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A Data-Driven Approach At Characterizing Heterogeneity In Neuropathy Assessments

Luke Johnston

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PURPOSE:

Get feedback, comments on two issues:

  • Analysis implementation

  • Extracting key results

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BACKGROUND

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Diabetic neuropathy: Major complication without strong definition

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Diabetic neuropathy: Major complication without strong definition

  • Many assessments:
    • DN4, UENS, TCSS, mTCSS, Monofilament-based, MNSI, Heart rate variability, Sural nerve conduction
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Diabetic neuropathy: Major complication without strong definition

  • Many assessments:
    • DN4, UENS, TCSS, mTCSS, Monofilament-based, MNSI, Heart rate variability, Sural nerve conduction
  • No consensus on assessing neuropathy
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Study objectives

  • Are there specific groups of people who share similar assessment responses?
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Study objectives

  • Are there specific groups of people who share similar assessment responses?

  • Are some assessment tools better at capturing features of neuropathy?

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Study objectives

  • Are there specific groups of people who share similar assessment responses?

  • Are some assessment tools better at capturing features of neuropathy?

  • Based on above, could we simplify what assessment items to give and use the responses?

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Study and measurements

  • Cohort: ~13 year followup of ADDITION-DK (n=526)

  • Measures: 8 different neuropathy assessment tools (105 total items)

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Rationale on statistical analysis

ID A1 A2 A3 A4 A5 A6
1 absent present present present present absent
2 absent absent absent absent present present
3 absent present absent absent present present
4 present absent present absent absent absent
5 absent present present absent absent absent
6 absent absent absent absent absent present
7 present present absent present present present
8 absent absent present present absent absent
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Groups by row: Hierarchical cluster (HCA)

ID A1 A2 A3 A4 A5 A6
1 absent present present present present absent
2 absent absent absent absent present present
3 absent present absent absent present present
4 present absent present absent absent absent
5 absent present present absent absent absent
6 absent absent absent absent absent present
7 present present absent present present present
8 absent absent present present absent absent
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"Groups" by variable: Factor analysis

ID A1 A2 A3 A4 A5 A6
1 absent present present present present absent
2 absent absent absent absent present present
3 absent present absent absent present present
4 present absent present absent absent absent
5 absent present present absent absent absent
6 absent absent absent absent absent present
7 present present absent present present present
8 absent absent present present absent absent
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FIRST ISSUE:

Both methods data-specific, with fixed groups.

What is likelihood individual will be in group?

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My idea for implementation:

Run methods on resampled sets (4-fold CV, x 25)

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ID A1 A2 A3 A4 A5 A6
1 absent present present present present absent
3 absent present absent absent present present
6 absent absent absent absent absent present
7 present present absent present present present
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ID A1 A2 A3 A4 A5 A6
1 absent present present present present absent
3 absent present absent absent present present
6 absent absent absent absent absent present
7 present present absent present present present

 

ID A1 A2 A3 A4 A5 A6
2 absent absent absent absent present present
5 absent present present absent absent absent
7 present present absent present present present
8 absent absent present present absent absent
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HCA results: Likelihood of group membership

Focusing on HCA for time.

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SECOND ISSUE:

What are common responses by group?

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This is 50 rows of what results look like:

ClusterNumber Questionnaire AssessmentResponse MeanPercent
Cluster: 1 MNSI Ankle reflex: Present with reinforcement 0.8977778
Cluster: 1 TCSS Ankle reflex: Decreased(present by reinforcement) 0.8977778
Cluster: 1 HRV E:i (expiration inspiration): High 0.8107937
Cluster: 1 mTCSS Tingling?: No 0.7972152
Cluster: 1 UENS Neurotip section 1: Normal 0.7894309
Cluster: 1 MNSI Do you ever have any burning pain in your legs and/or feet?: No 0.7872358
Cluster: 1 TCSS Ataxia?: No 0.7855172
Cluster: 1 MNSI Do your legs hurt when you walk?: No 0.7803376
Cluster: 1 MNSI Ulceration foot?: Absent 0.7726740
Cluster: 1 MNSI Ulceration foot?: Absent 0.7726740
Cluster: 1 mTCSS Position sensation: Normal 0.7721547
Cluster: 1 UENS Neurotip section 4: Decreased 0.7600000
Cluster: 1 UENS Neurotip section 2: Decreased 0.7569231
Cluster: 1 TCSS Temperature for foot: Abnormal 0.7544304
Cluster: 1 TCSS Upper limb symptoms?: Yes 0.7446667
Cluster: 1 DPN Amplitude: Low-mid 0.7406803
Cluster: 1 DN4 Pain in area may reveal hypoesthesia to touch?: No 0.6948315
Cluster: 1 UENS Vibration on great toe: Decreased 0.6471795
Cluster: 1 MNSI Have you ever had an open sore on your foot?: Yes 0.4088889
Cluster: 1 DN4 Do you suffer from pain in your feet?: Yes 0.2711111
Cluster: 1 DN4 Pain feels like painful cold?: No 0.2320000
Cluster: 2 mTCSS Foot pain?: Yes 0.5133333
Cluster: 2 DN4 Pain feels like electric shocks?: Yes 0.5093333
Cluster: 2 TCSS Knee reflex: Decreased(present by reinforcement) 0.4174359
Cluster: 2 TCSS Ataxia?: Yes 0.4150000
Cluster: 2 MNSI Do you ever have any burning pain in your legs and/or feet?: Yes 0.3059259
Cluster: 2 DN4 Pain caused or increased by brushing?: No 0.2794203
Cluster: 2 DPN Velocity: Low-mid 0.2385185
Cluster: 2 MNSI Do your legs hurt when you walk?: Yes 0.2350000
Cluster: 2 Monofilament Light touch under foot, point 4: Abnormal(≤1/3) 0.2112821
Cluster: 2 Monofilament Light touch under foot, point 1: Normal(≥ 2/3) 0.2088623
Cluster: 2 MNSI Monofilament great toe: Normal(8-10) 0.2086842
Cluster: 2 UENS Neurotip section 5: Normal 0.2084291
Cluster: 2 MNSI Do you ever have any burning pain in your legs and/or feet?: No 0.2000000
Cluster: 2 UENS Extension great toe: Normal 0.1996101
Cluster: 2 UENS Neurotip section 3: Decreased 0.1966667
Cluster: 2 UENS Neurotip section 1: Absent 0.0333333
Cluster: 3 MNSI Has your doctor ever told you that you have diabetic neuropathy?: Yes 0.2966667
Cluster: 3 Monofilament Light touch under foot, point 1: Abnormal(≤1/3) 0.2555556
Cluster: 3 DN4 Pain feels like electric shocks?: No 0.1720000
Cluster: 3 Monofilament Light touch under foot, point 3: Abnormal(≤1/3) 0.1293333
Cluster: 3 HRV Root mean square of successive differences for hr: Mid-high 0.0720000
Cluster: 3 mTCSS Upper limb symptoms?: No 0.0525490
Cluster: 3 HRV High frequency (?): Low 0.0512000
Cluster: 3 TCSS Ataxia?: No 0.0482270
Cluster: 3 TCSS Ankle reflex: Normal 0.0477778
Cluster: 3 UENS Extension great toe: Normal 0.0475789
Cluster: 3 Monofilament Light touch under foot, point 1: Normal(≥ 2/3) 0.0400000
Cluster: 3 MNSI Vibration perception at great toe: Decreased 0.0346667
Cluster: 3 mTCSS Tingling?: No 0.0315447
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How to make sense of this data?

How to extract meaning?

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PURPOSE:

Get feedback, comments on two issues:

  • Analysis implementation

  • Extracting key results

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