concussion projectdefenseversion2

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STOP WATCH TESTING An analysis into the use of a new testing technique to identify and treat concussions By Peter Eggleston Connor Data provided by Southern Oregon Orthopedics A Graduate Thesis from Southern Oregon University

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Page 1: Concussion projectdefenseversion2

STOP WATCH TESTINGAn analysis into the use of a new testing technique to identify and treat concussions

By Peter Eggleston ConnorData provided by

Southern Oregon OrthopedicsA Graduate Thesis from

Southern Oregon University

Page 2: Concussion projectdefenseversion2

TERMINOLOGY

Reaction TimeHealthy / Injured / Recovering

Days Since Injury (or: Recovery Time)

Symptom Score

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HISTORY

• Prior to 2001: Concussion detection had little empirical evidence supporting it.

• 2001-2012: American Academy of Neurology (AAN) creates guidelines for more globally accessing concussion risks in athletes.

• 2013: An update came out pointing towards evidence that having a concussion made future concussions more likely.

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OBJECTIVES

• Identify changes between healthy and injured reaction times

• Determine a concussion recovery rate based on reaction time

• Identify significant symptom scores over course of recovery

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DATA COLLECTION – HEALTHY AND INJURY FORM

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DATA COLLECTION – RECOVERING FORM

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DATA ORGANIZATION

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DESCRIPTIVE ANALYSIS

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DESCRIPTIVE ANALYSIS – RECOVERY TIME

n = 39

Mean:8.2 days

Standard Deviation:5.3 days

90th Percentile:~11 days

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DESCRIPTIVE ANALYSIS – HEALTHY REACTION TIME

Mean:0.18 sec

Standard Deviation:0.03 sec

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DESCRIPTIVE ANALYSIS – HEALTHY REACTION TIME IN CONCUSSED PLAYERSMean:

0.18 secStandard Deviation:

0.02 sec

Hypothesis Test All vs Concussed Healthy Reaction Timesp-value:

0.16Conclusions:

Accept Null

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DESCRIPTIVE ANALYSIS – INJURED REACTION TIME Mean:

0.27 secStandard Deviation:

0.10 sec

Hypothesis Test Healthy vs Injured Reaction Time in Concussed Athletes p-value:

~1Conclusion:

Reject Null

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DESCRIPTIVE ANALYSIS – REACTION TIME

DIFFERENCES

Mean:.088 sec

Standard Deviation:.098 sec

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DESCRIPTIVE ANALYSIS – REACTION TIME RATIOS

Mean:1.49

Standard Deviation:0.52

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COMPAREDAYS TO REACTION TIME

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EXPONENTIAL MODELING:DIFFERENCE 𝑦=(𝑐−h)𝑒𝛽𝑡+hy: The reaction time at t days since injury

c: The reaction time at the time of injury

h: The healthy reaction time

β: The rate of decay in the reaction time during recovery

t: The number of days since the concussion injury

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EXPONENTIAL MODELING

𝑦=(𝑐−h)𝑒𝛽𝑡+h

Purple:β = .01

Red:β = .2

Blue:β = 1

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EXPONENTIAL MODELING: DIFFERENCES

𝑦 𝑖=(𝑐 𝑖−h 𝑖¿𝑒−𝛽 𝑡+h𝑖

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EXPONENTIAL MODELING: DIFFERENCES

Where:i: Index for patient histories (1 to 39)ŷ: The predicted reaction time at t days since injury

Objective: Find the β that minimizes

∑𝑖

𝑛

∑𝑗

𝑚𝑖

( 𝑦 𝑖− ŷ𝑖 )2

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PREDICTIVE MODELUSINGDIFFERENCES

𝑦=(𝑐−h )𝑒−0.5441 𝑡+h

With β selected as 0.5441 is optimized at 0.62

Peter Eggleston Connor
Split into 2 slides"t=..." Should be its own slide
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PREDICTIVE MODEL USING DIFFERENCES

Can be transformed into: 𝑡 𝑦 ,𝑖=¿¿Where 𝑘=𝑦−h𝑖

Peter Eggleston Connor
Split into 2 slides"t=..." Should be its own slide
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PREDICTIVE MODEL USING DIFFERENCE BETWEEN HEALTHY AND INJURY

𝑡𝑦 ,𝑖=¿¿Optimal k:0.0014

Mean:6.97 Days

Standard Deviation:1.52 Days

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EXPONENTIAL MODELING: RATIO

𝑦 𝑖

h 𝑖=(

𝑐 𝑖

h𝑖−1)𝑒−𝛽 𝑡+1

Page 24: Concussion projectdefenseversion2

EXPONENTIAL MODELING: RATIO

Objective: Find the β that minimizes

∑𝑖

𝑛

∑𝑗

𝑚𝑖

( 𝑦 𝑖

h𝑖−^(𝑦 𝑖

h 𝑖))

2

Where: : Is the predicted ratio

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PREDICTIVE MODEL USING RATIOS

With β selected as 0.5696 is optimized at 0.43

𝑦 𝑖

h 𝑖=(

𝑐 𝑖

h𝑖−1)𝑒− 0.5696𝑡+1

Peter Eggleston Connor
Split into 2 slides"t=..." Should be its own slide
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PREDICTIVE MODEL USING RATIOS

To predict days until RTP:

Where𝑝=

𝑦 𝑖

h𝑖−1

Peter Eggleston Connor
Split into 2 slides"t=..." Should be its own slide
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PREDICTIVE MODEL USING RATIOS OF HEALTHY TO INJURY

Optimal p:0.008

Mean:6.97 Days

Standard Deviation:1.50 Days

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SYMPTOMS Blurry Vision Concentration Dizziness Fatigue Headache Heightened Feelings Light Sensitivity Loss of Balance Memory Loss Nausea Noise Sensitivity Sleeping Habits

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SYMPTOMS COMPARED TO DAYS SINCE INJURYHEADACHE EXAMPLE

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SYMPTOM LINEAR MODELING: SINGLE DESCRIPTIVE VARIABLE

Where:y: Represents the response variable, days since

injury x: Represents the predictor variable, a symptom: Is the value of y when x is zero: The amount y changes when x increases by 1

𝑦=𝑏0+𝑏1𝑥

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SYMPTOM LINEAR MODELING: MULTIPLE DESCRIPTIVE VARIABLES

Where:n: Is the number of predictor variables used in the

model: Is a predictor variable value, where are

symptoms: The amount y changes when increases by 1

𝑦=𝑏0+𝑏1𝑥1+𝑏2 𝑥2+...+𝑏𝑛𝑥𝑛

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SYMPTOMS COMPARED TO DAYS SINCE INJURY

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ANALYSIS OF VARIANCE(ANOVA)

• Identify Predictor Variables Independently in Multivariable Experiments

• Assess Explained and Residual Variation of Response Variable

• Determine Significance of Predictor Variables on Response Variable

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SYMPTOMS COMPARED TO DAYS SINCE INJURYANOVA

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SYMPTOMS COMPARED TO REACTION TIMEHEADACHE EXAMPLE

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SYMPTOMS COMPARED TO REACTION TIME

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SYMPTOMS COMPARED TO REACTION TIMEANOVA

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CONCLUSIONS:DETERMINING A CONCUSSION OFF OF STOP WATCH TESTINGThe reaction times taken after injury were significantly different from those of healthy times taken at the beginning of the season.

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CONCLUSIONS:RETURN TO PLAY

𝑡𝑦 ,𝑖=¿¿Best Calculator:

Roughly 97.5% of cases recover in 10 Days.

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CONCLUSIONS:CONCUSSION SYMPTOMS

Headache, dizziness, fatigue, heightened feelings, and feeling nauseas showed significance when looking at reaction time.

Headache showed significance when looking at days since injury.

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FURTHER RESEARCH

Unconscious Incidents

Multiple Concussions

Correlation Coefficients in Linear Analysis

Larger Data Set