ABSTRACT
Background: Pathology reports are stored as unstructured, ungrammatical, fragmented, and abbreviated free text with linguistic variability among pathologists. For this reason, tumor information extraction requires a significant human effort. Recording data in an efficient and high-quality format is essential in implementing and establishing a hospital-based-cancer registry Objective: This study aimed to describe implementing a natural language processing algorithm for oncology pathology reports. Methods: An algorithm was developed to process oncology pathology reports in Spanish to extract 20 medical descriptors. The approach is based on the successive coincidence of regular expressions. Results: The validation was performed with 140 pathological reports. The topography identification was performed manually by humans and the algorithm in all reports. The human identified morphology in 138 reports and by the algorithm in 137. The average fuzzy matching score was 68.3 for Topography and 89.5 for Morphology. Conclusions: A preliminary algorithm validation against human extraction was performed over a small set of reports with satisfactory results. This shows that a regular-expression approach can accurately and precisely extract multiple specimen attributes from free-text Spanish pathology reports. Additionally, we developed a website to facilitate collaborative validation at a larger scale which may be helpful for future research on the subject.
Introducción: Los reportes de patología están almacenados como texto libre sin estructura, gramática, fragmentados o abreviados, con variabilidad lingüística entre patólogos. Por esta razón, la extracción de información de tumores requiere un esfuerzo humano significativo. Almacenar información en un formato eficiente y de alta calidad es esencial para implementar y establecer un registro hospitalario de cáncer. Objetivo: Este estudio busca describir la implementación de un algoritmo de Procesamiento de Lenguaje Natural para reportes de patología oncológica. Métodos: Desarrollamos un algoritmo para procesar reportes de patología oncológica en Español, con el objetivo de extraer 20 descriptores médicos. El abordaje se basa en la coincidencia sucesiva de expresiones regulares. Resultados: La validación se hizo con 140 reportes de patología. La identificación topográfica se realizó por humanos y por el algoritmo en todos los reportes. La morfología fue identificada por humanos en 138 reportes y por el algoritmo en 137. El valor de coincidencias parciales (fuzzy matches) promedio fue de 68.3 para Topografía y 89.5 para Morfología. Conclusiones: Se hizo una validación preliminar del algoritmo contra extracción humana sobre un pequeño grupo de reportes, con resultados satisfactorios. Esto muestra que múltiples atributos del espécimen pueden ser extraídos de manera precisa de texto libre de reportes de patología en Español, usando un abordaje de expresiones regulares. Adicionalmente, desarrollamos una página web para facilitar la validación colaborativa a gran escala, lo que puede ser beneficioso para futuras investigaciones en el tema.
ABSTRACT
Resumen Introducción y objetivo: La infección por coronavirus (COVID-19) en pacientes intervenidos es causa de importante mortalidad posoperatoria, aunque su incidencia es variable. El objetivo primario fue evaluar la incidencia de COVID-19 en los pacientes intervenidos en nuestro Servicio de Cirugía General y Digestiva, durante el máximo impacto de la pandemia en España. El objetivo secundario fue evaluar la mortalidad perioperatoria y determinar los factores de riesgo para la infección por COVID-19. Materiales y Método: Estudio observacional retrospectivo de pacientes consecutivos sometidos a Cirugía General y Digestiva con ingreso superior a 24 h, del 1 de febrero de 2020 al 30 de abril de 2020 en un hospital terciario de Madrid, España. Resultados: Se analizaron 441 pacientes: 423 sin COVID-19 y 18 con COVID-19. Las características preoperatorias y operatorias fueron similares para ambos grupos, salvo por el grado ASA (American Society of Anesthesiologists). La incidencia de COVID-19 en los pacientes intervenidos fue del 4,1%. La mortalidad posoperatoria fue elevada, del 22,2% en pacientes con COVID-19, frente a un 2,8% en pacientes no COVID-19 (p: 0,003). Los factores de riesgo para la infección por COVID-19 en los pacientes intervenidos fueron una estancia hospitalaria prolongada (OR: 1,035 [95% CI: 1,007-1,065]) y la reintervención quirúrgica (OR: 5,025 [95% CI: 1,650-15,311]). Conclusión: Las intervenciones durante la pandemia de COVID-19 causaron una baja tasa de infección con elevada mortalidad posoperatoria. La intervención quirúrgica debe valorarse frente al riesgo adicional para el paciente en contextos de alta transmisión.
The impact of coronavirus disease (COVID-19) in intervened patients seems to cause large postoperative mortality, although its incidence varies among centres. Primary aim was to evaluate the incidence of COVID-19 on the patients intervened in our General and Digestive Surgery Department, during the maximum impact of the pandemia in Spain. Secondary outcomes were evaluating perioperative mortality, and determining the risk factors for COVID-19 infection. Materials and Method: Retrospective single centre study of consecutive patients undergoing general and gastrointestinal surgical procedures with more than 24 hours of inhospital stay, from February 1, 2020 to April 30, 2020 in a tertiary referral centre in Madrid, Spain. Results: A total of 441 patients were analysed: 423 were non-COVID-19 patients while 18 of them had COVID-19. Preoperative and operative characteristics were similar for both groups, unless for the American Society of Anesthesiologists grade. The incidence of COVID-19 in our intervened patients was 4.1%. Postoperative mortality was high among surgical patients with COVID-19, with a mortality rate of 22.2% compared to a 2.8% in non COVID-19 patients. The risk factors for COVID-19 infection were a prolonged postoperative stay (OR: 1.035 [95% CI: 1.007-1.065]) and the need of a reintervention (OR: 5.025 [95% CI: 1.650-15.311]). Conclusion: Surgical interventions during the COVID-19 pandemia resulted in a low infection rate but a high postoperative COVID-19 mortality. The decision to intervene must be carefully balanced against the additional risk for patients in a high transmission setting.
Subject(s)
Humans , Male , Female , Middle Aged , Aged , Surgical Procedures, Operative/adverse effects , COVID-19/mortality , Surgical Procedures, Operative/methods , Risk Factors , Perioperative PeriodABSTRACT
Two isolations of fungi from a bank of microorganisms in the Biological Sciences Laboratory at Escuela Superior Politécnica de Chimborazo were tested on the galling caused by Meloidogyne incognita in tomato seedlings grown in pots with substrate infested with a suspension of nematodes, with approximately 2000 juvenile stages (J2) from root galls of plants infested with M. incognita, taken from the Nematology laboratory of the Ecuadorian Agricultural Quality Assurance Agency (AGROCALIDAD). Pleurotus ostreatus was a fungus with nematicidal characteristics through production of toxins; while Trichoderma harzianum is a widely known fungus, although it is a plant growth promoter rather than a nematicide. The two fungi were formulated in wheat straw and rabbit manure. A complete randomized design (CRD) with three replications was used, with a chemical control (Fenamiphos) and an absolute control. Five grams of each formulation was applied per plant before the transplant. The number of galls in the roots, plant height, stem diameter, number of leaves and fresh and dry weight of the aerial part and roots of 180 tomato plants grown in greenhouse were evaluated at 60 days after transplant. The results showed that the two fungi reduced the number of galls and made it possible to obtain dry weights of the aerial and radicular part very close to the chemical control (10.09 and 3.39 g) with 8.68; 8.04; 2.96 and 3.25 g respectively. Besides Trichoderma harzianum proved to be a good promoter of root growth, therefore, the use of these bioformulates is a promising measure for the control of this phytonematode