Objective: Aimed to asses the role of PT estimation in early diagnosis and predicting the extent and the outcome of head injury with ICerH and/ or Contusion
Method :PT was measured by Digiclot 818
Group –1: One hundred consecutive head injured patients admitted at Neurosurgical and Al Ramadi teaching hospitals were initially estimated for prothrombin time and subsequently scanned
Group-2 : Two hundred twenty five consecutive non scanned head injured patients admitted to Neurosurgical and Al Ramadi teaching hospitals were estimated with prothrombin time at the time of insult and subsequently for the next two weeks Al – Kindy Col Med J 2012; Vol. 8 No. 1 P: 54
Clinical and neurological evaluation (GCS) score in addition to computerized tomography scan was done for both groups
Result :Group -1: Twenty eight (28%) of the initially estimated head injured patients had prolonged prothrombin time in which their subsequent CT scan revealed an ICer H and/or contusion
Seventy six (76%) percent of those with severely head injured patients (GCS≤8) were having an initial prothrombin time prolongation..While those with mild head injury (GCS≥12) only thirty (30%) of them were having the initial prothrombin time prolongation
Group-2 Those patients who survived the initial insult and subsequently thereafter (surgically or conservatively treated) even with a deficit.. Daily estimation of prothrombin time showed a decline within the 7-14 days
Those patients who finally died (surgically or conservatively treated) daily estimation of prothrombin time showed a persistent elevation or a fluctuation within the next 7-14 day
Conclusion Prothrmbin time is an important
parameter in :
1-Reflecting the severity of head injury (GCS)
3-Early detection of ICerH and /or contusion
2-Prognostic value in cases of of ICerH and /or contusion
Abb : ICerH = Intracerebral hematomas,SDH=subdural hematomas,EDH=epidural hematomas,SAH=subarachnoid hemorrhages,PT=Prothrombin time,Pts=Patients,CT scan=computarized tomography.
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Abstract:
We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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Many athletes believe that it enhances the level of performance during training and competition, in addition to compensating for fluids during exercise when the levels of temperature and humidity in the atmosphere rise during the athlete's intensive training, as it increases the requirements for fluid compensation to avoid the risk of potential thermal disorders. If training continues for more than an hour causing fatigue, athletes are advised to drink carbohydrate drinks that quickly convert to glucose in the blood, while sodium should be included in the fluids consumed during exercise or matches that last more than (1-2 hours). The effect of drinking a drink containing 12% carbohydrates and electrolytes before each half of a simul
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