Late-Onset Hypogonadism in Latvia

Objective: The aim of this study was to examine how common is LOH in Latvian men and to determine the target audience that needs screening for LOH. Design and Method: 300 men over the age of 40 who came to their family doctors and to sexologists were asked to complete the questionnaires for Aging Male Symptoms Rating Scale. Men were divided in three groups based on their age: 40-49 years old, 50-59 years old, and >59 years old. The men who according to the AMS questionnaires had suspicion of LOH symptoms were asked to check their level of testosterone in the blood serum. The authors also have summarized the data on the spread of different chronic diseases among the men. Results: 134 men were asked to check level of testosterone in the blood serum. 29% of men appeared to have hypogonadism. 38% of this men appeared to have adiposity, 77% - hypertension, 18% – diabetes, 51% – dislipidemia, 66%– erectile dysfunction. Among men with normal testosterone level adiposity was found in 29%, hypertension-in 56%, diabetes-in 5%, dislipidemia-in 39%, erectile dysfunction-in 61%. Significantly in hypogonadal men in the group 50-59 years was more frequent hypertension, and in all groups – diabetes mellitus. Conclusions: 1/3 of men aged 40 and older have diagnosis of LOH in the groups under research. It is necessary to check testosterone and free testosterone level: in all men 50-59 years old with arterial hypertension; in all men over the age of 40 with diabetes.

Practices Associated with Serum Antiepileptic Drug Level Monitoring at a Pediatric Neurology Clinic

Objectives: To assess the practices associated with the application of therapeutic drug monitoring (TDM) for antiepileptic drugs (AEDs) in the management of children with structural–metabolic epilepsy. Methods: It was a retrospective chart review and included children aged ≥2 years old with structural–metabolic epilepsy, treated with AEDs, and received TDM. The data were extracted from the medical records. Results: Thirty-two patients were identified with 50 TDM assays. In two thirds of the assays, “check level” and “recheck level” were the reasons behind the requesting of serum level monitoring of AEDs. Knowledge of serum AED levels led to alterations in the management in 60% of the assays. Thirty-two (76%) pediatrician’s actions were consistent with the recommendation of TDM pharmacist. Forty-nine (98%) levels were appropriately indicated. In relation to the appropriateness of sampling time, 9 (18%) levels were not assessed due to missing data. Twenty-seven (54%) levels were appropriately sampled. Conclusions: More studies should be designed to improve the component of the current TDM request form, especially in the reason section. By the same token, the number of pointless assays and the costs to the health care system can be reduced both by enhancing and improving the educational standards of the requesting neurologists

Recognition of Handwritten Worded Amounts on Checks Using Symbolic and Neural Classifiers

This paper proposes symbolic and neural classifiers to read unconstrained handwritten worded amounts in bankchecks. Features are extracted from the binary image of the worded amount. Depending on the features extracted, some words are recognized entirely symbolically, some words entirely neurally, and the remaining both symbolically and neurally. Results of experiments at word level and check level are provided.

ACCURATE DEPTH DETERMINATION OF THE VELOCITY SURVEY WELL PHONE

Many velocity surveys have been shot in which the actual depth of the well phone was in question at one or more of the levels shot in the borehole. The computed time to the questioned level would not fit the other data obtained from the velocity survey, i.e., the data from the questioned level would not fit the time‐depth curve within reason or, more recently, it could not properly be fitted to the corrected continuous velocity log data. If the “first break” of the questioned level could not be repicked to conform to the other data, a notation was made in the velocity survey report that the depth of the well phone was probably in error. Although this assumption was correct in many cases, there are various other reasons why data from one check level should not fit the rest of the data.