Frailty as a Predictor of Surgical Outcomes Following Femoral Hernia Repair.

BACKGROUND: Femoral hernias are associated with significant morbidity and mortality due to risk of strangulation. Frailty has shown to be strongly associated with adverse outcomes. A modified five-factor frailty index (mFI-5) is a simple validated predictor of postoperative complications and mortality within the ACS-NSQIP® database. This study aims to evaluate the impact of frailty and age on 30-day outcomes after femoral hernia repair. METHODS: Patients who underwent femoral hernia repair were queried using the ACS-NSQIP database (2017) and divided into two groups based on frailty score (FS): Frail (FS = 1-5) and Non-frail (FS = 0). We evaluated the association between postoperative outcomes and frailty, age, sex, presentation, ASA class, timing of surgery, and surgical approaches. Univariate analysis followed by a multivariable logistic regression model was performed to evaluate postoperative morbidity. RESULTS: Of a total of 1,295 patients, 540 (42.7%) were in the Frail group. No differences in sex and race proportions were observed between groups. The Frail group had a higher rate of serious morbidity (4.4% vs 1.9%, P < .001), overall morbidity (7.8% vs 3.4%, P < .010), readmission rate (5.4% vs 2.3%, P = .003), and median (IQR) hospital length of stay (1 [0, 4] vs 0 [0, 1] days, P < .001). In multivariable analysis, male sex, presentation with complication, emergency surgery, and FS were associated with increased odds of overall morbidity. All deaths were in the Frail group. CONCLUSION(S): Frailty, male sex, presentation with obstruction/strangulation, and emergency surgery are independent predictors of increased 30-day morbidity. Thirty-day mortality was noted in the Frail group.

Bridging the phenotypic and genetic data useful for integrated breeding through a data annotation using the Crop Ontology developed by the crop communities of practice.

The Crop Ontology (CO) of the Generation Challenge Program (GCP) (http://cropontology.org/) is developed for the Integrated Breeding Platform (IBP) (http://www.integratedbreeding.net/) by several centers of The Consultative Group on International Agricultural Research (CGIAR): bioversity, CIMMYT, CIP, ICRISAT, IITA, and IRRI. Integrated breeding necessitates that breeders access genotypic and phenotypic data related to a given trait. The CO provides validated trait names used by the crop communities of practice (CoP) for harmonizing the annotation of phenotypic and genotypic data and thus supporting data accessibility and discovery through web queries. The trait information is completed by the description of the measurement methods and scales, and images. The trait dictionaries used to produce the Integrated Breeding (IB) fieldbooks are synchronized with the CO terms for an automatic annotation of the phenotypic data measured in the field. The IB fieldbook provides breeders with direct access to the CO to get additional descriptive information on the traits. Ontologies and trait dictionaries are online for cassava, chickpea, common bean, groundnut, maize, Musa, potato, rice, sorghum, and wheat. Online curation and annotation tools facilitate (http://cropontology.org) direct maintenance of the trait information and production of trait dictionaries by the crop communities. An important feature is the cross referencing of CO terms with the Crop database trait ID and with their synonyms in Plant Ontology (PO) and Trait Ontology (TO). Web links between cross referenced terms in CO provide online access to data annotated with similar ontological terms, particularly the genetic data in Gramene (University of Cornell) or the evaluation and climatic data in the Global Repository of evaluation trials of the Climate Change, Agriculture and Food Security programme (CCAFS). Cross-referencing and annotation will be further applied in the IBP.

Multifunctional crop trait ontology for breeders' data: field book, annotation, data discovery and semantic enrichment of the literature.

BACKGROUND AND AIMS: Agricultural crop databases maintained in gene banks of the Consultative Group on International Agricultural Research (CGIAR) are valuable sources of information for breeders. These databases provide comparative phenotypic and genotypic information that can help elucidate functional aspects of plant and agricultural biology. To facilitate data sharing within and between these databases and the retrieval of information, the crop ontology (CO) database was designed to provide controlled vocabulary sets for several economically important plant species. METHODOLOGY: Existing public ontologies and equivalent catalogues of concepts covering the range of crop science information and descriptors for crops and crop-related traits were collected from breeders, physiologists, agronomists, and researchers in the CGIAR consortium. For each crop, relationships between terms were identified and crop-specific trait ontologies were constructed following the Open Biomedical Ontologies (OBO) format standard using the OBO-Edit tool. All terms within an ontology were assigned a globally unique CO term identifier. PRINCIPAL RESULTS: The CO currently comprises crop-specific traits for chickpea (Cicer arietinum), maize (Zea mays), potato (Solanum tuberosum), rice (Oryza sativa), sorghum (Sorghum spp.) and wheat (Triticum spp.). Several plant-structure and anatomy-related terms for banana (Musa spp.), wheat and maize are also included. In addition, multi-crop passport terms are included as controlled vocabularies for sharing information on germplasm. Two web-based online resources were built to make these COs available to the scientific community: the 'CO Lookup Service' for browsing the CO; and the 'Crops Terminizer', an ontology text mark-up tool. CONCLUSIONS: The controlled vocabularies of the CO are being used to curate several CGIAR centres' agronomic databases. The use of ontology terms to describe agronomic phenotypes and the accurate mapping of these descriptions into databases will be important steps in comparative phenotypic and genotypic studies across species and gene-discovery experiments.

International crop information system for germplasm data management.

Passport and phenotypic data on germplasm and breeding lines are available from worldwide sources in various electronic formats. These data can be collated into a single database format to enable strategic interrogation to make the best use of data for effective germplasm use and enhancement. The International Crop Information System (http://www.icis.cgiar.org) is an open-source project under development by a global community of crop researchers and includes applications designed to achieve the storage and interrogation of pedigree and phenotypic data.

Generation Challenge Programme (GCP): standards for crop data.

The Generation Challenge Programme (GCP) is an international research consortium striving to apply molecular biological advances to crop improvement for developing countries. Central to its activities is the creation of a next generation global crop information platform and network to share genetic resources, genomics, and crop improvement information. This system is being designed based on a comprehensive scientific domain object model and associated shared ontology. This model covers germplasm, genotype, phenotype, functional genomics, and geographical information data types needed in GCP research. This paper provides an overview of this modeling effort.