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Biomedical subjects

Kenichi Yoshiko

Publications and source records attributed to Kenichi Yoshiko.

2 recordsLinked to original sources

A useful new classification of dysmorphic urinary erythrocytes.

BACKGROUND: Among dysmorphic urinary erythrocytes (D cells), G1 cells or doughnut-shaped erythrocytes with one or more blebs are considered to be reliable markers for glomerular diseases. However, although there are many D cells with cytoplasmic color loss and without blebs in the urinary sediment, the significance of these cells is not clear. In this study, we devised a classification system for D cells and examined the relation between these cell types and urinalysis data. METHODS: We classified D cells into three types (D1, D2, and D3 cells): D1 cells showed a ring-like shape and severe loss of cytoplasmic color with protrusions or blebs; D2 cells showed a doughnut-like shape and moderate cytoplasmic color loss with protrusions or blebs; and D3 cells showed a doughnut-like shape and mild cytoplasmic color loss without protrusions or blebs. We calculated the numbers of D cells of each type in 45 patients with glomerular diseases and in 303 general outpatients. This was done by bright-field microscopy modified for the analysis of urinary sediment, and we also examined the significance of these cell types. RESULTS: In the 45 patients with glomerular diseases, the numbers of D1, D2, and D3 cells correlated with urine levels of proteinuria and hematuria and numbers of cellular and fatty casts. Numbers of D1 and D2 cells correlated with urine concentrations of albumin and N-acetyl-beta-D-glucosaminidase, and the proportions of D1 and D2 cells in D cells increased with the activity of glomerular diseases classified by urinalysis data. Only the number of D1 cells correlated with the urine concentration of potassium, which may increase in hemolysis. In the 303 outpatients, the sensitivity of D3 cells and D1 and/or D2 cells (G1 cells) was 73% and 46%, respectively, for the detection of glomerular diseases and the specificity was 93% and 99%, respectively. CONCLUSIONS: These data indicate that the D3 cell is a sensitive marker for glomerular diseases, and that D1 and/or D2 cells are markers for severe glomerular diseases.

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Predictive model for assessing cognitive impairment by quantitative electroencephalography.

OBJECTIVE: To assess the utility of quantitative electroencephalographic analysis as an indicator of cognitive impairment, we examined the correlation between Mini-Mental State Examination (MMSE) scores and quantitative electroencephalographic (QEEG) power values in elderly patients and constructed a regression model to predict MMSE scores. BACKGROUND: Because of the growing number of elderly individuals with cognitive deficits, there is an increasing need for simple and objective methods with which to evaluate cognitive function. Although QEEG is reportedly a useful method for this purpose, few researchers have constructed a QEEG-based model for predicting the degree of cognitive impairment in clinical settings. METHOD: We evaluated brain function using QEEG in 44 elderly patients with memory complaints and compared the results with their MMSE scores. RESULTS: In the correlation analysis, no significant correlation was found between MMSE scores and QEEG power values. However, a regression model created using relative QEEG and gender for predicting MMSE scores had an adjusted R2 of 0.471. CONCLUSIONS: This finding suggests that QEEG analysis may be a useful indicator of cognitive decline in patients with memory complaints.

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