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B P Kovatchev

Publications and source records attributed to B P Kovatchev.

12 recordsLinked to original sources
PubMed2000

Episodes of severe hypoglycemia in type 1 diabetes are preceded and followed within 48 hours by measurable disturbances in blood glucose.

This study quantifies blood glucose (BG) disturbances occurring before and after episodes of severe hypoglycemia (SH). For 6-8 months, 85 individuals with type 1 diabetes and a history of SH (age, 44+/-10 yr; 41 women and 44 men; duration of diabetes, 26+/-11 yr; hemoglobin A1c, 7.7+/-1.1%) used Lifescan One Touch BG meters for self-monitoring three to five times daily and recorded the date and time of SH episodes in diaries. For each subject, the timing of SH episodes was located in the temporal stream of SMBG readings recorded by the meter, and characteristics, including the Low BG index (LBGI), were computed in 24-h increments. In the 24-h period before the SH episode LBGI rose (P < 0.001), average BG was lower (P = 0.001), and BG variance increased (P = 0.001). In the 24 h after SH, LBGI and BGvariance remained elevated (P < 0.001), but average BG returned to baseline. These disturbances disappeared in 48 h. On the basis of LBGI we identified subjects at low, moderate, and high risk of SH, who reported, on the average, 1.7, 3.4, and 7.4 SH episodes (P < 0.005) during the study. In addition, we designed an algorithm that predicted 50% of all SH episodes that occurred in this subject group. We conclude that episodes of SH are preceded and followed by quantifiable BG disturbances, which could be used to devise warnings of imminent SH.

Activity Cycles↗
PubMed2000

Progressive hypoglycemia's impact on driving simulation performance. Occurrence, awareness and correction.

OBJECTIVE: Progressive hypoglycemia leads to cognitive-motor and driving impairments. This study evaluated the blood glucose (BG) levels at which driving was impaired, impairment was detected, and corrective action was taken by subjects, along with the mechanisms underlying these three issues. RESEARCH DESIGN AND METHODS: There were 37 adults with type 1 diabetes who drove a simulator during continuous euglycemia and progressive hypoglycemia. During testing, driving performance, EEG, and corrective behaviors (drinking a soda or discontinuing driving) were continually monitored, and BG, symptom perception, and judgement concerning impairment were assessed every 5 min. Mean +/- SD euglycemia performance was used to quantify z scores for performance in three hypoglycemic ranges (4.0-3.4, 3.3-2.8, and <2.8 mmol/l). RESULTS: During all three hypoglycemic BG ranges, driving was significantly impaired, and subjects were aware of their impaired driving. However, corrective actions did not occur until BG was <2.8 mmol/l. Driving impairment was related to increased neurogenic symptoms and increased theta-wave activity. Awareness of impaired driving was associated with neuroglycopenic symptoms. increased beta-wave activity, and awareness of hypoglycemia. High beta and low theta activity and awareness of both hypoglycemia and the need to treat low BG influenced corrective behavior. CONCLUSIONS: Driving performance is significantly disrupted at relatively mild hypoglycemia, yet subjects demonstrated a hesitation to take corrective action. The longer treatment is delayed, the greater the neuroglycopenia (increased theta), which precludes corrective behaviors. Patients should treat themselves while driving as soon as low BG and/or impaired driving is suspected and should not begin driving when their BG is in the 5.0-4.0 mmol/l range without prophylactic treatment.

Adult↗
PubMed1999

The effects of age and alcohol intoxication on simulated driving performance, awareness and self-restraint.

AIMS: To investigate whether, compared with middle-aged men (aged 30-50), older men (age > or =60) (i) perform more poorly on a driving simulator and (ii) are more sensitive to the effects of ethanol in terms of blood alcohol concentration (BAC) and driving performance, but more aware of their driving difficulties, and therefore exercise better driving judgement. METHODS: 14 Healthy middle-aged men (mean age 36 years) were compared with 14 healthy older men (mean age 69 years) on an interactive driving simulator, while sober and while legally intoxicated (BAC >80 mg/dl). RESULTS: Older age was associated with poorer driving performance on the simulator. While sober, older men exhibited more improper braking, slower driving, greater speed variability, fewer appropriate full stops and more crashes, and spent more time executing left turns (across oncoming traffic); all values < or =0.02. BACs > or =80 mg/dl were associated with impaired driving, with more inappropriate braking, fewer appropriate full stops and more time executing left turns (all values > or =0.02) and trends towards more speed variability, more low speed collisions and more wrong turns (values <0.1). However, similar ethanol consumption did not produce higher peak BAC or more driving impairments in older drivers. While there were no differences between age groups in terms of awareness of intoxication or driving difficulties, older men were unwilling to drive while legally intoxicated because of fear of physical injury, whereas middle-aged men were more likely to avoid driving when intoxicated due to fear of legal ramifications. CONCLUSION: While both age and legal intoxication affected driving performance, older men were no more sensitive to ethanol in terms of peak BACs, driving performance or awareness/judgement than middle-aged men.

Adult↗
PubMed1999

Biopsychobehavioral model of severe hypoglycemia. II. Understanding the risk of severe hypoglycemia.

OBJECTIVE: To evaluate the clinical/research utility of the biopsycho-behavioral model of severe hypoglycemia in differentiating patients with and without a history of severe hypoglycemia and in predicting occurrence of future severe hypoglycemia. RESEARCH DESIGN AND METHODS: A total of 93 adults with type 1 diabetes (mean age 35.8 years, duration of diabetes 16 +/- 10 years, HbA1 8.6 +/- 1.8%), 42 of whom had a recent history of recurrent severe hypoglycemia (SH) and 51 who did not (NoSH), used a handheld computer for 70 trials during 1 month recording cognitive-motor functioning, symptoms, blood glucose (BG) estimates, judgments concerning self-treatment of BG, actual BG readings, and actual treatment of low BG. For the next 6 months, patients recorded occurrence of severe hypoglycemia. RESULTS: SH patients demonstrated significantly more frequent and extreme low BG readings (low BG index), greater cognitive-motor impairments during hypoglycemia, fewer perceived symptoms of hypoglycemia, and poorer detection of hypoglycemia. SH patients were also less likely to treat their hypoglycemia with glucose and more likely to treat with general foods. Low BG index, magnitude of hypoglycemia-impaired ability to do mental subtraction, and awareness of neuroglycopenia, neurogenic symptoms, and hypoglycemia correlated separately with number of SH episodes in the subsequent 6 months. However, only low BG index, hypoglycemia-impaired ability to do mental subtraction, and awareness of hypoglycemia entered into a regression model predicting future severe hypoglycemia (R2 = 0.25, P < 0.001). CONCLUSIONS: Patients with a history of severe hypoglycemia differed on five of the seven steps of the biopsychobehavioral model of severe hypoglycemia. Helping patients with a recent history of severe hypoglycemia to reduce the frequency of their low-BG events, become more sensitive to early signs of neuroglycopenia and neurogenic symptoms, better recognize occurrence of low BG, and use fast-acting glucose more frequently in the treatment of low BG, may reduce occurrence of future severe hypoglycemia.

Adult↗
PubMed1998

Electroencephalographic and psychometric differences between boys with and without attention-deficit/Hyperactivity disorder (ADHD): a pilot study.

Attention-Deficit/Hyperactivity Disorder (ADHD) is reported to have an incidence of 3-5%, and is associated with a variety of interpersonal, academic, and social problem behaviors. There is controversy as to whether ADHD is a learned behavioral or brain dysfunction. Research has explored a variety of measures to assess behavioral and brain dysfunctions in this population, with no consistent and clearly diagnostic results. We investigated whether a new psychometric and a new electroencephalographic procedure would clearly differentiate ADHD. The psychometric was based on DSM-IV criteria and the EEG measure was based on the assumption that ADHD interferes with cognitive transition from one discrete task to another. Parents of four ADHD boys (ages 8-12) and four age- and interest-matched non-ADHD boys completed the ADHD Symptom Inventory, while their sons' EEG was monitored during viewing of a video and reading of a book. For the ADHD boys, this was repeated a second time, 3 months later, to assess test-retest reliability. Both the psychometric and the EEG measures clearly differentiated the two samples (p's < .01) with no overlap in scores, were reliable over 3 months (r = .87), and were significantly correlated with one another (r = .85). While a small sample size, these robust, related and reliable findings suggest that both the psychometric and the psychophysiological EEG measures deserve further replication and exploration.

Attention Deficit Disorder with Hyperactivity↗
PubMed1998

Assessment of risk for severe hypoglycemia among adults with IDDM: validation of the low blood glucose index.

OBJECTIVE: To evaluate the clinical/research utility of the low blood glucose index (LBGI), a measure of the risk of severe hypoglycemia (SH), based on self-monitoring of blood glucose (SMBG). RESEARCH DESIGN AND METHODS: There were 96 adults with IDDM (mean age 35+/-8 years, duration of diabetes 16+/-10 years, HbA1 8.6+/-1.8%), 43 of whom had a recent history of SH (53 did not), who used memory meters for 135+/-53 SMBG readings over a month, and then for the next 6 months recorded occurrence of SH. The SMBG data were mathematically transformed, and an LBGI was computed for each patient. RESULTS: The two patient groups did not differ with respect to HbA1, insulin units per day, average blood glucose (BG) and BG variability. Patients with history of SH demonstrated a higher LBGI (P < 0.0005) and a trend to be older with longer diabetes duration. Analysis of odds for future SH classified patients into low- (LBGI <2.5), moderate- (LBGI 2.5-5), and high- (LBGI >5) risk groups. Over the following 6 months low-, moderate-, and high-risk patients reported 0.4, 2.3, and 5.2 SH episodes, respectively (P = 0.001). The frequency of future SH was predicted by the LBGI and history of SH (R2 = 40%), while HbA1, age, duration of diabetes, and BG variability were not significant predictors. CONCLUSIONS: LBGI provides an accurate assessment of risk of SH. In the traditional relationship history of SH-to-future SH, LBGI may be the missing link that reflects present risk. Because it is based on SMBG records automatically stored by many reflectance meters, the LBGI is an effective and clinically useful on-line indicator for SH risk.

Adult↗
PubMed1997

Symmetrization of the blood glucose measurement scale and its applications.

OBJECTIVE: To introduce a data transformation that enhances the power of blood glucose data analyses. RESEARCH DESIGN AND METHODS: In the standard blood glucose scale, hypoglycemia (blood glucose, < 3.9 mmol/l) and hyperglycemia (blood glucose, > 10 mmol/l) have very different ranges, and euglycemia is not central in the entire blood glucose range (1.1-33.3 mmol/l). Consequently, the scale is not symmetric and its clinical center (blood glucose, 6-7 mmol/l) is distant from its numerical center (blood glucose, 17 mmol/l). As a result, when blood glucose readings are analyzed, the assumptions of many parametric statistics are routinely violated. We propose a logarithmic data transformation that matches the clinical and numerical center of the blood glucose scale, thus making the transformed data symmetric. RESULTS: The transformation normalized 203 out of 205 data samples containing 13,584 blood glucose readings of 127 type 1 diabetic individuals. An example illustrates that the mean and standard deviation based on transformed, rather than on raw, data better described subject's blood glucose distribution. Based on transformed data: 1) the low blood glucose index predicted the occurrence of severe hypoglycemia, while the raw blood glucose data (and glycosylated hemoglobin levels) did not; 2) the high blood glucose index correlated with the subjects' glycosylated hemoglobin (r = 0.63, P < 0.001); and 3) the low plus high blood glucose index was more sensitive than the raw data to a treatment (blood glucose awareness training) designed to reduce the range of blood glucose fluctuations. CONCLUSIONS: Using symmetrized, instead of raw, blood glucose data strengthens the existing data analysis procedures and allows for the development of new statistical techniques. It is proposed that raw blood glucose data should be routinely transformed to a symmetric distribution before using parametric statistics.

Adult↗
PubMed1994

Frequency of severe hypoglycemia in insulin-dependent diabetes mellitus can be predicted from self-monitoring blood glucose data.

Severe hypoglycemia is associated with insulin-dependent diabetes mellitus and may occur more frequently as metabolic control approaches normal. The goal of this study was to determine whether the frequency of severe hypoglycemia could be predicted by the following predictor variables: 1) frequency and degree of low blood glucose (BG) readings, 2) degree of BG variability during routine self-monitoring blood glucose (SMBG) readings, and 3) level of glycemic control measured by glycosylated hemoglobin-A1 (HbA1). Seventy-eight insulin-dependent diabetes mellitus subjects from 3 different sites had their glycosylated HbA1 assayed and then performed 50 SMBG recordings during the next 2-3 weeks. Over the following 6 months, subjects recorded their severe hypoglycemic episodes (stupor or unconsciousness). There was no difference in the number of severe hypoglycemic episodes between subjects in good vs. poor metabolic control. A higher frequency of severe hypoglycemia during the subsequent 6 months was predicted by frequent and extreme low SMBG readings and variability in day to day SMBG readings. Regression analysis indicated that 44% of the variance in severe hypoglycemic episodes could be accounted for by initial measures of BG variance and the extent of low BG readings. Patients who recorded variable and frequent very low BG readings during routine SMBG were at higher risk for subsequent severe hypoglycemia. Individuals who had lower glycosylated Hb levels were not at higher risk of severe hypoglycemic episodes.

Adult↗
PubMedDate not supplied

Evaluating driving performance of outpatients with Alzheimer disease.

BACKGROUND: Alzheimer disease (AD) is a progressive disease, with multiple physiologic, psychologic, and social implications. A critical issue in its management is when to recommend restrictions on autonomous functioning, such as driving an automobile. This study evaluates driving performance of patients with AD and its relation to patient scores on the Mini-Mental State Exam (MMSE). METHODS: This study compared 29 outpatients with probable AD with 21 age-matched control participants on an interactive driving simulator to determine how the two groups differed and how such differences related to mental status. RESULTS: Patients with AD (1) were less likely to comprehend and operate the simulator cognitively, (2) drove off the road more often, (3) spent more time driving considerably slower than the posted speed limit, (4) spent less time driving faster than the speed limit, (5) applied less brake pressure in stop zones, (6) spent more time negotiating left turns, and (7) drove more poorly overall. There were no observed differences between AD patients and the control group in terms of crossing the midline and driving speed variability. Among the AD patients, those who could not drive the simulator because of confusion and disorientation (n = 10) had lower MMSE scores and drove fewer miles annually. Those AD patients who had stopped driving also scored lower on their MMSE but did not perform more poorly on the driving simulator. Factor analysis revealed five driving factors associated with AD, explaining 93 percent of the variance. These five factors correctly classified 27 (85 percent) of 32 AD patients compared with the control group. Of the 15 percent who were improperly classified, there were three false positives (control participants misclassified as AD patients) and two false negatives (AD patients misclassified as control participants). The computed total driving score correlated significantly with MMSE scores (r = -.403, P = 0.011). CONCLUSION: Driving simulators can provide an objective means of assessing driving safety.

Aged↗