Temperature-dependent phonon dynamics of Ag3PO4 microcrystals.

In this work, we present the study of the temperature-dependent behavior of silver orthophosphate (Ag3PO4) microcrystals using in situ Raman scattering. The Ag3PO4 as-synthesized microcrystals were prepared by the precipitation method and characterized by powder X-ray diffraction (XRD), scanning electron microscopy (SEM), Raman and infrared spectroscopy, and differential scanning calorimetry (DSC). Temperature-dependent phonon dynamics were performed on Ag3PO4 microcrystals and pointed to a first-order phase transition in the temperature range 500-515 °C: Phase I (25-500 °C) â†’ Phase II (515-590 °C). The phase transition is reversible and a temperature hysteresis was observed during the heating - cooling process: Phase II (590-470 °C) â†’ Phase I (455-25 °C). The reversible phase transition is related to the distortion of the tetrahedral symmetry of PO4 caused by the decrease in the crystalline order. DSC analysis confirmed the results of temperature-dependent Raman spectroscopy.

Hemodynamic, autonomic and neurohormonal behaviour of familial amyloidotic polyneuropathy and neurally mediated syncope patients during supine and orthostatic stress.

Orthostatic intolerance (OI) syndromes are frequent and share symptoms like dizziness and orthostatic syncope. Their pathophysiology however seems to be different. The aim of our work was to evaluate autonomic and hemodynamic behaviour in patients with familial amyloidotic polyneuropathy and neurally mediated syncope in supine position and after acute orthostatic passive stress. We studied 12 patients with autonomic failure (group A), 12 patients with neurally mediated syncope (group B) and 16 aged matched normal controls (group C), in supine position and during the first 10 min of head-up tilt test (HUTT). Beat-by-beat blood pressure and heart rate were continuously monitored and digitised at 500 Hz. The baroreceptor alfa-index gain (vagal reflex-BRG), high frequency of RR variability (HFRR, vagal tonus) and low frequency of systolic arterial pressure variability (LFSAP, sympathetic tone) were calculated. Catecholamines, plasma brain (BNP) and atrial natriuretic (ANP) peptides were also measured. Hemodynamic data were derived and calculated by the non-invasive modelflow method. During supine position, cardiac output (CO) and stroke volume (SV) were similar in all groups. Mean arterial pressure (MAP) and BNP were higher in group A. Noradrenaline (NOR), BRG, HFRR and LFSAP were extremely low in this group. BRG and adrenaline (ADR) were higher in group B than in controls. Within the first 10 min of HUTT, there was a huge drop of CO, SV and MAP in group A, maintenance of very low levels of neurohormones and lack of autonomic function. HR, LFSAP and ADR had a higher rise at HUTT in group B compared with controls (p<0.01) but a significant decrease of BRG was noted (p<0.05). ANP or BNP did not change with tilt in any group. Different orthostatic intolerance syndromes may show important hormonal, autonomic and hemodynamic differences during supine rest and enhanced after passive orthostatism.

Determinants of in-hospital mortality in women with acute myocardial infarction who underwent primary coronary angioplasty.

INTRODUCTION: According to recent data, women have a greater risk of dying from an acute coronary event. The determinants of this ominous prognosis are not completely understood. Preliminary analysis of our data suggested that this poorer prognosis is also observed in the subgroup of patients with acute myocardial infarction submitted to direct coronary angioplasty (PTCA). This finding prompted us to investigate gender differences and their determinants in this particular context. OBJECTIVE: To identify risk factors associated with the greater in-hospital mortality of women with acute infarction who underwent PTCA. METHODS: One hundred and forty-five consecutive patients with acute myocardial infarction who underwent direct PTCA in the same hospital were studied retrospectively. Data were collected from the database of the catheterisation laboratory and from clinical files. The following parameters were analysed: in-hospital mortality, age, prevalence of diabetes mellitus, history of coronary heart disease, time elapsed from beginning of symptoms to coronary intervention, peak values of CK and MB-CK, number of coronary arteries with significant disease at angiography, culprit lesion localisation, and prevalence of shock on admission. For statistical analysis, cross-tabulation (Pearson x2) and comparison of means (Student's t test) were employed when appropriate; an error of 5% was admitted for the rejection of the null hypothesis. RESULTS: Women (n = 39) represented 26.9% of sample. In hospital mortality was 28.2% (n = 11) for women and 11.3% (n = 12) for men (p = 0.014). The prevalence of coronary heart disease before the current acute event, the time elapsed from beginning of symptoms to coronary intervention, and maximum values of CK and MB-CK were similar in both genders. Differences between women and men were found as regards the following variables (women vs men): age (61.7 +/- 10 vs 56.1 +/- 12.6 years), prevalence of left main disease (15.3 vs 1.9%) and prevalence of shock (41 vs 17%) and diabetes (38.7 vs 13.6%). Considering women and men who died, only disease severity as evaluated by the number of vessels involved distinguished both genders (p = 0.05). CONCLUSIONS: In our experience, women admitted with acute myocardial infarction and treated by direct PTCA are, on average, older than men and have a greater prevalence of shock at admission, of left main disease and of diabetes, and more severe coronary artery disease. In the present series and as regard in-hospital mortality, disease severity as evaluated by the number of vessels involved is the only variable that discriminates women from men.

Automatic classifiers for the interpretation of electrocardiograms.

The morphological diagnosis of ECGs is a pattern recognition procedure. The way the clinician does this is not clearly elucidated. Nevertheless, several models aimed at achieving identical results by automatic means are empleyed. While in the doctor's case this is not exactly so, the computer task for ECG interpretation comprises two distinct and sequential phases: feature extraction and classification. A set of signal measurements containing information for the characterization of the waveform is first obtained. These waveform descriptors are then used to allocate the ECG to one or more diagnostic classes in the classification phase. The classifier can embody rules-of-thumb used by the clinician to decide between conflicting ECG diagnosis and formal or fuzzy logic as a reasoning tool (heuristic classifiers). On the other hand, it can use complex and even abstract signal features as waveform descriptors and different discriminant function models for class allocation (statistical classifiers). More recently, artificial neural network techniques have also been used for signal classification. The authors review feature selection techniques and classification strategies, problems and methods of performance evaluation and results obtained by different classification approaches. A brief discussion of the relative merits of the two main types of ECG classifiers, logical and statistical, is included.

The diagnostic performance of computer programs for the interpretation of electrocardiograms.

BACKGROUND: Computer programs for the interpretation of electrocardiograms (ECGs) are now widely used. However, a systematic assessment of various computer programs for the interpretation of ECGs has not been performed. METHODS: We undertook a large international study to compare the performance of nine electrocardiographic computer programs with that of eight cardiologists in interpreting ECGs in 1220 clinically validated cases of various cardiac disorders. ECGs from the following groups were included in the sample: control patients (n = 382); patients with left ventricular hypertrophy (n = 183), right ventricular hypertrophy (n = 55), or biventricular hypertrophy (n = 53); patients with anterior myocardial infarction (n = 170), inferior myocardial infarction (n = 273), or combined myocardial infarction (n = 73); and patients with combined infarction and hypertrophy (n = 31). The interpretations of the computer programs and the cardiologists were compared with the clinical diagnoses made independently of the ECGs, and the computer interpretations were compared with those of the cardiologists. RESULTS: The percentage of ECGs correctly classified by the computer programs (median, 91.3 percent) was lower than that of the cardiologists (median, 96.0 percent; P less than 0.01). The median sensitivity of the computer programs was also significantly lower than that of the cardiologists in diagnosing left ventricular hypertrophy (56.6 percent vs. 63.9 percent, P less than 0.02), right ventricular hypertrophy (31.8 percent vs. 46.6 percent, P less than 0.01), anterior myocardial infarction (77.1 percent vs. 84.9 percent, P less than 0.001), and inferior myocardial infarction (58.8 percent vs. 71.7 percent, P less than 0.0001). The median total accuracy level (the percentage of correct classifications) was 6.6 percent lower for the computer programs (69.7 percent) than for the cardiologists (76.3 percent; P less than 0.001). However, the performance of the best programs nearly matched that of the most accurate cardiologists. CONCLUSIONS: Our study shows that some but not all computer programs for the interpretation of ECGs perform almost as well as cardiologists in identifying seven major cardiac disorders.

Evaluation of ECG interpretation results obtained by computer and cardiologists.

In an international project investigators from 25 institutes are trying to establish a common reference library and evaluation methods for testing the diagnostic performance of various ECG computer programs and of cardiologists, based on ECG-independent clinical information. A first set of 500 validated ECGs was collected and analyzed by fifteen different computer programs and nine cardiologists, seven of who analysed the ECG and five the VCG. A coding scheme was used to map individual diagnostic statements onto a common set. Combined program and referee results were obtained by weighted averaging. Preliminary results indicate that the classification accuracy of several programs can still be improved. However, it was also apparent that the results of the best 12-lead ECG computer programs proved to be almost as accurate as the best of seven cardiologists in classifying seven main disease categories, i.e., normal, left, right and biventricular hypertrophy, anterior, inferior and combined myocardial infarction. Evaluation of rhythm statements and conduction disturbances was not included in the study. The data collection is still being pursued in order to reach over 1,000 cases. In this way a common diagnostic database is being established for comparative testing of diagnostic computer programs. This should lead to consumer protection and improve the accuracy and reliability of computerized electrocardiography.

Interpretation of short ECGs with a personal computer: the Porto program.

A computer program for ECG analysis and interpretation developed at the University of Porto, Portugal is presented. The program runs on a microcomputer and employs the three-lead Frank VCG. The signals are sampled at 250 Hz with 8-bit precision during 5.5 s. Details on signal conditioning and wave recognition and measurement techniques are given. The diagnostic part of the program uses decision-tree logic. The decision rules are mainly derived from the Washington Code. The diagnostic accuracy of four classes (normal, left and right ventricular hypertrophies and myocardial infarction), evaluated in a sample of 1,075 pediatric and adult patients and classified by ECG-independent means was 76%. The program is currently being evaluated on the CSE database.

Effect of combining electrocardiographic interpretation results on diagnostic accuracy.

In order to test the diagnostic performance of various ECG computer programs a reference library of ECGs is being established and evaluation methods are being developed in an international co-operative project. A pilot study was undertaken in which 250 validated electrocardiograms (ECG) and vectorcardiograms (VCG) comprising seven diagnostic groups i.e., normal, left, right and bi-ventricular hypertrophy, anterior, inferior and combined infarction have been analysed independently by 11 different computer programs as well as by six cardiologists. A coding scheme was applied to assign individual diagnostic statements to a common set and to obtain combined program and cardiologist interpretation results. Preliminary results indicate that the accuracy of classification by different programs varies widely. Total accuracy varied between 57.2% and 75.8% (median 69.4%). The cardiologists had a higher accuracy (median 74.3%) than the majority of programs, at least when using the standard ECG. As it is considered premature to stress individual program results, in view of the current sample size, the enhancement in diagnostic accuracy obtained by combining interpretation results is highlighted. Indeed combined cardiologist and program results demonstrated the highest accuracy i.e., respectively 78.7% and 76.1%, higher than the result of any individual reader or program. The combined result of the five most accurate programs was 78.4%, that of the six least accurate was 71.5%, which is again higher than the respective individual components. These findings demonstrate that the combination of expert knowledge of computer programs can, similar to panel review and group analysis in clinical practice, enhance diagnostic accuracy.

Frontal-plane QRS axis revisited: accuracy of current approximations and reappraisal of their merit in the diagnosis of right ventricular hypertrophy.

The frontal-plane mean QRS vector orientation (AQRSxy)--the so-called electrical axis--is an ECG feature commonly used for the diagnosis of right ventricular hypertrophy and is correctly measured by calculating the areas subtended by QRS deflections in two different leads. To overcome the drawbacks of doing this by hand, two alleged approximations of AQRSxy have become popular and are in current use: one is based on the measurement of QRS component wave peak amplitudes and the other on the estimation of the half-area vector of the frontal plane loop. The values obtained with the correct and the two more practical methods are compared and their diagnostic efficiency is assessed by means of a procedure for ECG criteria optimization based on the receiver operating characteristics (ROC) curve analyzed in terms of information theory. The authors conclude that the two more popular methods for AQRSxy determination provide similar values that, although correlated with the true measure of the parameter are statistically different from it. On the other hand, the diagnostic efficiency of AQRSxy alone, regardless of the method by which it is computed, is only as good as, if not bettered by, other much more easily measurable frontal-plane parameters (ie, left to rightward forces amplitude ratio in adults and rightward forces amplitude in pediatric patients).

Testing the performance of ECG computer programs: the CSE diagnostic pilot study.

In an international project investigators from 21 institutes are trying to establish a common reference library and evaluation methods for testing the diagnostic performance of various ECG computer programs using ECG independent clinical information. Preliminary results indicate that the classification accuracy of different programs varies widely.

A new ECG classifier based on linear prediction techniques.

A longstanding tradition in automatic ECG classification has been the use of conventional features (amplitudes, duration, etc.) as waveform descriptors for pattern discrimination purposes. This paper presents an alternative approach in statistical ECG classification. It is based on the use of linear prediction coefficients, a sort of "abstract" features which, as waveform descriptors, enjoy the desirable property of whole-signal dependency, being rather insensitive to high-frequency noise. Experimental results obtained on 400 ECGs distributed by four clinical groups according to clinicopathological data (normal, myocardial infarction, right and left hypertrophies) show interesting potentialities of this new method, namely a classification error for equal class prevalences (30%) significantly lower than by using conventional features. Classification and cluster separability results are presented and discussed as well as the viability of the new method in a clinical environment.

A double-blind trial comparing mianserin and maprotiline in depressed inpatients.

The antidepressant effects and side effects of mianserin and maprotiline were assessed in a double-blind trial in 62 inpatients (34 men and 28 women; mean age, 43.6 years) with primary depressive illness. For the first week of the trial, 32 patients received 30 mg/day of mianserin and 30 patients received 75 mg/day of maprotiline; for the next three weeks, the dosage of each drug was doubled. According to scores on the Hamilton Psychiatric Rating Scale for Depression, administered on days 0, 7, 14, 21, and 28, the antidepressant effects of the two drugs were virtually identical. Results of electrocardiographic and vectorcardiographic recordings and other measurements indicated that by day 28 the QRS duration was significantly longer (P less than 0.05) in the maprotiline group. On days 14 and 28, mean systolic blood pressure was significantly higher (P less than 0.05) in the maprotiline group. By day 28, the incidence of anticholinergic side effects--constipation and dry mouth--was significantly higher (P less than 0.05) in the maprotiline group. Although maprotiline's effects on heart functions never reached clinical significance, its anticholinergic side effects could be bothersome, especially to older patients.

A new ECG classification system for myocardial infarction based on receiver operating characteristic curve analysis and information theory.

An optimized three-lead ECG hierarchial decision-tree type of classification system for myocardial infarction is presented. For selection of the best threshold values for each criterion and the best association of features, we developed a procedure based on "receiver operating characteristic" (ROC) curve data analysis and information theory. Optimization was obtained through maximization of information content of the criteria. The classifier is based on nine measurements that can be easily obtained by hand (QX duration, Q/R Y amplitude, R Y amplitude, Q/R Y duration, Q Z amplitude, QRS and T axes in the horizontal plane, Q Z duration and R Z amplitude) and achieved a satisfactory performance in an independent group of patients (true-positive ratio 0.853, false-positive ratio 0.105, average information content 0.308 bits).