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Introduction Mortality risk prediction for Intermediate Respiratory Care Unit's (IRCU) patients can facilitate optimal treatment in high-risk patients. While Intensive Care Units (ICUs) have a long term experience in using algorithms for this purpose, due to the special features of the IRCUs, the same strategics are not applicable. The aim of this study is to develop an IRCU specific mortality predictor tool using machine learning methods. Methods Vital signs of patients were recorded from 1966 patients admitted from 2007 to 2017 in the Jimenez Diaz Foundation University Hospital's IRCU. A neural network was used to select the variables that better predict mortality status. Multivariate logistic regression provided us cut-off points that best discriminated the mortality status for each of the parameters. A new guideline for risk assessment was applied and mortality was recorded during one year. Results Our algorithm shows that thrombocytopenia, metabolic acidosis, anemia, tachypnea, age, sodium levels, hypoxemia, leukocytopenia and hyperkalemia are the most relevant parameters associated with mortality. First year with this decision scene showed a decrease in failure rate of a 50%. Conclusions We have generated a neural network model capable of identifying and classifying mortality predictors in the IRCU of a general hospital. Combined with multivariate regression analysis, it has provided us with an useful tool for the real-time monitoring of patients to detect specific mortality risks. The overall algorithm can be scaled to any type of unit offering personalized results and will increase accuracy over time when more patients are included to the cohorts.

Catathrenia is a sleep disorder characterized by a prolonged expiratory sound preceded by a deep inhalation and accompanied by a bradypnea breathing-pattern. Afflicted individuals are usually unaware of their problem, so it is common that bed partners report strange sounds while breathing during sleep. There is little documented experience in treating the condition, but some studies have shown resolution of this disorder with CPAP, especially in patients with a Sleep-Disordered-Breathing (SDB) associated. Usually high-pressure-levels are recommended. We describe a patient with a self-limited benign condition (without SDB associated), with clinical repercussions due to sleep fragmentation, responding favorably to a low setting on CPAP (4 cmH20). We believe a low setting CPAP-treatment can improve nocturnal groaning episodes and daytime complaints increasing adherence.

Resumen Introduccion Historicamente se ha asumido que las unidades de cuidados intermedios respiratorios (UCIR) eran estructuras eficientes por los costes evitados atribuibles a la reduccion de los ingresos en las unidades de cuidados intensivos (UCI) y eficaces por la especializacion neumologica. Metodos Se evaluo el numero de ingresos y mortalidad en la unidad, historica y en el ano 2016. Ese ano ademas se describieron los grupos relacionados de diagnostico (GRD) agrupados y el coste evitado por estancia en UCI en relacion con todos los capitulos presupuestarios. Se realizo un analisis multivariante para asociar costes a pesos medios y complejidad y se realizo una regresion logistica multiple sobre la totalidad de enfermos ingresados de 2004 a 2017 para describir las variables asociadas a la mortalidad en nuestra unidad. Resultados La UCIR evita un coste al hospital de 500.000 €/ano al reducir dias de estancia en las UCI. El analisis sobre la cohorte de 2016 describe que los costes se asocian al peso medio y mortalidad, y por tanto, a la complejidad. El analisis de regresion logistica multivariante sobre la cohorte de 2004-2017 describe la frecuencia respiratoria, la leucopenia, la anemia, la hiperpotasemia y la acidosis como las variables que mejor se asocian con la mortalidad. El area bajo la curva para el modelo logistico fue de 0,75. Conclusion La UCIR analizada ha demostrado ser eficiente en terminos de «coste evitado» y ahorro ligado a la complejidad. Nuestros resultados sugieren que las UCIR son un entorno seguro para los pacientes al tener una mortalidad menor que otras unidades similares.

Introduction : There is limited information describing features and outcomes of patients requiring Intermediate Respiratory Care Unit (IRCU) hospitalization for COVID19 disease and as of yet, no mechanical or medical treatments have clearly demonstrated efficacy in IRCU. Methods : Demographics and clinical variables on admission, as well as medical and mechanical therapeutic interventions, were extracted from Electronic Clinical Records in 274 SARS-CoV-2 infected patients attending a third level hospital IRCU. Using multivariate logistic regression analysis, variables that best discriminated mortality were obtained. Principal components analysis and a neural network (NN) algorithm were applied. Results : In relation to respiratory support, high-flow oxygen therapy and weaning procedures were associated with survival as were CPAP and non-invasive ventilation with low levels of support among the most severely affected. The IRCU achieved a survival rate of 87.6%, avoided 178 ICU admissions, successfully referred 35% to the ICU, and of these, 94% later survived the weaning phase. Higher mortality incidence was associated with cardiac and respiratory diseases and fever, heart rhythm and blood pressure disturbances. Following analysis of specific therapeutic options Corticoids and Anticoagulants were associated with better outcomes. Conclusions : The IRCU prevented the collapse of the ICU, allowed for recovered ICU patients to be quickly released from their unit, thus freeing up critical care beds and permitting them to function more effectively and in terms of mortality, achieved good results, that did not worsen due to a possible delay in intubation. In addition, we have generated an open-access NN capable of identifying severity predictors of SARS-CoV-2.

There is limited information describing features and outcomes of patients requiring hospitalization for COVID19 disease and still no treatments have clearly demonstrated efficacy. Demographics and clinical variables on admission, as well as laboratory markers and therapeutic interventions were extracted from electronic Clinical Records (eCR) in 4712 SARS-CoV2 infected patients attending 4 public Hospitals in Madrid. Patients were stratified according to age and stage of severity. Using multivariate logistic regression analysis, cut-off points that best discriminated mortality were obtained for each of the studied variables. Principal components analysis and a neural network (NN) algorithm were applied.A high mortality incidence associated to age >70, comorbidities (hypertension, neurological disorders and diabetes), altered vitals such as fever, heart rhythm disturbances or elevated systolic blood pressure, and alterations in several laboratory tests. Remarkably, analysis of therapeutic options either taken individually or in combination drew a universal relationship between the use of Cyclosporine A and better outcomes as also a benefit of tocilizumab and/or corticosteroids in critically ill patients.We present a large Spanish population-based study addressing factors influencing survival in current SARS CoV2 pandemic, with particular emphasis on the effectivity of treatments. In addition, we have generated an NN capable of identifying severity predictors of SARS CoV2. A rapid extraction and management of data protocol from eCR and artificial intelligence in-house implementations allowed us to perform almost real time monitoring of the outbreak evolution.

Introduction: Historically it has been assumed that the Intermediate Respiratory Care Units (IRCU) were efficient hospital structures mainly due to the avoided costs attributable to the reduction of stay in the intensive care units (ICU) and effective because of their pulmonology specialization. Methods: We evaluated admissions and mortality in the unit, historically and in 2016. In that year, the Related Diagnostic Groups were described as well as the avoided cost per ICU stay based on all budget chapters. A multivariate analysis was performed to associate costs to average weights and complexity, and multiple logistic regression analysis was performed on all patients admitted from 2004 to 2017 to describe the variables associated with mortality in our unit. Results: An IRCU avoids a cost to the hospital of 500,000 euros / year by reducing days of stay in the ICU. The 2016 Poisson Regression analysis relate costs to mortality and average weiths. The multivariate logistic regression analysis describes the respiratory frequency, leukopenia, anemia, hyperkalemia and acidosis as the variables that are best associated with mortality. The Area Under the Curve (AUC )for the logistic model was 0.75. Conclusion: The present study describes, on the one hand, the efficiency in the form of “avoided cost” and, on the other hand, confirms that it is a safe environment for patients by markedly reducing the mortality rate.

Introduction Historically, it has been assumed that Intermediate Respiratory Care Units (IRCU) were efficient, because they saved costs by reducing the number of admissions to intensive care units (ICU), and effective, because they specialized in respiratory diseases. Methods The number of IRCU admissions and mortality rate, historically and in 2016, were evaluated. For 2016, the grouped Related Diagnostic Groups (DRGs) were also described, and the savings achieved under all budgetary headings by avoiding UCI stays were calculated. A multivariate analysis was performed to associate costs with mean weights and complexity, and multiple logistic regression was performed on all patients admitted from 2004 to 2017 to describe the variables associated with mortality in our unit. Results An IRCU generates savings of €500,000/year by reducing length of ICU stay. Analysis of the 2016 cohort shows that costs correlate with mean weight and mortality, and consequently complexity. The multivariate logistic regression analysis of the 2004–2017 cohort found respiratory frequency, leukopenia, anemia, hyperkalemia, and acidosis to be the variables best associated with mortality. The area under the curve for the logistic model was 0.75. Conclusion The IRCU analyzed in our study was efficient in terms of ‘avoided costs’ and savings associated with complexity. Our results suggest that IRCUs have a lower mortality rate than other similar units, and are therefore a safe environment for patients.

Primordial germ cells (PGCs) are the embryonic precursors of the adult gametes. Although restricted in developmental potency, PGCs express many of the same molecular markers as pluripotent embryonic stem (ES) cells and can give rise to embryonal carcinoma (EC) cells, the stem cells of testicular tumors, in vivo. Likewise, when exposed to specific growth factors in vitro PGCs can be converted into pluripotent embryonic germ (EG) cells. Here, we propose that genes differentially expressed between PGCs and ES cells are good candidates for regulating germline development. To identify genes important in regulating germ cell development and mammalian fertility, we performed suppression subtraction hybridization (SSH) between PGCs and ES cells whole gene set. Using this method, we identified the transcriptional coactivator/histone acetyltransferase CREB-binding protein (CBP) as being highly expressed in PGCs compared to ES cells. To elucidate the function of CBP in PGCs, we generated mice with a PGC-specific deletion of CBP. Loss of CBP in PGCs leads to increased apoptosis and subsequent reduction in PGC numbers. These data indicate an essential role for CBP in maintaining normal germ cell development.

The survival of the germline is vital to the survival of all animal species. Failure of germ cells to survive or to differentiate properly in the animal can result in reduced fertility, or in some cases, complete sterility (1). In addition, defects in germline development can predispose individuals to development of cancer. For example, loss of germ cells from the ovary can be associated with premature ovarian failure, but can also dispose affected individuals to the development of ovarian cancer (2). Similarly in the male, loss of germ cells from the developing testis can be associated with the development of testicular teratocarcinoma (3). Testicular cancer is the most common malignancy in young men with a peak incidence from 18–35 yr of age (4, 5). This contrasts with the incidence of ovarian tumors, which show a higher incidence after 50 yr of age, as is the case with most other solid tumors (6). Thus, even in otherwise healthy individuals, survival of the germline is an important feature of adult homeostasis.

Correct testicular function requires that a full complement of testicular germ cells be present in the adult testis. The germ-cell compartment of the testis is established early in embryonic development from the germline progenitor cells, termed primordial germ cells (PGCs). In mammals, the embryonic history of the germline has been well established. PGCs can be traced in the embryo by staining embryo sections for tissue nonspecific alkaline phosphatase (TNAP) and by antigenic markers recognized by rabbit polyclonal and mouse monoclonal antibodies (1–5). That these TNAP+ cells are indeed PGCs is confirmed by the fact that these cells are deficient or absent in mouse mutants that are sterile (6–9). PGCs arise outside of the gonad anlagen, and colonization of the gonad is brought about partly through the morphogenetic movements of the embryo and partly through active directed migration (2). During this period of gonad colonization the numbers of germ cells increases.