[Diagnostic accuracy of a hysteroscopic score for the detection of endometrial cancer in patients with postmenopausal bleeding and endometrial thickening].

OBJECTIVE: To assess the diagnostic accuracy of hysteroscopic scores in endometrial cancer. METHODS: Diagnostic accuracy study assembled within a cross-sectional study that included patients with postmenopausal bleeding and endometrial thickening greater than 5 mm in whom hysteroscopy was performed and then compared with endometrial biopsy as the diagnostic gold standard, in two high complexity hospitals. Clinical, sociodemographic variables, as well as hysteroscopic scores and the results of endometrial tissue histopathology were measured. Sensitivity and specificity, likelihood ratios and area under the curve with their respective confidence intervals were estimated in the analysis. RESULTS: With a 9 % prevalence of endometrial cancer, the hysteroscopic assessment system was shown to have 75 % sensitivity (95 % CI; 30.1- 95.43), 95,1 % specificity (95 % CI; 83.9-98.7), a positive likelihood ratio of 15.38 (95 %; CI 3.55- 66.56), a negative likelihood ratio of 0.26 and area under the curve of 85 %. CONCLUSIONS: The standardized hysteroscopic assessment system was found to have an acceptable sensitivity for screening in patients with postmenopausal bleeding and endometrial thickening (≥ 5 mm). Further studies with larger sample sizes are required in order to arrive at a more precise estimation of the operational characteristics of the hysteroscopic assessment system for the detection of endometrial cancer.

TITULO: EXACTITUD DIAGNÓSTICA DE UNA ESCALA HISTEROSCÓPICA PARA LA DETECCIÓN DE CÁNCER ENDOMETRIAL EN PACIENTES CON SANGRADO POSMENOPÁUSICO Y ENGROSAMIENTO ENDOMETRIAL. OBJETIVO: Evaluar la exactitud diagnóstica del sistema de puntaje histeroscópico de cáncer endometrial. METODOS: Estudio de exactitud diagnóstica ensamblado en estudio transversal, que incluyó pacientes con sangrado posmenopáusico y engrosamiento endometrial mayor o igual a 5 mm, a quienes se practicó histeroscopia, cuyo resultado se comparó con la biopsia endometrial como patrón de oro diagnóstico, en dos hospitales de alta complejidad. Se midieron variables sociodemográficas, clínicas, puntaje de evaluación histeroscópica y resultado histopatológico de tejido endometrial. En el análisis se estimó sensibilidad, especificidad, razones de probabilidades y área bajo la curva con sus respectivos intervalos de confianza. RESULTADOS: Con una prevalencia del cáncer endometrial del 9 %, el sistema de evaluación por histeroscopia mostró una sensibilidad de 75 % (IC 95 %: 30,1-95,43), especificidad de 95,1 % (IC 95 %: 83,9- 98,7), una razón de probabilidades positiva de 15,38 (IC 95 %: 3,55-66,56), una razón de probabilidades negativa de 0,26 y un área bajo la curva del 85 %. CONCLUSIONES: el sistema de evaluación endometrial histeroscópico estandarizado mostró una sensibilidad aceptable para hacer la tamización en pacientes con sangrado posmenopáusico y engrosamiento endometrial (≥ 5 mm). Se requiere la realización de estudios con un mayor tamaño muestral que permitan hacer una estimación más precisa de las características operativas de este sistema de evaluación histeroscópico para la detección de cáncer endometrial.

Diagnostic accuracy of a hysteroscopic score for the detection of endometrial cancer in patients with postmenopausal bleeding and endometrial thickening / Exactitud diagnóstica de una escala histeroscópica para la detección de cáncer endometrial en pacientes con sangrado posmenopáusico y engrosamiento endometrial

RESUMEN Objetivo: evaluar la exactitud diagnóstica del sistema de puntaje histeroscópico de cáncer endometrial. Materiales y métodos: estudio de exactitud diagnóstica ensamblado en estudio transversal, que incluyó pacientes con sangrado posmenopáusico y engrosamiento endometrial mayor o igual a 5 mm, a quienes se practicó histeroscopia, cuyo resultado se comparó con la biopsia endometrial como patrón de oro diagnóstico, en dos hospitales de alta complejidad. Se midieron variables sociodemográficas, clínicas, puntaje de evaluación histeroscópica y resultado histopatológico de tejido endometrial. En el análisis se estimó sensibilidad, especificidad, razones de probabilidades y área bajo la curva con sus respectivos intervalos de confianza. Resultados: con una prevalencia del cáncer endometrial del 9 %, el sistema de evaluación por histeroscopia mostró una sensibilidad de 75 % (IC 95 %: 30,1-95,43), especificidad de 95,1 % (IC 95 %: 83,9- 98,7), una razón de probabilidades positiva de 15,38 (IC 95 %: 3,55-66,56), una razón de probabilidades negativa de 0,26 y un área bajo la curva del 85 %. Conclusión: el sistema de evaluación endometrial histeroscópico estandarizado mostró una sensibilidad aceptable para hacer la tamización en pacientes con sangrado posmenopáusico y engrosamiento endometrial (≥ 5 mm). Se requiere la realización de estudios con un mayor tamaño muestral que permitan hacer una estimación más precisa de las características operativas de este sistema de evaluación histeroscópico para la detección de cáncer endometrial.

ABSTRACT Objective: To assess the diagnostic accuracy of hysteroscopic scores in endometrial cancer. Materials and methods: Diagnostic accuracy study assembled within a cross-sectional study that included patients with postmenopausal bleeding and endometrial thickening greater than 5 mm in whom hysteroscopy was performed and then compared with endometrial biopsy as the diagnostic gold standard, in two high complexity hospitals. Clinical, sociodemographic variables, as well as hysteroscopic scores and the results of endometrial tissue histopathology were measured. Sensitivity and specificity, likelihood ratios and area under the curve with their respective confidence intervals were estimated in the analysis. Results: With a 9 % prevalence of endometrial cancer, the hysteroscopic assessment system was shown to have 75 % sensitivity (95 % CI; 30.1- 95.43), 95,1 % specificity (95 % CI; 83.9-98.7), a positive likelihood ratio of 15.38 (95 %; CI 3.55- 66.56), a negative likelihood ratio of 0.26 and area under the curve of 85 %. Conclusion: The standardized hysteroscopic assessment system was found to have an acceptable sensitivity for screening in patients with postmenopausal bleeding and endometrial thickening (≥ 5 mm). Further studies with larger sample sizes are required in order to arrive at a more precise estimation of the operational characteristics of the hysteroscopic assessment system for the detection of endometrial cancer.

Experiencia de pacientes sometidas a histerectomía laparoscópica en el Hospital Universitario San José de Popayán entre 2014 y 2018 / Experience of patients who underwent laparoscopic hysterectomy between 2014 and 2018 at the Hospital Universitario San José in Popayán, Colombia

Resumen Introducción. La histerectomía es un procedimiento común en la práctica ginecológica para el manejo de condiciones benignas y malignas. En la actualidad, se ha demostrado que el abordaje mínimamente invasivo es mejor que la cirugía abierta, ya que presenta menos complicaciones intraoperatorias y posoperatorias. Objetivo. Describir la experiencia de pacientes sometidas a histerectomía laparoscópica entre 2014 y 2018 en el Hospital Universitario San José de Popayán Empresa Social del Estado. Materiales y métodos. Estudio observacional descriptivo de serie de casos que incluyó 36 pacientes intervenidas entre enero de 2014 y abril de 2018. Se evaluaron variables socio-demográficas y clínicas. Para medir el grado de satisfacción posoperatoria y la calidad de vida se realizó una encuesta telefónica. Resultados. La edad promedio de las entrevistadas fue 45 años, el tiempo quirúrgico promedio fue 124 minutos, la tasa de complicaciones intraoperatorias fue 2.78% (n = 1) y la estancia hospitalaria promedio fue 1.3 días. Los principales diagnósticos preoperatorios fueron carcinoma in situ (28%) y leiomiomatosis (17%). En cuanto al grado de satisfacción, el 92% refirió mejoría en la calidad de vida y el 64% manifestó tener una recuperación posoperatoria rápida. Conclusión. Para la población estudiada, la histerectomía laparoscópica fue un procedimiento seguro con una baja tasa de complicaciones y un alto grado de satisfacción posoperatoria.

Abstract Introduction: Hysterectomy is a common procedure used in gynecological practice for the management of benign and malignant conditions. Currently, it has been proved that the minimally invasive surgery approach is better than the open surgery approach, since it implies fewer intraoperative and postoperative complications. Objective: To describe the experience of women who underwent laparoscopic hysterectomy between 2014 and 2018 at Hospital Universitario San José de Popayan Empresa Social del Estado (San José de Popayán University Hospital - State-owned Healthcare Institution). Materials and methods: Descriptive observational case series study. The study population consisted of 36 women who underwent laparoscopic hysterectomy between January 2014 and April 2018. The patients' sociodemographic and clinical variables were evaluated and a telephone survey was conducted in order to measure their postoperative level of satisfaction and their quality of life. Results: Participants' average age was 45 years, average surgical time was 124 minutes, intraoperative complications rate was 2.78% (n = 1), and average hospital stay was 1.3 days. Main diagnoses prior to surgery were carcinoma in situ (28%) and leiomyomatosis (17%). Regarding their level of satisfaction, 92% reported their quality of life improved after the surgical procedure and 64% stated their postoperative recovery was fast. Conclusion: Laparoscopic hysterectomy, in the case of the study population, was a safe surgical procedure with a low rate of complications and a high level of postoperative satisfaction.

Cross-lingual semantic annotation of biomedical literature: experiments in Spanish and English.

MOTIVATION: Biomedical literature is one of the most relevant sources of information for knowledge mining in the field of Bioinformatics. In spite of English being the most widely addressed language in the field; in recent years, there has been a growing interest from the natural language processing community in dealing with languages other than English. However, the availability of language resources and tools for appropriate treatment of non-English texts is lacking behind. Our research is concerned with the semantic annotation of biomedical texts in the Spanish language, which can be considered an under-resourced language where biomedical text processing is concerned. RESULTS: We have carried out experiments to assess the effectiveness of several methods for the automatic annotation of biomedical texts in Spanish. One approach is based on the linguistic analysis of Spanish texts and their annotation using an information retrieval and concept disambiguation approach. A second method takes advantage of a Spanish-English machine translation process to annotate English documents and transfer annotations back to Spanish. A third method takes advantage of the combination of both procedures. Our evaluation shows that a combined system has competitive advantages over the two individual procedures. AVAILABILITY AND IMPLEMENTATION: UMLSMapper (https://snlt.vicomtech.org/umlsmapper) and the annotation transfer tool (http://scientmin.taln.upf.edu/anntransfer/) are freely available for research purposes as web services and/or demos. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Short- and long-term outcomes of arterial reconstruction on recipient splenic artery in adult liver transplantation. Single-center prospective study 25 years after first description.

Several techniques have been proposed for liver transplantation with inadequate hepatic artery (HA) anastomosis. We aimed to analyze outcomes of arterial reconstruction with the splenic artery (SA). This was a prospective study of our experience with recipients who underwent arterial anastomosis on the SA compared with patients who underwent standard HA. We included 54 patients in the SA group and 1405 in the HA group. Patients in SA group were more frequently retransplantation (31% vs. 8%; P = 0.001), required more transfusion (11 ± 12 vs. 6 ± 9.9 PRC; P = 0.001), had longer surgeries (424 ± 95 vs. 394 ± 102 min; P = 0.03), and longer hospital stays (28 ± 29 vs. 20 ± 18 days; P = 0.002). There were no differences in vascular and biliary complications (15% and 7%; P = 0.18; and 32% and 23%; P = 0.32), primary dysfunction (11% and 9%; P = 0.74), reoperation (12% and 10%; P = 0.61), postoperative mortality (13% and 7%; P = 0.12) and 5 years survival (66% vs. 63%; P = 0.71). Following primary transplantation, there were no differences. The outcomes of arterial reconstruction using the recipients' SA in adult liver transplantation are comparable to those for standard HA reconstruction after a first transplant.

comoRbidity: an R package for the systematic analysis of disease comorbidities.

Motivation: The study of comorbidities is a major priority due to their impact on life expectancy, quality of life and healthcare cost. The availability of electronic health records (EHRs) for data mining offers the opportunity to discover disease associations and comorbidity patterns from the clinical history of patients gathered during routine medical care. This opens the need for analytical tools for detection of disease comorbidities, including the investigation of their underlying genetic basis. Results: We present comoRbidity, an R package aimed at providing a systematic and comprehensive analysis of disease comorbidities from both the clinical and molecular perspectives. comoRbidity leverages from (i) user provided clinical data from EHR databases (the clinical comorbidity analysis) and (ii) genotype-phenotype information of the diseases under study (the molecular comorbidity analysis) for a comprehensive analysis of disease comorbidities. The clinical comorbidity analysis enables identifying significant disease comorbidities from clinical data, including sex and age stratification and temporal directionality analyses, while the molecular comorbidity analysis supports the generation of hypothesis on the underlying mechanisms of the disease comorbidities by exploring shared genes among disorders. The open-source comoRbidity package is a software tool aimed at expediting the integrative analysis of disease comorbidities by incorporating several analytical and visualization functions. Availability and implementation: https://bitbucket.org/ibi_group/comorbidity. Supplementary information: Supplementary data are available at Bioinformatics online.

Identifying temporal patterns in patient disease trajectories using dynamic time warping: A population-based study.

Time is a crucial parameter in the assessment of comorbidities in population-based studies, as it permits to identify more complex disease patterns apart from the pairwise disease associations. So far, it has been, either, completely ignored or only, taken into account by assessing the temporal directionality of identified comorbidity pairs. In this work, a novel time-analysis framework is presented for large-scale comorbidity studies. The disease-history vectors of patients of a regional Spanish health dataset are represented as time sequences of ordered disease diagnoses. Statistically significant pairwise disease associations are identified and their temporal directionality is assessed. Subsequently, an unsupervised clustering algorithm, based on Dynamic Time Warping, is applied on the common disease trajectories in order to group them according to the temporal patterns that they share. The proposed methodology for the temporal assessment of such trajectories could serve as the preliminary basis of a disease prediction system.

Text mining and expert curation to develop a database on psychiatric diseases and their genes.

Database URL: http://www.psygenet.org. PsyGeNET corpus: http://www.psygenet.org/ds/PsyGeNET/results/psygenetCorpus.tar.

Sexual Desire Among an Online Sample of Men Sexually Attracted to Children.

Sexual attraction to children occurs in roughly 3 to 9 percent of the population. However, most knowledge about such desires comes from forensic samples, and most studies fail to assess preferred sexual activity and sexual partner. A new multimodal assessment of sexual desire was used to investigate interest in consensual and nonconsensual sex with adults and children in an online sample of men sexually attracted to children (n = 101). Desires were compared across history of sex offending behavior and preferred gender of child victim. Men who have and have not acted on their sexual attractions to children reported similar levels of sexual desire. Men primarily attracted to girls reported greater desire for sex with adults than did men primarily attracted to boys. Results highlight the heterogeneity of men sexually attracted to children as well as possible distinctions across gender of children to whom they are primarily attracted.

DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants.

The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype-phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.

Combining machine learning, crowdsourcing and expert knowledge to detect chemical-induced diseases in text.

Drug toxicity is a major concern for both regulatory agencies and the pharmaceutical industry. In this context, text-mining methods for the identification of drug side effects from free text are key for the development of up-to-date knowledge sources on drug adverse reactions. We present a new system for identification of drug side effects from the literature that combines three approaches: machine learning, rule- and knowledge-based approaches. This system has been developed to address the Task 3.B of Biocreative V challenge (BC5) dealing with Chemical-induced Disease (CID) relations. The first two approaches focus on identifying relations at the sentence-level, while the knowledge-based approach is applied both at sentence and abstract levels. The machine learning method is based on the BeFree system using two corpora as training data: the annotated data provided by the CID task organizers and a new CID corpus developed by crowdsourcing. Different combinations of results from the three strategies were selected for each run of the challenge. In the final evaluation setting, the system achieved the highest Recall of the challenge (63%). By performing an error analysis, we identified the main causes of misclassifications and areas for improving of our system, and highlighted the need of consistent gold standard data sets for advancing the state of the art in text mining of drug side effects.Database URL: https://zenodo.org/record/29887?ln»en#.VsL3yDLWR_V.

DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases.

MOTIVATION: DisGeNET-RDF makes available knowledge on the genetic basis of human diseases in the Semantic Web. Gene-disease associations (GDAs) and their provenance metadata are published as human-readable and machine-processable web resources. The information on GDAs included in DisGeNET-RDF is interlinked to other biomedical databases to support the development of bioinformatics approaches for translational research through evidence-based exploitation of a rich and fully interconnected linked open data. AVAILABILITY AND IMPLEMENTATION: http://rdf.disgenet.org/ CONTACT: support@disgenet.org.

A crowdsourcing workflow for extracting chemical-induced disease relations from free text.

Relations between chemicals and diseases are one of the most queried biomedical interactions. Although expert manual curation is the standard method for extracting these relations from the literature, it is expensive and impractical to apply to large numbers of documents, and therefore alternative methods are required. We describe here a crowdsourcing workflow for extracting chemical-induced disease relations from free text as part of the BioCreative V Chemical Disease Relation challenge. Five non-expert workers on the CrowdFlower platform were shown each potential chemical-induced disease relation highlighted in the original source text and asked to make binary judgments about whether the text supported the relation. Worker responses were aggregated through voting, and relations receiving four or more votes were predicted as true. On the official evaluation dataset of 500 PubMed abstracts, the crowd attained a 0.505F-score (0.475 precision, 0.540 recall), with a maximum theoretical recall of 0.751 due to errors with named entity recognition. The total crowdsourcing cost was $1290.67 ($2.58 per abstract) and took a total of 7 h. A qualitative error analysis revealed that 46.66% of sampled errors were due to task limitations and gold standard errors, indicating that performance can still be improved. All code and results are publicly available athttps://github.com/SuLab/crowd_cid_relexDatabase URL:https://github.com/SuLab/crowd_cid_relex.

PsyGeNET: a knowledge platform on psychiatric disorders and their genes.

UNLABELLED: PsyGeNET (Psychiatric disorders and Genes association NETwork) is a knowledge platform for the exploratory analysis of psychiatric diseases and their associated genes. PsyGeNET is composed of a database and a web interface supporting data search, visualization, filtering and sharing. PsyGeNET integrates information from DisGeNET and data extracted from the literature by text mining, which has been curated by domain experts. It currently contains 2642 associations between 1271 genes and 37 psychiatric disease concepts. In its first release, PsyGeNET is focused on three psychiatric disorders: major depression, alcohol and cocaine use disorders. PsyGeNET represents a comprehensive, open access resource for the analysis of the molecular mechanisms underpinning psychiatric disorders and their comorbidities. AVAILABILITY AND IMPLEMENTATION: The PysGeNET platform is freely available at http://www.psygenet.org/. The PsyGeNET database is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). CONTACT: lfurlong@imim.es SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Exploring brand-name drug mentions on Twitter for pharmacovigilance.

Twitter has been proposed by several studies as a means to track public health trends such as influenza and Ebola outbreaks by analyzing user messages in order to measure different population features and interests. In this work we analyze the number and features of mentions on Twitter of drug brand names in order to explore the potential usefulness of the automated detection of drug side effects and drug-drug interactions on social media platforms such as Twitter. This information can be used for the development of predictive models for drug toxicity, drug-drug interactions or drug resistance. Taking into account the large number of drug brand mentions that we found on Twitter, it is promising as a tool for the detection, understanding and monitoring the way people manage prescribed drugs.

Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research.

BACKGROUND: Current biomedical research needs to leverage and exploit the large amount of information reported in scientific publications. Automated text mining approaches, in particular those aimed at finding relationships between entities, are key for identification of actionable knowledge from free text repositories. We present the BeFree system aimed at identifying relationships between biomedical entities with a special focus on genes and their associated diseases. RESULTS: By exploiting morpho-syntactic information of the text, BeFree is able to identify gene-disease, drug-disease and drug-target associations with state-of-the-art performance. The application of BeFree to real-case scenarios shows its effectiveness in extracting information relevant for translational research. We show the value of the gene-disease associations extracted by BeFree through a number of analyses and integration with other data sources. BeFree succeeds in identifying genes associated to a major cause of morbidity worldwide, depression, which are not present in other public resources. Moreover, large-scale extraction and analysis of gene-disease associations, and integration with current biomedical knowledge, provided interesting insights on the kind of information that can be found in the literature, and raised challenges regarding data prioritization and curation. We found that only a small proportion of the gene-disease associations discovered by using BeFree is collected in expert-curated databases. Thus, there is a pressing need to find alternative strategies to manual curation, in order to review, prioritize and curate text-mining data and incorporate it into domain-specific databases. We present our strategy for data prioritization and discuss its implications for supporting biomedical research and applications. CONCLUSIONS: BeFree is a novel text mining system that performs competitively for the identification of gene-disease, drug-disease and drug-target associations. Our analyses show that mining only a small fraction of MEDLINE results in a large dataset of gene-disease associations, and only a small proportion of this dataset is actually recorded in curated resources (2%), raising several issues on data prioritization and curation. We propose that joint analysis of text mined data with data curated by experts appears as a suitable approach to both assess data quality and highlight novel and interesting information.

DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes.

DisGeNET is a comprehensive discovery platform designed to address a variety of questions concerning the genetic underpinning of human diseases. DisGeNET contains over 380,000 associations between >16,000 genes and 13,000 diseases, which makes it one of the largest repositories currently available of its kind. DisGeNET integrates expert-curated databases with text-mined data, covers information on Mendelian and complex diseases, and includes data from animal disease models. It features a score based on the supporting evidence to prioritize gene-disease associations. It is an open access resource available through a web interface, a Cytoscape plugin and as a Semantic Web resource. The web interface supports user-friendly data exploration and navigation. DisGeNET data can also be analysed via the DisGeNET Cytoscape plugin, and enriched with the annotations of other plugins of this popular network analysis software suite. Finally, the information contained in DisGeNET can be expanded and complemented using Semantic Web technologies and linked to a variety of resources already present in the Linked Data cloud. Hence, DisGeNET offers one of the most comprehensive collections of human gene-disease associations and a valuable set of tools for investigating the molecular mechanisms underlying diseases of genetic origin, designed to fulfill the needs of different user profiles, including bioinformaticians, biologists and health-care practitioners. Database URL: http://www.disgenet.org/

Anatomical relations of anterior and posterior ankle arthroscopy portals: a cadaveric study.

BACKGROUND: Ankle arthroscopy is an increasingly used technique. Knowledge of the anatomical structures in relation to its portals is paramount to avoid complications. METHODS: Twenty cadaveric ankles were analysed to assess the distance between relevant neurovascular structures to the anteromedial, anterolateral, posteromedial, and posterolateral arthroscopy portals. RESULTS: The intermediate dorsal branch of the superficial peroneal nerve was the closest structure to any of the portals (4.8 mm from the anterolateral portal), followed by the posterior tibial nerve (7.3 mm from the posteromedial portal). All structures analysed but one (posterior tibial artery) were, at least in one specimen, <5 mm distant from one of the portals. DISCUSSION: This study provides information on the anatomical relations of ankle arthroscopy portals and relevant neurovascular structures, confirming previous studies identifying the superficial peroneal nerve as the structure at highest risk of injury, but also highlighting some important variations. Techniques to minimise the injury to these structures are discussed.