Mass screening

About: Mass screening is a research topic. Over the lifetime, 34508 publications have been published within this topic receiving 1365148 citations.

Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram

Abstract: Asymptomatic left ventricular dysfunction (ALVD) is present in 3–6% of the general population, is associated with reduced quality of life and longevity, and is treatable when found1–4. An inexpensive, noninvasive screening tool for ALVD in the doctor’s office is not available. We tested the hypothesis that application of artificial intelligence (AI) to the electrocardiogram (ECG), a routine method of measuring the heart’s electrical activity, could identify ALVD. Using paired 12-lead ECG and echocardiogram data, including the left ventricular ejection fraction (a measure of contractile function), from 44,959 patients at the Mayo Clinic, we trained a convolutional neural network to identify patients with ventricular dysfunction, defined as ejection fraction ≤35%, using the ECG data alone. When tested on an independent set of 52,870 patients, the network model yielded values for the area under the curve, sensitivity, specificity, and accuracy of 0.93, 86.3%, 85.7%, and 85.7%, respectively. In patients without ventricular dysfunction, those with a positive AI screen were at 4 times the risk (hazard ratio, 4.1; 95% confidence interval, 3.3 to 5.0) of developing future ventricular dysfunction compared with those with a negative screen. Application of AI to the ECG—a ubiquitous, low-cost test—permits the ECG to serve as a powerful screening tool in asymptomatic individuals to identify ALVD. A deep learning algorithm applied to the electrocardiogram—a test of the heart’s electrical activity—can detect abnormally low contractile function of the heart, opening up the possibility for a simple screening tool for this condition.

Psychological side effects of breast cancer screening.

Abstract: Evaluated the impact of receiving abnormal mammogram results on women's anxiety and breast cancer worries and on their breast self-examination (BSE) frequency and intentions to obtain subsequent mammograms. A telephone survey was conducted with 308 women 50 years old and older approximately 3 months following a screening mammogram. Subjects included women with suspicious abnormal mammograms, nonsuspicious abnormal mammograms, and normal mammograms. Women with suspicious abnormal mammograms exhibited significantly elevated levels of mammography-related anxiety and breast cancer worries that interfered with their moods and functioning, despite the fact that diagnostic work-ups had ruled out breast cancer. Women with moderate levels of impairment in mood or functioning were more likely to practice monthly BSE than women with either high or low levels of impairment. Breast cancer worries, perceived susceptibility to breast cancer, and physician encouragement to get mammograms all exhibited independent positive relationships to mammogram intentions.

Screening, detection and management of depression in elderly primary care attenders. I: The acceptability and performance of the 15 item Geriatric Depression Scale (GDS15) and the development of short versions.

Abstract: One-hundred and ninety-eight elderly subjects attending their general practitioners (GPs) were asked to complete the 15 item Geriatric Depression Scale (GDS15). Analysable results were obtained from 194 (98%). Of these, 67 (34%) scored above the GDS15 cut-off (4/5) for significant depressive symptomatology. 87.6% found the questionnaire to be acceptable and only 3.6% found it very difficult or very stressful. The GDS15 had a high level of internal consistency (Cronbach's alpha = 0.80). All the individual items of the GDS15 associated significantly (P < 0.01) with total score and 'caseness'. A single question "do you feel that your life is empty?" identified 84% of 'cases'. In an attempt to devise short scales to screen elderly primary care patients for depression, the data were subjected to logistic regression analysis. Ten (GDS10), four (GDS4) and on (GDS1) item versions were generated. Agreement between these short scales and the GDS15 in the original sample was 95, 91 and 79% respectively. Cronbach's alpha was 0.72 for the GDS10 and 0.55 for the GDS4. The short scales were then validated in an independent sample of 120 patients in whom both GDS data and the results of a detailed psychiatric interview (the Geriatric Mental Status Schedule, GMS) were available. The sensitivity and specificity of the GDS10 against GMS caseness were 87 and 77% (cut-off 3/4); those of the GDS4 were 89 and 65% (cut-off 0/1) and 61 and 81% (cut-off 1/2). Sensitivity and specificity for the GDS1 were 59 and 75%. It is concluded that these short scales may be useful in helping GPs and practice staff to identify elderly patients with significant depressive symptoms.