Database description

Table of Contents

1. Origin of data
2. Data of 10 virtual patients
3. Why these choices?

In this section we describe a virtual patient database that has been generated using some synthetic data.

1. Origin of data

The data that are used to generate the database are derived from experimental values reported in literature.

We report the values and the sources we have adopted for our purpose in Table 1.

Table 1. Reference values for the virtual patients
Quantity	Symbol	Mean value	Std deviation	Unit	Source
Systolic blood pressure	SBP	116	23.2	mmHg	[Wright2011]
Diastolic blood pressure	DBP	69	13.8	mmHg	[Wright2011]
Heart rate	HR	69	15	beats per minute	[Bryan2010]
Intraocular pressure	IOP	17	6	mmHg	[Colton1980]
Retrolaminar tissue pressure	RLTp	9.5	2.2	mmHg	[Ren2010]

2. Data of 10 virtual patients

The actual data for 10 virtual patients are reported in Table 2.

Table 2. Virtual patients data
Name	Gender	Age	SBP	DBP	HR	IOP	RLTp	Note
Tony	M	65	116.0	69.0	69	17	9.5	Baseline
John	M	47	116.0	69.0	69	26	9.5	High IOP
Tina	F	81	116.0	69.0	69	26	12.8	High IOP, RLTp
Margaret	F	55	150.8	89.7	69	26	12.8	High IOP, RLTp, BP
Sophie	F	59	116.0	69.0	69	17	12.8	High RLTp
Luke	M	61	116.0	69.0	69	17	6.2	Low RLTp
Max	M	57	116.0	69.0	69	11	9.5	Low IOP
Clara	F	69	116.0	69.0	69	11	6.2	Low IOP, RLTp
Jim	M	72	150.8	89.7	69	11	9.5	Low IOP high BP
Jenny	F	85	116.0	69.0	100	17	9.5	High HR

3. Why these choices?

The table would like to span some cases that are interesting from an ophthalmological viewpoint.

In particular we have selected a baseline subject (Tony), three glaucoma risk patients that have high IOP (John, Tina, Margaret), one subject with Idiopathic Intracranial Hypertension risk (Sophie), one subject with high translaminar tissue pressure difference due to intracranial hypotension (Luke), three patients with ocular hypotony risk (Max, Clara, Jim) and finally one patient with tachycardia (Jenny).

The idea of this patient selection is to vary few parameters at time in order to understand the influences of each parameter variation and disentagle the different effects.

The variation of each parameter has been based on experimental results briefly resumed in Table 1, in particular to simulate high conditions we have selected the mean + standard deviation and for low values we chose mean - standard deviation with the exception of IOP and heart rate where the high values were pointed out directly from the literature [Colton1980][Bryan2010].

Undoubtedly this is just a preliminary analysis and it does not want to be exhaustive of any pathological situation, moreover we do not consider the fact that the parameters are not independent from each other.

Despite these assumptions, we highlight the fact that the Ocular Mathematical Virtual Simulator is still able to predict some clinically relevant conditions as certified by the interest risen by our work in various conferences and articles.

Bibliography

References

Wright, J. D., Hughes, J. P., Ostchega, Y., Yoon, S. S., & Nwankwo, T. Mean systolic and diastolic blood pressure in adults aged 18 and over in the United States, 2001–2008. Natl Health Stat Report, 35(1-22), 24. 2011.
Bryan, S., Larose, M. S. P., Campbell, N., Clarke, J., & Tremblay, M. S. Resting blood pressure and heart rate measurement in the Canadian Health Measures Survey, cycle 1. Health Reports, 21(1), 71. 2010.
Colton, T., & Ederer, F. The distribution of intraocular pressures in the general population. Survey of ophthalmology, 25(3), 123-129. 1980.
Ren, R., Jonas, J. B., Tian, G., Zhen, Y., Ma, K., Li, S., … & Wang, N. Cerebrospinal fluid pressure in glaucoma: a prospective study. Ophthalmology, 117(2), 259-266. 2010.