Assessing Importance of Dietary Data in Anticoagulation Treatment - - PowerPoint PPT Presentation

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Assessing Importance of Dietary Data in Anticoagulation Treatment - - PowerPoint PPT Presentation

Dec 15, 2023 12 likes •214 views

Assessing Importance of Dietary Data in Anticoagulation Treatment Peter Brnnum Nielsen M.Sc. BME, PhD fellow Department of Health Science and Tech. Aalborg University Introduction Oral Anticoagulation Methods and data Modelling

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SLIDE 1

Assessing Importance of Dietary Data in Anticoagulation Treatment

Peter Brønnum Nielsen M.Sc. BME, PhD fellow Department of Health Science and Tech. Aalborg University

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SLIDE 2

Oral Anticoagulation Treatment (OAT)

  • People with increased risk of thrombosis
  • Mechanical heart valve replacement
  • Deep Venous Thrombosis (DVT)
  • Atrial fibrillation
  • Pulmonary embolism
  • Current patient figures
  • DK 100.000 patients1 (2% of population)
  • Expected to rise
  • Introduction
  • Methods and data
  • Modelling
  • Results

1. Holm T, Lassen JF., Ugeskr Laeger, 2003

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SLIDE 3

Treatment management

  • Introduction
  • Methods and data
  • Modelling
  • Results
  • Management of daily oral intake of

vitamin K antagonists (warfarin)

  • Monitoring of INR - International Normalized Ratio
  • Beneficial balance between clotting and

tendency to bleed

  • Affected by dietary vitamin K

2

  • Slow-acting physiological system

2. Stafford, DW., J Thromb Haemost, 2005

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SLIDE 4

Patient management

  • Introduction
  • Methods and data
  • Modelling
  • Results
  • Conventional treatment
  • Physician managed
  • Partly managed by patient
  • Patient self-testing
  • Patient self-management

INR Vitamin K Warfarin

  • Patients have to

comprehend:

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SLIDE 5

Self-management and self-testing of OAT

  • Introduction
  • Methods and data
  • Modelling
  • Results
  • Benefits
  • Cost-effectiveness
  • Clinical effectiveness
  • Reduce frequency of ambulatory visits
  • Increase quality of life for OAT patients
  • Risks
  • Potential lethal drug
  • Biological variability affecting INR
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SLIDE 6
  • Medication errors

can cause death

Summary of challenges

  • Introduction
  • Methods and data
  • Modelling
  • Results

Utilizing vitamin K information when prediction INR values

  • INR values are

affected by biological variability as dietary vitamin K

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SLIDE 7
  • Introduction
  • Methods and data
  • Modelling
  • Results

Methods

  • Metabolic modelling
  • Collection of data from five patients in

“normal, everyday setting”

  • Data parameters:
  • INR
  • Warfarin
  • Vitamin K
  • Others
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SLIDE 8
  • Introduction
  • Methods and data
  • Modelling
  • Results

Data collection protocol

  • Cooperation with highly specialized

ambulatory (Medicinsk Ambulatorium, Brædstrup Sygehus)

  • Daily scheme to be filled for one month
  • Mail correspondence once a week
  • No. of days

INR TTR Warfarin Mean 27,2 2,5 83,7% 2,5mg Indications for OAT: Heart valve replacement, DVT, or atria fibrillation. Abbreviations: TTR = Time in Therapeutic Range.

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SLIDE 9
  • Introduction
  • Methods and data
  • Modelling
  • Results

Modelling

  • Already existing model

3 expanded

  • Break down into

compartments

  • Warfarin
  • Coagulation factors
  • Vitamin K
  • Predict future INR

values

3. Vadher B., J Clin Pathol, 1999

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SLIDE 10
  • Introduction
  • Methods and data
  • Modelling
  • Results

Warfarin modelling

  • Warfarin modelled as single compartment
  • Effect of warfarin on coagulation factors
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SLIDE 11
  • Introduction
  • Methods and data
  • Modelling
  • Results

Coagulation factors

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SLIDE 12
  • Introduction
  • Methods and data
  • Modelling
  • Results

Vitamin K modelling

  • Modelled effect

4

  • f vitamin K

intake upon INR values

4. Schugers LG., Blood, 2004

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SLIDE 13
  • Introduction
  • Methods and data
  • Modelling
  • Results

Model summary

Mathematical overview of model

  • 1. INR(t) = 1+(∑[ai((100-Fi)/100)Si] – VitK)
  • 2. dFi/dt = w ● Fsyn - Fdeg
  • 3. w = 1 – tanh(W(t) ● warf-sens)
  • 4. W(t) = W(0) ● e-(k) ● t
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SLIDE 14

Model predictions

  • Introduction
  • Methods and data
  • Modelling
  • Results
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SLIDE 15

Model prediction results

  • Introduction
  • Methods and data
  • Modelling
  • Results
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SLIDE 16

Model prediction results

  • Introduction
  • Methods and data
  • Modelling
  • Results
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SLIDE 17

Model prediction results

  • Introduction
  • Methods and data
  • Modelling
  • Results
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SLIDE 18
  • Introduction
  • Methods and data
  • Modelling
  • Results

Results for vitamin K rich data

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SLIDE 19
  • Introduction
  • Methods and data
  • Modelling
  • Results

Discussion

  • Pros
  • Decision support for management of OAT patients
  • Help to avoid oscillating INR values
  • Opportunity to raise patient’s awareness
  • Cons
  • Burden of data collection
  • False or incomplete data pose a potential risk
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SLIDE 20

Thank you for listening

Peter Brønnum Nielsen M.Sc. BME, PhD fellow Department of Health Science and Tech. Aalborg University E-mail: pbn@hst.aau.dk