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The efficacy of botulinum toxin type A injection in the hamstring and calf muscles with and without serial foot casting in gait improvement in children with cerebral palsy
Amirsalari S, Dalvand H, Dehghan L, Feizy A, Hosseini Sa, Shamsoddini A,
Volume 69, Issue 8 (11-2011)
Abstract

Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 Background: The goal of this study was to compare the efficacy of botulinum toxin type A (BTX-A) injection in the hamstring and calf muscles with and without ankle serial casting in the improvement of gait in children with cerebral palsy (CP).
Methods : This double-blind prospective clinical trial was performed on 25, 2 to 8-year-old children with hemiplegic or diplegic CP in Tehran, Iran in 2010. The participants were chosen by simple randomized sampling and were matched for age, gross motor function classification system (GMFCS) and type of CP and were randomly divided into two groups: children in the first group (13) only received BTX-A injection, but the second group (12) received BTX-A and serial foot casting starting one week after the injection.
Results : Comparison of the gross motor function, right and left knee spasticities and passive ROM of both knees between the two groups before and 1, 3, 6 and 12 months after the injections were not statistically significant (P>0.1). Furthermore, comparison of the right and left ankle spasticities and passive ROM before the injections and in1 and 3-month follow-ups did not show a statistically significant difference (P>0.1), but the differences were significant in 6 and 12-month follow-ups (P<0.05).
Conclusion: BTX-A injection with serial foot casting vs. BTX-A alone was more effective in decreasing spasticity and improving passive ROM in the ankle of children with CP, but such injections in the hamstrings were not useful in these regards.


Predicting the cause of kidney stones in patients using random forest, support vector machine and neural network
Mojgan Mortazavi, Abdolamir Atapour, Maryam Mohammadi, Mohammad Sattari,
Volume 79, Issue 9 (12-2021)
Abstract
Background: Today, with the advancement of technology in various fields, the importance of recording data in the field of health is increasing so much that for many diseases around the world, including kidney disease, registration systems have been set up. This is happening in our country and in the future, the number of these systems will increase. The medical data set contains valuable information that will be time-consuming and costly to obtain using laboratory methods, so there is a need for low-cost methods for extracting information. This study focuses on developing a predictive model for classifying the cause of kidney stones in Isfahan using three data mining techniques.
Methods: This cross-sectional research has been done from February 2021 to May 2021. The used medical data set includes information of 353 kidney stone patients in Isfahan. In this study, six target attributes of sodium, phosphate, oxalate, citrate, cysteine and uric acid were identified. The techniques for each of the 6 attributes are used separately. The techniques used in this study were three data mining techniques including random forest (RF), artificial neural network (ANN) and support vector machine (SVM).
Results: The best performance in terms of accuracy is related to support vector machine techniques in uric acid class, support vector machine in oxalate class and neural network in cysteine class. The worst performance is related to the random forest technique in the citrate class. The safest rules with a 66% confidence level are for the citrate and sodium classes, and the least reliable rule with a 50% confidence level is for the oxalate class.
Conclusion: Kidney stones can occur due to various reasons such as low citrate and high calcium oxalate. For example, for citrate, factors such as blood pH (potential of hydrogen), blood sugar and blood pressure are effective. To prevent any of the causes of kidney stones, factors should be controlled.

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