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At least 73 records · Page 4Linked to original sources
PubMed1976

The cleaning and disinfection by heat of bedpans in automatic and semi-automatic machines.

This work is concerned with the cleaning and disinfection by heat of stainless-steel and polypropylene bedpans, which had been soiled with either a biological contaminant, human serum albumin (HSA) labelled with technetium-99m 99m(Tc), or a bacteriological contaminant, streptococcus faecalis mixed with Tc-labelled HSA. Results of cleaning and disinfection achieved with a Test Machine and those achieved by procedures adopted in eight different wards of a general hospital are reported. Bedpan washers installed in wards were found to be less efficient than the Test Machine, at least partly because of inadequate maintenance. Stainless-steel and polypropylene bedpans gave essentially the same results.

Automation↗
PubMed1997

Automatic arrhythmia identification using analysis of the atrioventricular association. Application to a new generation of implantable defibrillators. Participating Centers of the Automatic Recognition of Arrhythmia Study Group.

BACKGROUND: Atrioventricular association is a key criterion for arrhythmia diagnosis. Its use in a defibrillator should significantly reduce the incidence of inappropriate shocks. Therefore, we evaluated the diagnostic accuracy of an algorithm that uses dual-chamber sensing and analysis of atrioventricular association to discriminate ventricular from supraventricular arrhythmias in a prototype of an implantable defibrillator. METHODS AND RESULTS: The algorithm performed a stepwise analysis of arrhythmias. The rhythm was first classified on the basis of cycle lengths. Each episode was then classified as supraventricular or ventricular in origin on the basis of the stability of cycle lengths and atrioventricular association. This algorithm was evaluated in 156 episodes of induced sustained tachycardias. Eighty-nine tachycardias were taken from the Ann Arbor electrogram library; the others were recorded in 50 patients during electrophysiological studies. The atrial and ventricular signals were stored on an external recorder and then injected into an external prototype of a defibrillator system. The algorithm correctly diagnosed 96% of ventricular tachycardia episodes, 100% of ventricular fibrillation episodes, and 92% of double-tachycardia episodes. The mean detection time for ventricular tachycardia was 2.6 +/- 0.8 seconds, and for ventricular fibrillation, it was 2.1 +/- 0.4 seconds. The positive predictive values for the diagnoses of atrial fibrillation and atrial flutter were 92% and 86%, respectively. For ventricular tachycardia and ventricular fibrillation, the values were 95% and 100%, respectively. CONCLUSIONS: Analysis of atrioventricular association promotes reliable differentiation between ventricular and supraventricular tachycardias and should enhance the diagnostic capabilities of implantable defibrillators.

Algorithms↗
PubMed1997

Automatic external defibrillators for public access defibrillation: recommendations for specifying and reporting arrhythmia analysis algorithm performance, incorporating new waveforms, and enhancing safety. A statement for health professionals from the American Heart Association Task Force on Automatic External Defibrillation, Subcommittee on AED Safety and Efficacy.

These recommendations are presented to enhance the safety and efficacy of AEDs intended for public access. The task force recommends that manufacturers present developmental and validation data on their own devices, emphasizing high sensitivity for shockable rhythms and high specificity for nonshockable rhythms. Alternative defibrillation waveforms may reduce energy requirements, reducing the size and weight of the device. The highest levels of safety for public access defibrillation are needed. Safe and effective use of AEDs that are widely available and easily handled by nonmedical personnel has the potential to dramatically increase survival from cardiac arrest.

Algorithms↗
PubMed1986

Automatic detection of cardiac arrest rhythms prior to automatic external cardiac defibrillation.

The detection and correction of ventricular fibrillation at the earliest time after its onset is essential to ensure long-term survival. During successive cardiac arrests the rhythms occurring were sensed by using disposable pre-gelled ECG defibrillator pads placed in the anterior-anterior position. Simultaneously with the treatment, the arrest rhythms were analyzed continually every 8 to 18 seconds by a microprocessor system. This system sampled digitally the electrocardiogram, and the algorithm looked for absence of the isoelectric segment, irregular energy density spectrum, and irregular wave shape. The analysis was displayed visually as ventricular fibrillation (VF) or non-VF, and simultaneously the ECG and system's analysis were recorded on tape. Later, the system's interpretation of the rhythm was compared with the ECG record. There were 46 males and 32 females. Their ages ranged from 14 to 85 years, with a mean of 63 years. Twenty-nine patients had sustained an acute myocardial infarction. In the remaining 49 patients, there were a variety of causes for cardiac arrest, including heart failure, vasovagal syncope, cardiomyopathy, and postoperative cases. We report in detail the process and results.

Journal Article↗