This individual's Blood Pressure (Diastolic - Bottom Number) is generally highest after a daily total of 150 milligrams of Cosentyx intake over the previous 33 days.
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Blue represents the sum of Cosentyx intake over the previous 33 days
An increase in 33 days cumulative Cosentyx intake is usually followed by an decrease in Blood Pressure (Diastolic - Bottom Number). (R = -0.191)
Typical values for Blood Pressure (Diastolic - Bottom Number) following a given amount of Cosentyx intake over the previous 33 days.
Typical Cosentyx intake seen over the previous 33 days preceding the given Blood Pressure (Diastolic - Bottom Number) value.
Correlation between outcome and aggregated predictor measurements over given number of days
Peak correlation suggests the delay between predictor and observable outcome
This chart shows how your Cosentyx changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Cosentyx on each day of the week.
This chart shows the typical value recorded for Cosentyx for each month of the year.
This chart shows how your Blood Pressure changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Blood Pressure on each day of the week.
This chart shows the typical value recorded for Blood Pressure for each month of the year.

Abstract

This individual's Blood Pressure (Diastolic - Bottom Number) is generally 1% higher than normal after a total of 150 milligrams Cosentyx intake over the previous 33 days. This individual's data suggests with a medium degree of confidence (p=0.18219451884083, 95% CI -1.574 to 1.192) that Cosentyx has a weakly negative predictive relationship (R=-0.19) with Blood Pressure (Diastolic - Bottom Number). The highest quartile of Blood Pressure (Diastolic - Bottom Number) measurements were observed following an average 274.24 milligrams Cosentyx per day. The lowest quartile of Blood Pressure (Diastolic - Bottom Number) measurements were observed following an average 376.19047619048 mg Cosentyx per day.Blood Pressure (Diastolic - Bottom Number) is generally 1% lower than normal after a total of 376.19047619048 milligrams of Cosentyx intake over the previous 33 days. Blood Pressure (Diastolic - Bottom Number) is generally 1% higher after a total of 274.24 milligrams of Cosentyx intake over the previous 33 days.

Objective

The objective of this study is to determine the nature of the relationship (if any) between Cosentyx and Blood Pressure. Additionally, we attempt to determine the Cosentyx values most likely to produce optimal Blood Pressure values.

Participant Instructions

Record your Cosentyx daily in the reminder inbox or using the interactive web or mobile notifications.
Get Withings here and use it to record your Blood Pressure. Once you have a Withings account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.

Design

This study is based on data donated by one participant. Thus, the study design is consistent with an n=1 observational natural experiment.

Data Analysis

Cosentyx Pre-Processing
Cosentyx measurement values below 0 milligrams were assumed erroneous and removed. No maximum allowed measurement value was defined for Cosentyx. It was assumed that any gaps in Cosentyx data were unrecorded 0 milligrams measurement values.
Cosentyx Analysis Settings

Blood Pressure Pre-Processing
Blood Pressure measurement values below 0 millimeters merc were assumed erroneous and removed. No maximum allowed measurement value was defined for Blood Pressure. No missing data filling value was defined for Blood Pressure so any gaps in data were just not analyzed instead of assuming zero values for those times.
Blood Pressure Analysis Settings

Predictive Analytics
It was assumed that 168 hours would pass before a change in Cosentyx would produce an observable change in Blood Pressure (Diastolic - Bottom Number). It was assumed that Cosentyx could produce an observable change in Blood Pressure (Diastolic - Bottom Number) for as much as 33.33 days after the stimulus event.
Predictive Analysis Settings

Data Quantity
30 raw Cosentyx measurements with 50 changes spanning 1205 days from 2015-12-03 to 2019-03-22 were used in this analysis. 1521 raw Blood Pressure (Diastolic - Bottom Number) measurements with 347 changes spanning 2255 days from 2013-03-05 to 2019-05-08 were used in this analysis.

Data Sources

Cosentyx data was primarily collected using QuantiModo. QuantiModo allows you to easily track mood, symptoms, or any outcome you want to optimize in a fraction of a second. You can also import your data from over 30 other apps and devices. QuantiModo then analyzes your data to identify which hidden factors are most likely to be influencing your mood or symptoms.

Blood Pressure (Diastolic - Bottom Number) data was primarily collected using Withings. Withings creates smart products and apps to take care of yourself and your loved ones in a new and easy way. Discover the Withings Pulse, Wi-Fi Body Scale, and Blood Pressure Monitor.

Limitations

As with any human experiment, it was impossible to control for all potentially confounding variables. Correlation does not necessarily imply causation. We can never know for sure if one factor is definitely the cause of an outcome. However, lack of correlation definitely implies the lack of a causal relationship. Hence, we can with great confidence rule out non-existent relationships. For instance, if we discover no relationship between mood and an antidepressant this information is just as or even more valuable than the discovery that there is a relationship.
We can also take advantage of several characteristics of time series data from many subjects to infer the likelihood of a causal relationship if we do find a correlational relationship. The criteria for causation are a group of minimal conditions necessary to provide adequate evidence of a causal relationship between an incidence and a possible consequence.

The list of the criteria is as follows:
Strength (A.K.A. Effect Size)
A small association does not mean that there is not a causal effect, though the larger the association, the more likely that it is causal. There is a weakly negative relationship between Cosentyx intake and Blood Pressure (Diastolic - Bottom Number)

Consistency (A.K.A. Reproducibility)
Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect. Furthermore, in accordance with the law of large numbers (LLN), the predictive power and accuracy of these results will continually grow over time. 129 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Cosentyx intake values, the observed strength of the relationship will decline until it is below the threshold of significance. To it another way, in the case that we do find a spurious correlation, suggesting that banana intake improves mood for instance, one will likely increase their banana intake. Due to the fact that this correlation is spurious, it is unlikely that you will see a continued and persistent corresponding increase in mood. So over time, the spurious correlation will naturally dissipate.

Specificity
Causation is likely if a very specific population at a specific site and disease with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship.

Temporality
The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay). The confidence in a causal relationship is bolstered by the fact that time-precedence was taken into account in all calculations.

Biological Gradient
Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.

Plausibility
A plausible bio-chemical mechanism between cause and effect is critical. This is where human brains excel. Based on our responses so far, 1 humans feel that there is a plausible mechanism of action and 0 feel that any relationship observed between Cosentyx intake and Blood Pressure (Diastolic - Bottom Number) is coincidental.

Coherence
Coherence between epidemiological and laboratory findings increases the likelihood of an effect. It will be very enlightening to aggregate this data with the data from other participants with similar genetic, diseasomic, environmentomic, and demographic profiles.

Experiment
All of human life can be considered a natural experiment. Occasionally, it is possible to appeal to experimental evidence.

Analogy
The effect of similar factors may be considered.

Relationship Statistics

Property Value
Cause Variable Name Cosentyx intake
Effect Variable Name Blood Pressure (Diastolic - Bottom Number)
Sinn Predictive Coefficient 0.069
Confidence Level medium
Confidence Interval 1.3828117246656
Forward Pearson Correlation Coefficient -0.191
Critical T Value 1.646
Total Cosentyx intake Over Previous 33 days Before ABOVE Average Blood Pressure ( Diastolic - Bottom Number) 274.24 milligrams
Total Cosentyx intake Over Previous 33 days Before BELOW Average Blood Pressure ( Diastolic - Bottom Number) 376.19 milligrams
Duration of Action 33 days
Effect Size weakly negative
Number of Paired Measurements 129
Optimal Pearson Product 0.068131005737964
P Value 0.18219451884083
Statistical Significance 0.3614
Strength of Relationship 1.3828117246656
Study Type individual
Analysis Performed At 2019-06-15

Cosentyx Statistics

Property Value
Variable Name Cosentyx
Aggregation Method SUM
Analysis Performed At 2019-06-26
Duration of Action 33 days
Kurtosis 132.27831578308
Mean 4.8617 milligrams
Median 0 milligrams
Minimum Allowed Value 0 milligrams
Number of Changes 50
Number of Correlations 96
Number of Measurements 30
Onset Delay 7 days
Standard Deviation 38.49010219756
Unit Milligrams
Variable ID 5538381
Variance 1481.4879671786

Blood Pressure Statistics

Property Value
Variable Name Blood Pressure (Diastolic - Bottom Number)
Aggregation Method MEAN
Analysis Performed At 2019-05-09
Duration of Action 7 days
Kurtosis 3.0902415726782
Mean 79.585 millimeters merc
Median 79.5 millimeters merc
Minimum Allowed Value 0 millimeters merc
Number of Changes 347
Number of Correlations 2630
Number of Measurements 1521
Onset Delay 0 seconds
Standard Deviation 6.3392479360027
Unit Millimeters Merc
Variable ID 5554981
Variance 40.186064394114

Tracking Cosentyx

Record your Cosentyx daily in the reminder inbox or using the interactive web or mobile notifications.

Tracking Blood Pressure

Get Withings here and use it to record your Blood Pressure. Once you have a Withings account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.
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https://lh6.googleusercontent.com/-BHr4hyUWqZU/AAAAAAAAAAI/AAAAAAAIG28/2Lv0en738II/photo.jpg Principal Investigator - Mike Sinn