Usefulness of Artificial Neural Networks in the Diagnosis and Treatment of Sleep Apnea-Hypopnea Syndrome

Sleep apnea-hypopnea syndrome (SAHS) is a chronic and highly prevalent disease considered a major health problem in industrialized countries. The gold standard diagnostic methodology is in-laboratory nocturnal polysomnography (PSG), which is complex, costly, and time consuming. In order to overcome these limitations, novel and simplified diagnostic alternatives are demanded. Sleep scientists carried out an exhaustive research during the last decades focused on the design of automated expert systems derived from artificial intelligence able to help sleep specialists in their daily practice. Among automated pattern recognition techniques, artificial neural networks (ANNs) have demonstrated to be efficient and accurate algorithms in order to implement computer-aided diagnosis systems aimed at assisting physicians in the management of SAHS. In this regard, several applications of ANNs have been developed, such as classification of patients suspected of suffering from SAHS, apnea-hypopnea index (AHI) prediction, detection and quantification of respiratory events, apneic events classification, automated sleep staging and arousal detection, alertness monitoring systems, and airflow pressure optimization in positive airway pressure (PAP) devices to fit patients’ needs. In the present research, current applications of ANNs in the framework of SAHS management are thoroughly reviewed

Synthesis and SAR studies on azetidine-containing dipeptides as HCMV inhibitors

SAR studies on an azetidine-containing dipeptide prototype inhibitor of HCMV are described. Three series of structurally modified analogues, involving substitutions at the N- and C-terminus, and at the C-terminal side-chain were synthesized and evaluated for antiviral activity. Aliphatic or no substituents at the C-carboxamide group, an aliphatic C-terminal side-chain, as well as a benzyloxycarbonyl moiety at the N-terminus were absolute requirements for anti-HCMV activity. The conformational restriction induced by the 2-azetidine residue into the dipeptide derivatives, identified by (1)H NMR as a γ-type reverse turn, seems to have influence on the activity of these molecules.status: publishe

European Respiratory Society International Congress 2017

Producción CientíficaBackground. Standard pediatric in-lab polysomnography (PSG) is relatively unavailable and particularly intrusive for children. In low resource settings, nocturnal oximetry has been proposed as a feasible and potentially reliable screening tool for childhood obstructive sleep apneahypopnea syndrome (OSAHS), although additional confirmatory evidence is needed. Aims and objectives. Discrete wavelet transform (DWT) could be a useful tool to characterize fluctuations in nocturnal oximetry. We aimed at designing and assessing a model for detecting childhood OSAHS using anthropometric and DWT features. Methods. A total of 298 children with clinical suspicion of OSAHS underwent in-lab PSG. A cut-off of 5 events/h was stipulated as confirming OSAHS. DWT was used to inspect the spectral content of oximetry in frequency bands linked with apnea pseudo-periodicity: detail levels D9 (0.024-0.049 Hz) and D10 (0.012-0.024 Hz). Mean, variance, minimum, and maximum of DWT coefficients were computed. Stepwise logistic regression was employed to build an OSAHS model from DWT, age, gender, and body mass index (BMI) z score. Training (60%) and test (40%) sets were randomly allocated. Results. Age, gender, D9 mean, and D10 variance were automatically selected. Our model reached 79.1% sensitivity, 81.7% specificity, 4.33 LR+, 0.26 LR-, and 80.5% accuracy in the test set. Conclusions. Features from DWT coefficients and anthropometric variables such as age provide complementary information that enables detection of moderate-to-severe childhood OSAHS in a high pre-test probability cohort.SEPAR (153/2015), Junta Castilla y LeÓn (VA037U16), MINECO (IJCI-2014-22664)

Compilación de Proyectos de Investigación desde el año 2003 al 2012

Listado de Proyectos de investigación de UPIICSA desde 2003 a 201

Evolution over Time of Ventilatory Management and Outcome of Patients with Neurologic Disease∗

OBJECTIVES: To describe the changes in ventilator management over time in patients with neurologic disease at ICU admission and to estimate factors associated with 28-day hospital mortality. DESIGN: Secondary analysis of three prospective, observational, multicenter studies. SETTING: Cohort studies conducted in 2004, 2010, and 2016. PATIENTS: Adult patients who received mechanical ventilation for more than 12 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among the 20,929 patients enrolled, we included 4,152 (20%) mechanically ventilated patients due to different neurologic diseases. Hemorrhagic stroke and brain trauma were the most common pathologies associated with the need for mechanical ventilation. Although volume-cycled ventilation remained the preferred ventilation mode, there was a significant (p < 0.001) increment in the use of pressure support ventilation. The proportion of patients receiving a protective lung ventilation strategy was increased over time: 47% in 2004, 63% in 2010, and 65% in 2016 (p < 0.001), as well as the duration of protective ventilation strategies: 406 days per 1,000 mechanical ventilation days in 2004, 523 days per 1,000 mechanical ventilation days in 2010, and 585 days per 1,000 mechanical ventilation days in 2016 (p < 0.001). There were no differences in the length of stay in the ICU, mortality in the ICU, and mortality in hospital from 2004 to 2016. Independent risk factors for 28-day mortality were age greater than 75 years, Simplified Acute Physiology Score II greater than 50, the occurrence of organ dysfunction within first 48 hours after brain injury, and specific neurologic diseases such as hemorrhagic stroke, ischemic stroke, and brain trauma. CONCLUSIONS: More lung-protective ventilatory strategies have been implemented over years in neurologic patients with no effect on pulmonary complications or on survival. We found several prognostic factors on mortality such as advanced age, the severity of the disease, organ dysfunctions, and the etiology of neurologic disease