ABSTRACT
In this study, a novel approach is proposed, the imaging of crackle sounds distribution on the thorax based on processing techniques that could contend with the detection and count of crackles; hence, the normalized fractal dimension (NFD), the univariate AR modeling combined with a supervised neural network (UAR-SNN), and the time-variant autoregressive (TVAR) model were assessed. The proposed processing schemes were tested inserting simulated crackles in normal lung sounds acquired by a multichannel system on the posterior thoracic surface. In order to evaluate the robustness of the processing schemes, different scenarios were created by manipulating the number of crackles, the type of crackles, the spatial distribution, and the signal to noise ratio (SNR) at different pulmonary regions. The results indicate that TVAR scheme showed the best performance, compared with NFD and UAR-SNN schemes, for detecting and counting simulated crackles with an average specificity very close to 100%, and average sensitivity of 98 ± 7.5% even with overlapped crackles and with SNR corresponding to a scaling factor as low as 1.5. Finally, the performance of the TVAR scheme was tested against a human expert using simulated and real acoustic information. We conclude that a confident image of crackle sounds distribution by crackles counting using TVAR on the thoracic surface is thoroughly possible. The crackles imaging might represent an aid to the clinical evaluation of pulmonary diseases that produce this sort of adventitious discontinuous lung sounds.
Subject(s)
Auscultation/methods , Respiratory Sounds/diagnosis , Signal Processing, Computer-Assisted , Adult , Fractals , Humans , Neural Networks, Computer , Young AdultSubject(s)
Algorithms , Auscultation/methods , Diagnosis, Computer-Assisted/methods , Lung Diseases/diagnosis , Lung Diseases/therapy , Respiratory Sounds , Sound Spectrography/methods , Artifacts , Computer Simulation , Fractals , Humans , Models, Biological , Nonlinear Dynamics , Reproducibility of Results , Sensitivity and Specificity , Signal Processing, Computer-Assisted , Stochastic ProcessesABSTRACT
OBJECTIVES: To estimate the frequency of severe adverse events (AEs) during hospital stay as well as their type and correlates in a referral hospital for respiratory diseases, using methods similar to those used in the Harvard Medical Malpractice Study. DESIGN: Retrospective review of medical records in a stratified sample of 836 patients drawn from a total of 4,555 hospital admissions registered during the year 2001. SETTING: A referral tertiary-care hospital for patients with respiratory diseases located in Mexico City. MAIN OUTCOME MEASURES: Weighted prevalence of AEs and odds ratios for correlates. RESULTS: The overall weighted prevalence for AEs was 9.1% (95% confidence interval, 7.5 to 10.4%). Of these patients, 17% had a related transient disability, 52% had a prolonged hospital stay, and 26% had an AE that according to the reviewers contributed to their death. Of the total number of AEs, 74% were qualified as potentially preventable. Among all types of AEs, we identified as most relevant for a chest hospital the delayed surgical treatment of empyema, representing 11% of the total. CONCLUSIONS: The frequency of AEs in a tertiary-care respiratory hospital is similar to that reported in general hospitals. A strategy to improve the treatment of empyema is needed.
Subject(s)
Cause of Death , Iatrogenic Disease/epidemiology , Medical Errors/statistics & numerical data , Respiratory Tract Diseases/therapy , Safety Management/standards , Adult , Adverse Drug Reaction Reporting Systems , Age Distribution , Aged , Cohort Studies , Confidence Intervals , Female , Humans , Incidence , Male , Medical Records , Mexico/epidemiology , Middle Aged , Observer Variation , Probability , Respiratory Tract Diseases/diagnosis , Respiratory Tract Diseases/mortality , Retrospective Studies , Risk Assessment , Sex Distribution , Survival AnalysisABSTRACT
Background. To characterize the gasometric and oximetric response to simulated altitudes of 3,100 m and sea level of patients with Chronic Obstructive Pulmonary Disease (COPD) and Interstitial Lung Disease (ILD) studied at 2,240 m above sea level. Methods. Consecutive stable patients with COPD and ILD were studied at the National Institute of Respiratory Diseases, a referral center for pulmonary diseases in Mexico City, and a healthy control group. The patients breathed room air (F1 O2 =0.21), for at least 15 min, then, a hypoxic mixture (F1 O2 =0.18, simulating 3,100 m), and finally, a hyperoxic mixture (F1 O2= 0.28, simulating sea level). Arterial blood gases and oxygen saturation were measured by a pulse oximeter at the end of each stage. Results. Twelve patients with COPD, 13 patients with ILD and 11 healthy controls were studied. The PaCO2 and pH were constant in the three study stages in both groups of patients and controls. A slope of PaO2 vs. altitude of 9 Torr per Km was found for each of the study's patients, either by simple linear regression or multiple regression, which is identical to that previously obtained at sea level with COPD patients (Gong et al.). Oxygen desaturation per Km of altitude change was alinear, higher for the hypoxic than for the hyperoxic challenge and more severe for the most hypoxic patients. Conclusions. Exposure test to simulated altitudes are safe, and orient the physician concerning the patient's condition at altitudes different from the place where the measurement is done. Alveolar ventilation remains constant despite hypoxia or hyperoxia during the challenges. A computer model of the lung reproduces many of the findings in the challenges of this study
