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Geetha.T Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 5, Issue 4, ( Part -4) April 2015, pp.19-22
www.ijera.com 19 | P a g e
Distributed Mathematical Model of Vasopressin in Patients with
Severe Brain Injury
Geetha.T* and Sharmiladevi.S**.
* Asst.Professor of Mathematics .K. N. Govt. Arts College for Women. Thanjavur. Tamilnadu. South India
**Lecturer of Mathematics, BDU College. Orathanadu. Thanjavur. Tamilnadu. South India
ABSTRACT
Disorders of water and sodium balance are frequently seen in patients with severe brain injury (SBI), and may
worsen their prognosis. AVP serum levels remained within the normal range in SBI patients (either traumatic or
non-traumatic), although tended to be greater in non-survivor than in survivor patients. AVP serum levels
remained within the normal range values in these SBI patients, but those who died have shown higher incidence
of abnormal sodium and water balance during the first week post-injury. We applied this to the steady-state
availability of systems with times to outages and recoveries that are generally distributed. Also we provide the
steady-state availability for a system subject to unplanned outages, for which times-to-outages are exponentially
distributed and planned outages for which times-to outages have bounded distributions to check the damage of
the hormonal levels.
Keywords: Vasopressin, SBI, TTP, Availability
I. NOTATIONS
A-Steady-state system availability
λ- Rate of failures (unplanned outages)
µ- Repair rate for unplanned outage
µ2-Upgrade rate for planned outage
TTP-Time to planned outage.
TTU-Time to planned upgrade.
II. MATHEMATICAL MODEL
For some electronic components, the hazard
function of TTF has a bathtub curve is a
monotonically decreasing function initially,
eventually becoming a constant, and finally changing
to a monotonically increasing function after sufficient
time elapses. In other words, an exponential
distribution (constant hazard function) holds only
during one particular phase of the component life.
For the planned outage, e.g., upgrading the hardware
or software of the computer systems, the time
between two consecutive upgrades is nearly
deterministic, and even the time used to upgrade the
system is nearly deterministic. Amenable to analytic
treatment and numerical computation, the
exponential assumption dominates academic research
and industrial practices for evaluating system
reliability and availability.
System with planned and unplanned outages
The system has 2 types of outages: planned and
unplanned.
Unplanned outages could be caused by
unanticipated system failures.
Planned outages can be system upgrades,
maintenance, configuration change, etc., that are
scheduled to enhance system functionalities. TTP and
TTU can follow general distributions. The objective
is to derive a general formula of A, and to obtain
availability bounds when TTP
Distributions are given with insufficient
information.
The state of the system which is in 1 of the 3
states:
• State 0: the system is working perfectly;
• State 1: the system is under repair following an
unplanned failure;
• State 2: the system is undergoing a scheduled
upgrade.
Theorem 1: The steady-state availability of a system
with unplanned and planned outages is:
A = [ 1+
𝜆
µ
+
𝜆
µ2
·
𝛼(𝜆)
1−𝛼(𝜆)
]-1
= [ 1+
𝜆
µ
+θ(λ) ·
𝜆
µ2
]-1
α(λ) ≡ exp −𝜆. 𝑥 𝑑𝐹(𝑥)
∞
0
θ(λ) ≡
𝛼(𝜆)
1−𝛼(𝜆)
µ-1
≡ MTTU = 𝑥𝑑𝐺(𝑥)
∞
0
.
Because λ is a positive real number, then α(λ)
can be interpreted as Pr( a planned outage occurs
when the system is in the working state) .The
complementary probability,1- α(λ) , is Pr( working
system has an unplanned outage ) [3, 5 ].
RESEARCH ARTICLE OPEN ACCESS
Geetha.T Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 5, Issue 4, ( Part -4) April 2015, pp.19-22
www.ijera.com 20 | P a g e
Then α (λ) has the properties:
1) If λ1> λ2>0, then α(λ1)< α(λ2): α(λ) is a
monotonically Decreasing function;
2) α(0) = 1, α(∞) = 0 ,0 ≤ α(λ) ≤ 1 .
It follows that θ(λ) is also a monotonically decreasing
function of λ.
Now, the Availability formula for the distribution of
TTP is deterministic
Let TTP = T,
AD(T) = [ 1+
𝜆
µ
+
𝜆
µ2
·
exp (−𝜆.𝑇)
1−exp ⁡(−𝜆.𝑇)
]-1
= [ 1+
𝜆
µ
+
𝜆
µ2
·
1
exp −𝜆.𝑇 −1
]-1
also,let TTP Є [ T1,T2 ](0< T1<T2);the pdf of TTP is
defined in such a way that f(x) =0,for x not in [ T1,T2
] and f x dx = 1
T2
T1
.
Let AB( T1 ,T2 ) be the system availability, with a
distribution of TTP bounded [6] in
[T1,T2 ]. Hence, the availability bound for the
deterministically distributed outages is,
AD(T1) ≤ AB(T1, T2) ≤ AD(T2), 0 ≤ T1 ≤ T2.
III. APPLICATION
Patients with severe brain injury (SBI), such as
traumatic brain injury (TBI), hemorrhagic stroke
(HS), ischemic stroke (IS) and subarachnoid
hemorrhage (SAH) frequently have abnormal
arginine-vasopressin (AVP) secretion. Various
investigations has measured AVP in plasma and in
cerebrospinal fluid (CSF) in patients with SBI and
reported high levels, suggesting that increased AVP
secretion may contribute to increase the primary
lesion severity. Other investigations have suggested
that AVP serum levels may affect the mechanisms of
cardiovascular regulation of cerebral edema. In a
previous study5, we compared AVP serum levels of
healthy individuals with those of patients with SBI or
brain death, and found a great variation in AVP
values in the group with SBI, but no significant
differences in mean plasma AVP levels between the
three groups. A negative correlation between plasma
osmolality and sodium was also found, suggesting
the presence of syndrome of inappropriate
antidiuretic hormone secretion (SIADH) in SBI
group. Disorders of the sodium/water balance,
particularly diabetes insipidus (DI) and SIADH, are
common complications reported in the acute phase of
SBI[1 ,2 ,7], either traumatic brain injury or stroke,
and contribute to the high morbidity and mortality
observed in these patients6,7. Moderate and
occasionally severe hyponatremia has been reported
in around 30% of neurosurgical patients with SAH.
The decrease in serum sodium was progressive,
leading to neurological problems, such as confusion,
lethargy, convulsions and, finally, coma.
Hyponatremia was first reported in 1950 in
patients with SBI. Excessive natriuresis was observed
and the term “cerebral salt-wasting syndrome” was
coined9. The hypothesis of the natriuretic factor was
not raised and, following the discovery of the
antidiuretic hormone, SIADH was mentioned as the
causal mechanism of hyponatremia in patients with
SBI. The pathophysiology of the secretion and
liberation of AVP and the mechanisms involved in
sodium and water disorders in patients with acute
severe brain lesion have not been adequately
clarified. In many studies increased levels of AVP
have been found and it has been suggested that this
increase, in the early stages of the injury, may be of
significant importance in the pathogenesis of cerebral
edema.
IV. METHODS
Severe brain injured group was composed of 36
patients, both sexes, aging ≥18 years, with initial
Glasgow Coma Scale (GCS) score ≤ 8, and an
estimated time of injury ≤ 72 hours, enrolled non-
consecutively. Exclusion criteria were: aging <18
years; associated major thoracic or abdominal
trauma; sepsis; irresponsive circulatory shock;
patients pregnant or lactating; previous history of
chronic corticosteroids, thyroid hormone or
desmopressin use, physical signs suggestive of brain
death or clinical death during the observation period.
Laboratory data of 29 healthy volunteers, previously
reported served as control.
In the SBI patients, 10 mL blood samples were
drawn on the 1st (D1), 2nd (D2), 3rd (D3) and 5th
day (D5) post-inclusion for measuring AVP and
serum osmolality, using a previously placed venous
catheter. A 3 ml arterial blood sample was also
collected for gas analysis, electrolytes, hemoglobin,
hematocrit, lactate and glucose, using a previously
placed arterial catheter. An isolated urinary sample at
D1 and 24 hour urinary samples at D2, D3 and D5
were used for sodium and osmolality measurements.
Blood samples (10 ml) for measurement of urea,
creatinine and for carrying out a leukocyte count
were collected only once (at D1). All samples were
sent to specific laboratories for immediate evaluation,
except the AVP sample. At the time of blood
sampling for AVP measurement, the following
clinical parameters were recorded: systemic blood
pressure (SBP), central venous pressure (CVP), heart
rate, urinary output and body temperature. During
data collection, the volumes and types of fluid
infused into the patients in the preceding 24 hours
were registered for calculating the quantity of sodium
that has been administered. Simultaneously, twenty-
four hour urine collection was carried out, stored at
4oC and sent for measurement of urinary sodium.
Sodium balance was then calculated at D2, D3 and
D5[4 ,8].
Geetha.T Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 5, Issue 4, ( Part -4) April 2015, pp.19-22
www.ijera.com 21 | P a g e
Fig 1. Vasopressin serum levels in survivors and non-survivors.
V. MATHEMATICAL RESULTS
VI. CONCLUTION
Plasma levels of AVP in healthy individuals at
rest are usually very low. There was a slight
variability of serum AVP levels in patients with SBI,
seen as isolated plasmatic peaks, but their mean
values always remained within the normal range, and
these levels tended to decrease over time, both in
survivors and non-survivors. Serum sodium and
plasma osmolality have shown great variations in
patients with SBI, and non-survivors have shown
greater and more significant deviations from normal
values than those who survived. We found that the
vasopressin levels of non survivors were increased.
REFERENCES
[1]. Boughey JC, Yost MJ, Bynoe RP. Diabetes
insipidus in the head-injured patient. Am
Surg 2004;70:500-503.
[2]. Cintra E de A, Maciel JA Jr, Araújo S, et al.
Vasopressin serum levels in patients with
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
1 2 3 4
vasopressin
Time
Non survivors
Survivors
Geetha.T Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 5, Issue 4, ( Part -4) April 2015, pp.19-22
www.ijera.com 22 | P a g e
severe brain lesions and in brain-dead
patients. Arq Neuropsiquiatr 2004;62:226-
232.
[3]. V. G. Kulkarni, Modeling and Analysis of
Stochastic Systems: Chapman& Hall, 1995.
[4]. Laszló FA, Varga C, Dóczi T. Cerebral
oedema after subarachnoid haemorrhage.
Pathogenetic significance of vasopressin.
Acta Neurchir (Wien)1995;133:122-133.
[5]. R. Marie and K. S. Trivedi, “A note on the
effect of pre emptive policies on the stability
of a priority queue,” Information
Processing Letters, vol.24, no. 6, pp. 397–
401, 1987.
[6]. M. Perman, A. Senegacnik, and M. Tuma,
“Semi-Markov models with an application to
power-plant reliability analysis,” IEEE
Trans. Reliability,vol. 46, pp. 526–532,
1997.
[7]. Tenedieva VD, Lyamin PV, Nepomnyaschi
VP. The plasma and CSF vasopressin levels
in brain tumors with brain edema. Acta
Neurochir (Wien) 1994;60(Suppl):S387-
S389.
[8]. Yuan XQ, Wade CE. Neuroendocrine
abnormalities in patients with traumatic
brain injury. Front Neuroendocrinol 1991;
12:209-230.

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Distributed Mathematical Model of Vasopressin in Patients with Severe Brain Injury

  • 1. Geetha.T Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 5, Issue 4, ( Part -4) April 2015, pp.19-22 www.ijera.com 19 | P a g e Distributed Mathematical Model of Vasopressin in Patients with Severe Brain Injury Geetha.T* and Sharmiladevi.S**. * Asst.Professor of Mathematics .K. N. Govt. Arts College for Women. Thanjavur. Tamilnadu. South India **Lecturer of Mathematics, BDU College. Orathanadu. Thanjavur. Tamilnadu. South India ABSTRACT Disorders of water and sodium balance are frequently seen in patients with severe brain injury (SBI), and may worsen their prognosis. AVP serum levels remained within the normal range in SBI patients (either traumatic or non-traumatic), although tended to be greater in non-survivor than in survivor patients. AVP serum levels remained within the normal range values in these SBI patients, but those who died have shown higher incidence of abnormal sodium and water balance during the first week post-injury. We applied this to the steady-state availability of systems with times to outages and recoveries that are generally distributed. Also we provide the steady-state availability for a system subject to unplanned outages, for which times-to-outages are exponentially distributed and planned outages for which times-to outages have bounded distributions to check the damage of the hormonal levels. Keywords: Vasopressin, SBI, TTP, Availability I. NOTATIONS A-Steady-state system availability λ- Rate of failures (unplanned outages) µ- Repair rate for unplanned outage µ2-Upgrade rate for planned outage TTP-Time to planned outage. TTU-Time to planned upgrade. II. MATHEMATICAL MODEL For some electronic components, the hazard function of TTF has a bathtub curve is a monotonically decreasing function initially, eventually becoming a constant, and finally changing to a monotonically increasing function after sufficient time elapses. In other words, an exponential distribution (constant hazard function) holds only during one particular phase of the component life. For the planned outage, e.g., upgrading the hardware or software of the computer systems, the time between two consecutive upgrades is nearly deterministic, and even the time used to upgrade the system is nearly deterministic. Amenable to analytic treatment and numerical computation, the exponential assumption dominates academic research and industrial practices for evaluating system reliability and availability. System with planned and unplanned outages The system has 2 types of outages: planned and unplanned. Unplanned outages could be caused by unanticipated system failures. Planned outages can be system upgrades, maintenance, configuration change, etc., that are scheduled to enhance system functionalities. TTP and TTU can follow general distributions. The objective is to derive a general formula of A, and to obtain availability bounds when TTP Distributions are given with insufficient information. The state of the system which is in 1 of the 3 states: • State 0: the system is working perfectly; • State 1: the system is under repair following an unplanned failure; • State 2: the system is undergoing a scheduled upgrade. Theorem 1: The steady-state availability of a system with unplanned and planned outages is: A = [ 1+ 𝜆 µ + 𝜆 µ2 · 𝛼(𝜆) 1−𝛼(𝜆) ]-1 = [ 1+ 𝜆 µ +θ(λ) · 𝜆 µ2 ]-1 α(λ) ≡ exp −𝜆. 𝑥 𝑑𝐹(𝑥) ∞ 0 θ(λ) ≡ 𝛼(𝜆) 1−𝛼(𝜆) µ-1 ≡ MTTU = 𝑥𝑑𝐺(𝑥) ∞ 0 . Because λ is a positive real number, then α(λ) can be interpreted as Pr( a planned outage occurs when the system is in the working state) .The complementary probability,1- α(λ) , is Pr( working system has an unplanned outage ) [3, 5 ]. RESEARCH ARTICLE OPEN ACCESS
  • 2. Geetha.T Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 5, Issue 4, ( Part -4) April 2015, pp.19-22 www.ijera.com 20 | P a g e Then α (λ) has the properties: 1) If λ1> λ2>0, then α(λ1)< α(λ2): α(λ) is a monotonically Decreasing function; 2) α(0) = 1, α(∞) = 0 ,0 ≤ α(λ) ≤ 1 . It follows that θ(λ) is also a monotonically decreasing function of λ. Now, the Availability formula for the distribution of TTP is deterministic Let TTP = T, AD(T) = [ 1+ 𝜆 µ + 𝜆 µ2 · exp (−𝜆.𝑇) 1−exp ⁡(−𝜆.𝑇) ]-1 = [ 1+ 𝜆 µ + 𝜆 µ2 · 1 exp −𝜆.𝑇 −1 ]-1 also,let TTP Є [ T1,T2 ](0< T1<T2);the pdf of TTP is defined in such a way that f(x) =0,for x not in [ T1,T2 ] and f x dx = 1 T2 T1 . Let AB( T1 ,T2 ) be the system availability, with a distribution of TTP bounded [6] in [T1,T2 ]. Hence, the availability bound for the deterministically distributed outages is, AD(T1) ≤ AB(T1, T2) ≤ AD(T2), 0 ≤ T1 ≤ T2. III. APPLICATION Patients with severe brain injury (SBI), such as traumatic brain injury (TBI), hemorrhagic stroke (HS), ischemic stroke (IS) and subarachnoid hemorrhage (SAH) frequently have abnormal arginine-vasopressin (AVP) secretion. Various investigations has measured AVP in plasma and in cerebrospinal fluid (CSF) in patients with SBI and reported high levels, suggesting that increased AVP secretion may contribute to increase the primary lesion severity. Other investigations have suggested that AVP serum levels may affect the mechanisms of cardiovascular regulation of cerebral edema. In a previous study5, we compared AVP serum levels of healthy individuals with those of patients with SBI or brain death, and found a great variation in AVP values in the group with SBI, but no significant differences in mean plasma AVP levels between the three groups. A negative correlation between plasma osmolality and sodium was also found, suggesting the presence of syndrome of inappropriate antidiuretic hormone secretion (SIADH) in SBI group. Disorders of the sodium/water balance, particularly diabetes insipidus (DI) and SIADH, are common complications reported in the acute phase of SBI[1 ,2 ,7], either traumatic brain injury or stroke, and contribute to the high morbidity and mortality observed in these patients6,7. Moderate and occasionally severe hyponatremia has been reported in around 30% of neurosurgical patients with SAH. The decrease in serum sodium was progressive, leading to neurological problems, such as confusion, lethargy, convulsions and, finally, coma. Hyponatremia was first reported in 1950 in patients with SBI. Excessive natriuresis was observed and the term “cerebral salt-wasting syndrome” was coined9. The hypothesis of the natriuretic factor was not raised and, following the discovery of the antidiuretic hormone, SIADH was mentioned as the causal mechanism of hyponatremia in patients with SBI. The pathophysiology of the secretion and liberation of AVP and the mechanisms involved in sodium and water disorders in patients with acute severe brain lesion have not been adequately clarified. In many studies increased levels of AVP have been found and it has been suggested that this increase, in the early stages of the injury, may be of significant importance in the pathogenesis of cerebral edema. IV. METHODS Severe brain injured group was composed of 36 patients, both sexes, aging ≥18 years, with initial Glasgow Coma Scale (GCS) score ≤ 8, and an estimated time of injury ≤ 72 hours, enrolled non- consecutively. Exclusion criteria were: aging <18 years; associated major thoracic or abdominal trauma; sepsis; irresponsive circulatory shock; patients pregnant or lactating; previous history of chronic corticosteroids, thyroid hormone or desmopressin use, physical signs suggestive of brain death or clinical death during the observation period. Laboratory data of 29 healthy volunteers, previously reported served as control. In the SBI patients, 10 mL blood samples were drawn on the 1st (D1), 2nd (D2), 3rd (D3) and 5th day (D5) post-inclusion for measuring AVP and serum osmolality, using a previously placed venous catheter. A 3 ml arterial blood sample was also collected for gas analysis, electrolytes, hemoglobin, hematocrit, lactate and glucose, using a previously placed arterial catheter. An isolated urinary sample at D1 and 24 hour urinary samples at D2, D3 and D5 were used for sodium and osmolality measurements. Blood samples (10 ml) for measurement of urea, creatinine and for carrying out a leukocyte count were collected only once (at D1). All samples were sent to specific laboratories for immediate evaluation, except the AVP sample. At the time of blood sampling for AVP measurement, the following clinical parameters were recorded: systemic blood pressure (SBP), central venous pressure (CVP), heart rate, urinary output and body temperature. During data collection, the volumes and types of fluid infused into the patients in the preceding 24 hours were registered for calculating the quantity of sodium that has been administered. Simultaneously, twenty- four hour urine collection was carried out, stored at 4oC and sent for measurement of urinary sodium. Sodium balance was then calculated at D2, D3 and D5[4 ,8].
  • 3. Geetha.T Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 5, Issue 4, ( Part -4) April 2015, pp.19-22 www.ijera.com 21 | P a g e Fig 1. Vasopressin serum levels in survivors and non-survivors. V. MATHEMATICAL RESULTS VI. CONCLUTION Plasma levels of AVP in healthy individuals at rest are usually very low. There was a slight variability of serum AVP levels in patients with SBI, seen as isolated plasmatic peaks, but their mean values always remained within the normal range, and these levels tended to decrease over time, both in survivors and non-survivors. Serum sodium and plasma osmolality have shown great variations in patients with SBI, and non-survivors have shown greater and more significant deviations from normal values than those who survived. We found that the vasopressin levels of non survivors were increased. REFERENCES [1]. Boughey JC, Yost MJ, Bynoe RP. Diabetes insipidus in the head-injured patient. Am Surg 2004;70:500-503. [2]. Cintra E de A, Maciel JA Jr, Araújo S, et al. Vasopressin serum levels in patients with 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 1 2 3 4 vasopressin Time Non survivors Survivors
  • 4. Geetha.T Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 5, Issue 4, ( Part -4) April 2015, pp.19-22 www.ijera.com 22 | P a g e severe brain lesions and in brain-dead patients. Arq Neuropsiquiatr 2004;62:226- 232. [3]. V. G. Kulkarni, Modeling and Analysis of Stochastic Systems: Chapman& Hall, 1995. [4]. Laszló FA, Varga C, Dóczi T. Cerebral oedema after subarachnoid haemorrhage. Pathogenetic significance of vasopressin. Acta Neurchir (Wien)1995;133:122-133. [5]. R. Marie and K. S. Trivedi, “A note on the effect of pre emptive policies on the stability of a priority queue,” Information Processing Letters, vol.24, no. 6, pp. 397– 401, 1987. [6]. M. Perman, A. Senegacnik, and M. Tuma, “Semi-Markov models with an application to power-plant reliability analysis,” IEEE Trans. Reliability,vol. 46, pp. 526–532, 1997. [7]. Tenedieva VD, Lyamin PV, Nepomnyaschi VP. The plasma and CSF vasopressin levels in brain tumors with brain edema. Acta Neurochir (Wien) 1994;60(Suppl):S387- S389. [8]. Yuan XQ, Wade CE. Neuroendocrine abnormalities in patients with traumatic brain injury. Front Neuroendocrinol 1991; 12:209-230.