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Biomedical subjects

A C Walsh

Publications and source records attributed to A C Walsh.

At least 19 recordsLinked to original sources
PubMed1991

The psycho-chemical treatment of dementia: a very cost-effective therapy program.

The use of anticoagulant therapy along with standard psychiatric care can result in great improvement in the mental status of many dementia patients with tremendous financial savings by the elimination of the need for prolonged hospital and nursing home care. Although there is understandable fear in the medical profession of the complications of anticoagulant therapy, experience has shown that dementia patients are far safer on the therapy and at greater risk when denied the use of the anticoagulant. Two case reports are given to illustrate the effectiveness of this approach to dementia.

Aged↗
PubMed1990

Nuclear morphometry as a predictor of response to therapy in Wilms tumor: a preliminary report.

Present therapy in Wilms tumor is based upon prognosis. Current trends suggest less intensive chemotherapy and/or radiation therapy for children with favorable histological disease who are considered at low risk for recurrence and increasing the amount of therapy for those with unfavorable histological tumors who are at high risk for recurrence. Currently, pathological stage and histological appearance are used to predict prognosis. We tested a new approach. Histological sections of surgical specimens were obtained from 9 children treated for unilateral Wilms tumor. All patients had favorable histological disease, and received postoperative chemotherapy and/or radiotherapy. These specimens were evaluated by nuclear morphometry with the Hopkins Morphometry System to determine if nuclear shape descriptors could distinguish children who responded to therapy from those whose tumor recurred. Nuclear roundness, ellipticity, convexity and bending energy accurately separated the groups. Nuclear morphometry may provide useful information that will aid in predicting which children with Wilms tumor will respond to therapy and warrants further investigations.

Cell Nucleus↗
PubMed1989

A comparison of nuclear morphometry and Gleason grade as a predictor of prognosis in stage A2 prostate cancer: a critical analysis.

The natural history of stage A2 prostate cancer is unknown. Previous studies from this institution have shown that, without treatment, a third of the men with clinically localized stage A2 prostatic adenocarcinoma will have disease progression within 4 years. Presently, most patients who present with stage A2 prostate cancer receive surgical or radiation therapy. The degree of differentiation of the tumor (Gleason score) presently is used to predict the prognosis among patients with clinically localized prostate cancer. The Gleason score does well to predict the prognosis for patients with scores of 2 to 4 and 8 to 10. Unfortunately, the majority of patients fall within the range of Gleason scores of 5 to 7. Better methods are needed to predict which patients diagnosed with stage A2 prostate cancer have a high probability of disease progression. Several studies have reported that morphometrically determined nuclear shape descriptors provided accurate separation of these patients that was superior to Gleason grading methods. To evaluate critically the usefulness of nuclear morphometry for prediction of prognosis we developed a system. The Hopkins Morphometry System, that calculated and compared 15 different shape descriptors that were analyzed by 17 different statistical tests. We tested this system on 18 untreated patients with stage A2 prostate cancer with an average followup of 10.5 years (range 5 to 18 years). For each patient 17 statistical analyses of the 15 shape descriptors (255 total) were evaluated and 50 analyses (50 of 255, 19.6%), including average nuclear roundness factor, provided significant separation (p less than 0.01) of the patients on the basis of outcome, whereas the Gleason score (p equals 0.076) did not. The best separation (p less than 0.01) was provided by the lower quartile analysis of the ellipticity shape descriptor.

Adenocarcinoma↗