Nursing Professionals And Occupational Accidents

The current study has the objective to identify main work accidents that occurs with nursing workers. This is an integrative literature review that enabled to include scientific articles indexed in the databases of Virtual Library in Health (BVS). Searches were made from october to november 2016, using the descriptors: “work accidents”, “nursing professionals”, separated between themselves by the boolean operator AND. The following criteria were adopted: fully available articles, in portuguese language, published in the last five years. Articles that presented some duplicity and didn’t meet the proposed study objectives were excluded. After searches, ten scientific productions about the subject were selected. Results indicate the occurrence of accidents between nursing professionals and the main factors were related with sharp object handling, non-utilization of IPEs, excessive workload and needle resurfacing. It is concluded that strategies are required to minimize these occurrences, as the adoption of standard precautionary measures, the adequacy of staff numbers and better work conditions to this professional category. Besides that, the need of new researches about this subject are emphasized

Incorporating the Local Biological Effect of Dose Per Fraction in IMRT Inverse Optimization

In intensity modulated radiation therapy (IMRT), the dose in each voxel of the organs at risk (OAR) can be strongly reduced compared to conformal radiation therapy (RT). Due to the sensitivity of late side-effects to fraction size, a smaller dose per fraction in the normal tissues represent an increased tolerance to RT. This expected reduction in biological effect may then be used as an additional degree of freedom during IMRT optimization. In this study, the comparison between plans optimized with and without a voxel-based fractionation correction was made

Beam angle optimization in IMRT: are we really optimizing what matters?

Intensity-modulated radiation therapy (IMRT) is a modern radiotherapy modality that uses a multileaf collimator to enable the irradiation of the patient with non-uniform maps of radiation from a set of distinct beam irradiation directions. The aim of IMRT is to eradicate all cancerous cells by irradiating the tumor with a prescribed dose while simultaneously sparing, as much as possible, the neighboring tissues and organs. The optimal choice of beam irradiation directions – beam angle optimization (BAO) – can play an important role in IMRT treatment planning by improving organ sparing and tumor coverage, increasing the treatment plan quality. Typically, the BAO search is guided by the optimal value of the fluence map optimization (FMO) – the problem of obtaining the most appropriate radiation intensities for each beam direction. In this paper, a new score to guide the BAO search is introduced and embedded in a parallel multistart derivative-free optimization framework that is detailed for the extremely challenging continuous multi-modal BAO problem. For the set of ten clinical nasopharyngeal tumor cases considered, treatment plans obtained for optimized beam directions clearly outperform the benchmark treatment plans obtained considering equidistant beam directions typically used in clinical practice. Furthermore, treatment plans obtained considering the proposed score clearly improve the quality of the plans resulting from the use of the optimal value of the FMO problem to guide the BAO search

Comparison of two beam angular optimization algorithms guided by automated multicriterial IMRT

To compare two beam angle optimization (BAO) algorithms for coplanar and non-coplanar geometries in a multicriterial optimization framework

Clinical validation of a graphical method for radiation therapy plan quality assessment

Background: This work aims at clinically validating a graphical tool developed for treatment plan assessment, named SPIDERplan, by comparing the plan choices based on its scoring with the radiation oncologists (RO) clinical preferences. Methods: SPIDERplan validation was performed for nasopharynx pathology in two steps. In the first step, three ROs from three Portuguese radiotherapy departments were asked to blindly evaluate and rank the dose distributions of twenty pairs of treatment plans. For plan ranking, the best plan from each pair was selected. For plan evaluation, the qualitative classification of ‘Good’, ‘Admissible with minor deviations’ and ‘Not Admissible’ were assigned to each plan. In the second step, SPIDERplan was applied to the same twenty patient cases. The tool was configured for two sets of structures groups: the local clinical set and the groups of structures suggested in international guidelines for nasopharynx cancer. Group weights, quantifying the importance of each group and incorporated in SPIDERplan, were defined according to RO clinical preferences and determined automatically by applying a mixed linear programming model for implicit elicitation of preferences. Intra- and inter-rater ROs plan selection and evaluation were assessed using Brennan-Prediger kappa coefficient. Results: Two-thirds of the plans were qualitatively evaluated by the ROs as ‘Good’. Concerning intra- and inter-rater variabilities of plan selection, fair agreements were obtained for most of the ROs. For plan evaluation, substantial agreements were verified in most cases. The choice of the best plan made by SPIDERplan was identical for all sets of groups and, in most cases, agreed with RO plan selection. Differences between RO choice and SPIDERplan analysis only occurred in cases for which the score differences between the plans was very low. A score difference threshold of 0.005 was defined as the value below which two plans are considered of equivalent quality. Conclusion: Generally, SPIDERplan response successfully reproduced the ROs plan selection. SPIDERplan assessment performance can represent clinical preferences based either on manual or automatic group weight assignment. For nasopharynx cases, SPIDERplan was robust in terms of the definitions of structure groups, being able to support different configurations without losing accuracy

Learning target-based preferences through additive models: An application in radiotherapy treatment planning

This article presents a new Multi-Criteria Decision Aiding preference disaggregation method based on an asymmetric target-based model. The decision maker’s preferences are elicited considering the choices made given a set of comparisons among pairs of solutions (the stimuli). It is assumed that the decision maker has a reference value (target) for the stimulus. Solutions that do not comply with this reference value for some of the criteria dimensions considered will be penalized, and an inferred weight is as- sociated with each dimension to calculate a penalty score for each solution. One of the differentiating features of the proposed model when compared with other existing models is the fact that only solu- tions that do not meet the target are penalized. The target is not interpreted as an ideal solution, but as a set of threshold values that should be taken into account when choosing a solution. The proposed ap- proach was applied to the problem of choosing radiotherapy treatment plans, using a set of retrospective cancer cases treated at the Portuguese Oncology Institute of Coimbra. Using paired comparison choices made by one radiation oncologist, the preference model was built and was tested with in-sample and out-of-sample data. It is possible to conclude that the preference model is capable of representing the radiation oncologist’s preferences, presenting small mean errors and leading, most of the time, to the same treatment plan chosen by the radiation oncologist