Individual outcome prediction models for patients with COVID-19 based on their first day of admission to the intensive care unit.

BACKGROUND: Currently, good prognosis and management of critically ill patients with COVID-19 are crucial for developing disease management guidelines and providing a viable healthcare system. We aimed to propose individual outcome prediction models based on binary logistic regression (BLR) and artificial neural network (ANN) analyses of data collected in the first 24 h of intensive care unit (ICU) admission for patients with COVID-19 infection. We also analysed different variables for ICU patients who survived and those who died. METHODS: Data from 326 critically ill patients with COVID-19 were collected. Data were captured on laboratory variables, demographics, comorbidities, symptoms and hospital stay related information. These data were compared with patient outcomes (survivor and non-survivor patients). BLR was assessed using the Wald Forward Stepwise method, and the ANN model was constructed using multilayer perceptron architecture. RESULTS: The area under the receiver operating characteristic curve of the ANN model was significantly larger than the BLR model (0.917 vs 0.810; p < 0.001) for predicting individual outcomes. In addition, ANN model presented similar negative predictive value than the BLR model (95.9% vs 94.8%). Variables such as age, pH, potassium ion, partial pressure of oxygen, and chloride were present in both models and they were significant predictors of death in COVID-19 patients. CONCLUSIONS: Our study could provide helpful information for other hospitals to develop their own individual outcome prediction models based, mainly, on laboratory variables. Furthermore, it offers valuable information on which variables could predict a fatal outcome for ICU patients with COVID-19.

Current use of equations for estimating glomerular filtration rate in Spanish laboratories.

INTRODUCTION: In 2006 the Spanish Society of Clinical Biochemistry and Molecular Pathology (SEQC) and the Spanish Society of Nephrology (S.E.N.) developed a consensus document in order to facilitate the diagnosis and monitoring of chronic kidney disease with the incorporation of equations for estimating glomerular filtration rate (eGFR) into laboratory reports. The current national prevalence of eGFR reporting and the degree of adherence to these recommendations among clinical laboratories is unknown. METHODS: We administered a national survey in 2010-11 to Spanish clinical laboratories. The survey was through e-mail or telephone to laboratories that participated in the SEQC’s Programme for External Quality Assurance, included in the National Hospitals Catalogue 2010, including both primary care and private laboratories. RESULTS: A total of 281 laboratories answered to the survey. Of these, 88.2% reported on the eGFR, with 61.9% reporting on the MDRD equation and 31.6% using the MDRD-IDMS equation. A total of 42.5% of laboratories always reported serum creatinine values, and other variables only when specifically requested. Regarding the way results were presented, 46.2% of laboratories reported the exact numerical value only when the filtration rate was below 60mL/min/1.73m2, while 50.6% reported all values regardless. In 56.3% of the cases reporting eGFR, an interpretive commentary of it was enclosed. CONCLUSIONS: Although a high percentage of Spanish laboratories have added eGFR in their reports, this metric is not universally used. Moreover, some aspects, such as the equation used and the correct expression of eGFR results, should be improved.

Rutas de recogida de muestras y error en el proceso analítico / Sample collection routes and errors in the analytical process

Introducción. Distintos trabajos apuntan al hecho de que la fase preanalítica es la que concentra la mayor parte de los errores que afectan al resultado final del análisis. El tiempo que transcurre entre la toma de una muestra y su llegada al laboratorio para su análisis es crucial para garantizar la calidad de los resultados. Si se considera además la tendencia general de concentración del proceso analítico en grandes laboratorios, toma especial relevancia el diseño y la planificación de las rutas de recogida de muestras que minimicen el tiempo de transporte. Material y métodos. En primer lugar, se contextualiza el problema de la optimización de las rutas desde el punto de vista de la investigación operativa, presentando los dos modelos esenciales relacionados: el Vehicle Routing Problem y el Traveling Salesman Problem, introduciendo la representación de este último mediante grafos. Seguidamente, se describen dos estrategias básicas para obtener aproximaciones a las soluciones óptimas, que se aplicarán para resolver un caso sencillo y práctico con el fin de evaluar la calidad del servicio interno de transporte de muestras de un laboratorio clínico. Resultados. Se presentan los resultados obtenidos y se valora la calidad de la ruta que sigue el coche valija (CV) del laboratorio, concluyendo que el servicio prestado es casi óptimo en relación con los posibles circuitos alternativos. Discusión. La logística en el campo de la preanalítica es determinante en el buen funcionamiento de los laboratorios y un rasgo diferencial entre los que apuestan por la calidad y la innovación. Hemos creído conveniente redactar este artículo para que el personal sanitario encargado de la planificación y el seguimiento de las rutas de transporte de muestras sepa a qué tipo de problemas se enfrenta y cómo puede valorarlos. Consideramos que el ejemplo descrito, pese a su sencillez, puede despertar el interés del público al que va dirigido, y ayudar a la evaluación y mejora del proceso de recogida, traslado y análisis de las muestras (AU)

Introduction. Several studies point to the fact that the pre-analytical phase concentrates most of the errors affecting the outcome of the analysis. The time lag between taking a sample and its arrival to the laboratory for analysis is crucial to ensure the quality of results. If we consider the general trend of concentration of the analytical process in large laboratories, the design and planning of sample collection routes to minimise travel time becomes especially relevant. Methods and materials. First of all, the authors contextualize the problem of route optimization from the viewpoint of Operational Research, presenting the two basic related models: the Vehicle Routing Problem (VRP) and the Travelling Salesman Problem (TSP), introducing the representation of the latter through graphs. Afterwards, they describe two basic strategies for obtaining approximations to the optimal solutions, applying them to solve a simple and practical case to evaluate the quality of an internal transport service from a clinical laboratory. Results. The authors present the results and evaluate the quality of the route held by the lab's car bag, concluding that the service is nearly optimal in relation to possible alternative circuits. Discussion. Logistics in the field of pre-analytical processes is closely related to success in the daily operation of laboratories, and a distinguishing feature between those who are committed to quality and innovation. We thought it advisable to write this article so that the health personnel responsible for planning and monitoring sample transportation routes should know what problems there are and how to assess them. We consider that the example described here, despite its simplicity, can stimulate the interest of the audience it is directed to and can help to assess and improve the processes that include, collection, transport and analysis of clinical samples (AU)

Cistatina C en la evaluación de la función renal / Assessment of renal function using cystatin C

La medición del filtrado glomerular es el mejor índice de valoración de la función renal. La creatinina sérica es el marcador de filtrado glomerular más utilizado, a pesar de estar sometido a diferentes fuentes de variabilidad. La cistatina C es una proteína de bajo peso molecular propuesta como marcador de función renal más sensible que la creatinina al detectar de forma precoz alteraciones en la función renal. La medida de cistatina C en suero en determinados grupos de pacientes como ancianos, niños o diabéticos parece aportar mayor información que la creatinina. Sin embargo, presenta alteraciones en su concentración sérica por factores diferentes al filtrado glomerular. Actualmente no hay evidencia científica suficiente que justifique el cambio de las ecuaciones de estimación del filtrado glomerular basadas en la concentración sérica de creatinina por la medida de la concentración sérica de cistatina C en la evaluación de la función (AU)

Glomerular filtration is the best index for assessing renal function. Despite being subjected to several sources of variability, serum creatinine is the most common glomerular filtration marker in use. Cystatin C is a low molecular weight protein which is more sensitive than creatinine, particularly for the identification of initial small decreases in renal function. The use of cystatin C in certain groups of patients such as elderly, children or diabetics appears to provide more information than creatinine. However, serum cystatin C can be influenced by non-renal factors. Currently, there is not enough scientific evidence to recommend the use of cystatin C to assess renal function instead of creatinine and creatinine equations (AU)