seen so much is the use of AI for
inter-governmental cooperation on all these issues

4. Overview of Covid-19 Apps
https://www.coe.int/en/web/artificial-intelligence/ai-covid19

5. Studies on “COVID-19 and artificial intelligence”
sited in PubMed
0
50
100
150
200
250
300
350
400
Number
of
citations
(2020-2021)

6. COVID-19
Clinical classification and definition
Critical illness: patients with acute
respiratory distress syndrome or sepsis with acute
organ dysfunction
Severe illness: patients have fever or
suspected respiratory infection, plus one of the
following:
I. respiratory rate > 30 breaths/min
II. severe respiratory distress
III. pulse oximeter oxygen saturation ≤93% on
room air
Non-severe illness: patients without
any of the above conditions
https://www.who.int/publications-detail/clinical-management-of-severe-acute-respiratory-infection-when-novel-coronavirus-(ncov)-infection-is-suspected. Last access Nov.
2020; Chen et al. Lancet 2020;395:507-13. ; Huang et al. Lancet 2020;395:497-506
5%
15
%
80
%
mortality
35% to 45% Early identification of
patients at high risk for
clinical deterioration is
challenging for
• An appropriate
management
• A positive clinical
outcome

7. Hematological findings
of COVID-19
Hypercoagulable states together with lymphopenia, mild
thrombocytopenia, and increased biomarkers of inflammation are
common alterations in patients with COVID-19 hospitalized either at the
conventional medical ward or at the ICU
Hypercoagulability is based on
I. the significant increase of D-dimer levels in the plasma
II. the evidence of DIC; notably prolonged prothrombin time (PT)
and/or aPTT, thrombocytopenia, and acquired AT deficiency
Terpos et al. Am J Hematol. 2020 Jul;95(7):834-847.
Gerotziafas et al Thromb Haemost September 2020 DOI: 10.1055/s-0040-1715798

8. COVID-19 definition
COVID-19 is a systemic, potentially severe and life-threatening disease,
triggered by the SARS-CoV-2 infection which involves
I. immune and inflammatory responses
II. endothelial cell dysfunction
III. complement activation
IV. hypercoagulable state
COVID-19 is an hematological - vascular disease
Gerotziafas et al Thromb Haemost September 2020 DOI: 10.1055/s-0040-1715798

9. Gerotziafas et al Thromb Haemost Volume 120 · December 2020
COVID-19 worsening process

10. Dying with COVID-19 and VTE?
Rate of autopsy documented VTE in autopsy study in 80 deceased
40% VTE
12% fatal PE + DVT
12% non fatal PE
15 males also showed thrombi in the prostatic venous plexus
10 out of 26 patients (38%) who
died at home had VTE
Edler et al. Int J Leg 2020 Jun 4;1-10. doi: 10.1007/s00414-020-02317
Calabrese et al Virchows Arch. 2020 Jul 9:1-14.
16%
16%
64%
4%
Home Retirement home
Hospital Other
Place of death
Vascular damage: two
microthrombi in lung
small vessels, capillary
inflammation

11. COVID-19: a syndemic
Comorbidities Severe COVID-19 Critical CODIV-19
Odds ratio for disease
worsening (95% CI)
Current smoking 4.2% - 6.1% 3.9% - 5% 0.71 (0.19-2.68)
Malignancy 1%-6% 1.5% - 10% 1.6 (0.81 - 3.18)
Diabetes 6% - 25% 14% - 60% 2.13 (2.68 - 5.1)
Chronic renal disease 7 % 19 % 2.92 (1.04 - 6.09)
Hypertention 7% - 39% 15% - 64% 3.34 (1.72 - 5.47)
CVD 1% - 10% 9% - 40% 5.19 (3.25 - 8.29)
Respiratory disease 1% - 8% 5% - 10% 5.15 (2.51 - 10.5)
Obesity 8 % 31 % 5.4 (2.77 - 10.67)
Gerotziafas et al. Thromb Haemost September 2020 DOI: 10.1055/s-0040-1715798

12. COMPASS-COVID-19 strategy for midterm management
Prevention – Detection – Anticipation
Targeted Vaccine and Tracing
of SARS-CoV-2 infection

13. Disease worsening process and VTE risk
in patients with COVID-19
Exposure to
SARS-CoV-2
VTE risk
Incubation period 2 – 14 d 1st week
Ambulatory
period
Disease worsening
Conventional ward
Cytokine storm
Hypercoagulability
Endothelial cell activation
Complement activation
ICU
Viral symptom phase Inflammatory phase
Gerotziafas et al Sang Thrombose Vaisseaux 2020;32(6)
Patients at high risk of disease worsening
are probably at higher VTE risk
Who is at risk of disease worsening?
VTE: venous thromboembolism

14. Prevention for citizens at risk of
severe COVID-19
https://www.euro.who.int/en/about-us/governance/regional-committee-for-europe/70th-session/multimedia/video-gallery-introducing-4-whoeurope-flagship-initiatives/in
flagship-initiatives-empowerment-through-digital-health
Sergio Pillon Italy

15. Prevention for citizens at risk of severe
COVID-19 if infected by SARS-CoV-2
Frontera A et al J Infect. 2020 Aug;81(2):255-259.
Borro et al. Int J Environ Res Public Health, 2020 Aug 2;17(15):5573.
The level of pollution is associated with COVID-19 severity and mortality
Local strategy according to the incidence of cardiovascular risk factors
https://www.kff.org/coronavirus-covid-19/issue-brief/how-many-adults-are-at-risk-of-serious-
illness-if-infected-with-coronavirus/
Ribas A, et al. Priority COVID-19 Cancer Discov. 2020.
Gerotziafas et al Clin Appl Thromb Hemost. 2020 Jan-Dec;

16. Prevention for citizens at risk of severe
COVID-19 if infected by SARS-CoV-2
Frontera A et al J Infect. 2020 Aug;81(2):255-259.
Borro et al. Int J Environ Res Public Health, 2020 Aug 2;17(15):5573.
The level of pollution is associated with COVID-19 severity and mortality
Local strategy according to the incidence of cardiovascular risk factors
https://www.kff.org/coronavirus-covid-19/issue-brief/how-many-adults-are-at-risk-of-serious-
illness-if-infected-with-coronavirus/
Ribas A, et al. Priority COVID-19 Cancer Discov. 2020.
Gerotziafas et al Clin Appl Thromb Hemost. 2020 Jan-Dec;

17. March 2020
COMPASS-COVID-19 project
Detection of patients at risk of disease worsening

18. COMPASS-COVID-19 study: DIC in patients with COVID-19
• Compensated DIC is an independent risk factor for disease worsening OR : 4.58 (95%CI: 2.09-10.07 )
• The accuracy of the compensated DIC-ISTH score to identify patients at high risk for disease worsening is low
Derivation cohort
(March 18 - April 5, 2020)
Validation cohort
(April 6 - April 21, 2020)
Conventional ward
patients (n=208)
ICU patients
(n=102)
p
Conventional ward
patients (n=89)
ICU patients
(n=31)
p
Compensated DIC 8.2% 28.4% <0.001 2.2% 3.2% 0.3
Overt DIC 0 6 % 0 0 -
Gerotziafas et al. Thromb Haemost 2020 Doi: 10.1055/s-0040- 1716544
DIC: Disseminated intravascular coagulaiton

19. Mortality according to time period on presentation
Decrease of 28 days mortality
after early initiation of
anticoagulant treatment
• apixaban 2.5 bid: OR 0.46,
p = 0.001,
• apixaban 5 mgx2 bid: OR 0.57,
p = 0.006),
• enoxaparin 4000 IU od: OR
0.49, p = 0.001

20. COMPASS-COVID-19 RAM
Predictors for risk of worsening disease Score
Obesity (BMI>30) 19
Male gender 10
Compensated DIC-ISTH score ≥5
9
Confirmed COVID-19 2
Thrombocytopenia (Platelet count < 100.000/μL) 1
Prothrombin time prolongation (> control+ 3 sec) 1
D-Dimers increase
(>500 for age <60 years ; >600 ng/ml for age 60-59 years ; >600 ng/ml for age 60 -
69 years ; >700 ng/ml for age 70 - 79 years ; >800 ng/ml for age 80 - 89 years ;
>900 ng/ml for age 90 - 99)
1
Antithrombin decrease
(<lower normal limit established by the laboratory)
1
Protein C decrease
(<lower normal limit established by the laboratory)
1
Total
Lymphocytes <109/L 8
Hemoglobin <11 g/dL 8
Total
≥ 18 : high risk
< 18 : low risk
COMPASS-COVID-19 risk assessment model for COVID-19
worsening
94% sensitivity, 58% specificity Online calculator: www.medupdate.eu
March 2020
Gerotziafas et al. Thromb Haemost Sept. 2020 DOI: 10.1055/s-0040-1715798

21. COMPASS-COVID-19 score
Qualitative characteristics
Expected versus observed probability in
worsening cases (circles) and non-worsening
cases (triangles).
ROC analysis of the model
(area under the curve = 0.77).

22. Simplified profile of patients with COVID-19 at high or low
risk for disease worsening according to the COMPASS-
COVID-19 risk assessment model
Patients with COVID-19 at high risk for disease worsening
(COMPASS-COVID-19 score≥18)
Obese (BMI > 30), any sex, any examined comorbidities
Non obese, male with one or more of: compensated DIC-ISTH ≥ 5, lymphopenia, anemia
Non obese female with all three of: compensated DIC-ISTH ≥ 5, lymphopenia and anemia
Patients with COVID-19 at low risk for disease worsening (COMPASS-COVID-19 score < 18)
Non obese male, compensated DIC-ISTH < 5, without lymphopenia, without anemia
Non obese female with none, one, or two of: compensated DIC-ISTH ≥ 5, lymphopenia, anemia

23. Principle of the Compass Covid-19score
1.Hypercoagulability, endothelial cell activation and thrombosis, together with the
cytokinestorm and the exaggerated inflammatory reaction are the major pathological processes
leading to coronavirus deseases (COVID-19) worsening.
Start
For the evaluation of the risk for disease worsening
www.medupdate.eu

24. The COMPASS-COVID19-ICU score for
the evaluation of the risk of intubation
and mortality in patients with severe
COVID-19.
A prospective observational study.

25. COMPASS-COVID19-ICU
Variables
ICU-COVID-19 patients
(n=118).
Demographic Data
Age (age in years) 62.0 (52.3, 70.0)
Sex (male) 82/118 (69%)
Body mass index 27.6 (25.6, 30.1)
Cardiovascular risk factors and disease
Obesity (BMI>30) 15/118 (13%)
Diabetes 37/118 (31%)
Hypertension 70/118 (59%)
Cardiovascular disease 26/118 (22%)
Stroke 74/118 (63%)
Obliterating arterial disease of the lower limbs 4/118 (3%)
Acute myocardial infraction 17/118 (14%)
Regular tobacco use 10/118 (8%)
Non-vascular comorbidities
Active cancer 4/118 (3%)
Chronic Renal Disease 9/118 (8%)
Dialysis in patients with chronic renal disease 6/118 (5%)
Acute renal failure 18/118 (15%)
Dialysis in patients with acute renal failure 8/118 (7%)
Chronic obstructive pulmonary disease 4/118 (3%)
Chronic respiratory insufficiency 9/118 (8%)
Sickle cell anemia 2/118 (2%)
Personal history of VTE 3/118 (3%)
Antithrombotic treatment before hospital admission
Anticoagulant treatment 5/118 (4%)
Antiplatelet treatment 26/118 (22%)
ICU related complication
Hemoptysis 3/118 (3%)
Choc 53/118 (45%)
EER Dialysis 23/118 (19%)
All Infections 47/118 (40%)
Outcome
Death 21/118 (18%)
Intubation 83/118 (70%)
Risk of intubation Risk of death

26. Timeline for the Detection of patients at
risk of disease worsening
Exposure to
SARS-CoV-2
VTE risk
Incubation period 2 – 14 d 1st week
Ambulatory
period
Disease worsening
Conventional ward
Cytokine storm
Hypercoagulability
Endothelial cell activation
Complement activation
ICU
Viral symptom phase Inflammatory phase
Gerotziafas et al Sang Thrombose Vaisseaux 2021
Established VTE risk
IMPROVE and COMPASS-COVID-19
scores and standard prophylactic
dose of High risk patients: LMWH
or DOAC
IMPROVE D-Di score
High risk patients: LMWH or DOAC
at standard prophylactic dose
Post-hospital discharge
LMWH
Unselected patients: standard prophylactic dose for
Vascular patients: intermediate dose of LMWH
COMPASS-
COVID19-ICU

27. Development of artificial intelligence-based methodology and e-Health tools can improve
1. the benefit of the mitigation policies by decreasing the financial and social costs of the severe non
pharmacological interventions
2. the identification of population groups which are at higher risk of COVID-19 infection and vulnerable to
develop severe COVID-19 or a worsening disease
3. The development and availability of validated risk assessment models which together with the clinical
experience gained by physicians allow the allows Anticipated and personalized therapeutic intervention to
patients at risk of disease worsening
Acquisition of a collective experience by the medical community, the citizens and the policy makers in the
management of the pandemic will allow the adaptation of the strategies according to local customs and cultural
characteristics of the populations.
Take home message:
Prevention-Detection-Anticipation