Applying quantitative methods in the assessment of outcomes of pharmacotherapy of psoriasis

Healthcare providers and policy makers are faced with an ever-increasing number of medical publications. Searching for relevant information and keeping up to date with new research findings remains a constant challenge. It has been widely acknowledged that narrative reviews of the literature are susceptible to several types of bias and a systematic approach may protect against these biases. The aim of this thesis was to apply quantitative methods in the assessment of outcomes of topical therapies for psoriasis. In particular, to systematically examine the comparative efficacy, tolerability and cost-effectiveness of topical calcipotriol in the treatment of mild-to-moderate psoriasis. Over the years, a wide range of techniques have been used to evaluate the severity of psoriasis and the outcomes from treatment. This lack of standardisation complicates the direct comparison of results and ultimately the pooling of outcomes from different clinical trials. There is a clear requirement for more comprehensive tools for measuring drug efficacy and disease severity in psoriasis. Ideally, the outcome measures need to be simple, relevant, practical, and widely applicable, and the instruments should be reliable, valid and responsive. The results of the meta-analysis reported herein show that calcipotriol is an effective antipsoriatic agent. In the short-tenn, the pooled data found calcipotriol to be more effective than calcitriol, tacalcitol, coal tar and short-contact dithranol. Only potent corticosteroids appeared to have comparable efficacy, with less short-term side-effects. Potent corticosteroids also added to the antipsoriatic effect of calcipotriol, and appeared to suppress the occurrence of calcipotriol-induced irritation. There was insufficient evidence to support any large effects in favour of improvements in efficacy when calcipotriol is used in combination with systemic therapies in patients with severe psoriasis. However, there was a total absence of long-term morbidity data on the effectiveness of any of the interventions studied. Decision analysis showed that, from the perspective of the NHS as payer, the relatively small differences in efficacy between calcipotriol and short-contact dithranol lead to large differences in the direct cost of treating patients with mildto-moderate plaque psoriasis. Further research is needed to examine the clinical and economic issues affecting patients under treatment for psoriasis in the UK. In particular, the maintenance value and cost/benefit ratio for the various treatment strategies, and the assessment of patient's preferences has not yet been adequately addressed for this chronic recurring disease.

Knowledge engineering for mental-health risk assessment and decision support

Mental-health risk assessment practice in the UK is mainly paper-based, with little standardisation in the tools that are used across the Services. The tools that are available tend to rely on minimal sets of items and unsophisticated scoring methods to identify at-risk individuals. This means the reasoning by which an outcome has been determined remains uncertain. Consequently, there is little provision for: including the patient as an active party in the assessment process, identifying underlying causes of risk, and eecting shared decision-making. This thesis develops a tool-chain for the formulation and deployment of a computerised clinical decision support system for mental-health risk assessment. The resultant tool, GRiST, will be based on consensual domain expert knowledge that will be validated as part of the research, and will incorporate a proven psychological model of classication for risk computation. GRiST will have an ambitious remit of being a platform that can be used over the Internet, by both the clinician and the layperson, in multiple settings, and in the assessment of patients with varying demographics. Flexibility will therefore be a guiding principle in the development of the platform, to the extent that GRiST will present an assessment environment that is tailored to the circumstances in which it nds itself. XML and XSLT will be the key technologies that help deliver this exibility.

An assessment of the technique and clinical application of visual evoked response measurements

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Psychological cue use and implications for a clinical decision support system

Effective clinical decision making depends upon identifying possible outcomes for a patient, selecting relevant cues, and processing the cues to arrive at accurate judgements of each outcome's probability of occurrence. These activities can be considered as classification tasks. This paper describes a new model of psychological classification that explains how people use cues to determine class or outcome likelihoods. It proposes that clinicians respond to conditional probabilities of outcomes given cues and that these probabilities compete with each other for influence on classification. The model explains why people appear to respond to base rates inappropriately, thereby overestimating the occurrence of rare categories, and a clinical example is provided for predicting suicide risk. The model makes an effective representation for expert clinical judgements and its psychological validity enables it to generate explanations in a form that is comprehensible to clinicians. It is a strong candidate for incorporation within a decision support system for mental-health risk assessment, where it can link with statistical and pattern recognition tools applied to a database of patients. The symbiotic combination of empirical evidence and clinical expertise can provide an important web-based resource for risk assessment, including multi-disciplinary education and training. © 2002 Informa UK Ltd All rights reserved.

A Мodel for Assessment of Professional Competence in Physical Therapy Students

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015

The therapeutic effects of Millon Clinical Multiaxial Inventory -III assessment feedback

A study was conducted to test the therapeutic effects of assessment feedback on rapport-building and self-enhancement variables (self-verification, self-discovery, self-esteem), as well as symptomatology. Assessment feedback was provided in the form of interpretive information based on the results of the Millon Clinical Multiaxial Inventory-III (MCMI-III). Participants (N = 89) were randomly assigned to three groups: a Feedback group, a Reflective-Counseling group, and a No-Feedback group. The Feedback group was provided with assessment feedback, the Reflective-Counseling group was asked to comment on the meaning of the taking the MCMI-III, the No-Feedback group received general information about the MCMI-III. Results revealed that assessment feedback, when provided in the form of interpretive interpretation positively affects rapport-building and self-enhancement variables (self-verification and self-discovery). No significant results were found in terms of self-esteem or symptom decrease as a function of feedback. However, a significant decrease in symptoms across groups was found. Results indicate that assessment feedback in the form of interpretive information can be used as a starting point in therapy. Implications of the findings are discussed with respect to theory and clinical practice. ^

The therapeutic effects of Millon Clinical Multiaxial Inventory-III assessment feedback

A study was conducted to test the therapeutic effects of assessment feedback on rapport-building and self-enhancement variables (self-verification, self-discovery, self-esteem), as well as symptomatology. Assessment feedback was provided in the form of interpretive information based on the results of the Millon Clinical Multiaxial Inventory- III (MCMI-III). Participants (N = 89) were randomly assigned to three groups: a Feedback group, a Reflective-Counseling group, and a No-Feedback group. The Feedback group was provided with assessment feedback, the Reflective-Counseling group was asked to comment on the meaning of the taking the MCMI-III, the No- Feedback group received general information about the MCMI-III. Results revealed that assessment feedback, when provided in the form of interpretive interpretation positively affects rapport-building and self-enhancement variables (self-verification and self-discovery). No significant results were found in terms of self-esteem or symptom decrease as a function of feedback. However, a significant decrease in symptoms across groups was found. Results indicate that assessment feedback in the form of interpretive information can be used as a starting point in therapy. Implications of the findings are discussed with respect to theory and clinical practice.

The development of a self-directed learning module for rural emergency nurses on pediatric diabetic ketoacidosis

Background: Newfoundland and Labrador has a high incidence of type 1 diabetes and diabetic ketoacidosis (DKA) is a complication of type 1 diabetes. A clinical practice guideline was developed for the treatment of pediatric diabetic ketoacidosis (DKA) to standardize care in all Emergency Departments and improve patient outcomes. Rural emergency nurses are requires to maintain their competency and acquire new knowledge as stated by the Association of Registered Nurses of Newfoundland and Labrador (ARNNL). Purpose: The purpose of this practicum was to develop a self-learning module for rural emergency nurses to increase their knowledge and understanding of the clinical practise guideline to assess, treat, and prevent pediatric ketoacidosis. Methods: Two methodologies were used in this practicum. A review of the literature and consultations with key stakeholders were completed. Results: The self-learning module created was composed of three units and focused on the learning needs of rural emergency nurses in the areas of assessment, treatment, and prevention of pediatric DKA. Conclusion: The goal of the practicum was to increase rural emergency nurses’ knowledge and implementation of the clinical practice guideline when assessing and treating children and families experiencing DKA to improve patient outcomes. A planned evaluation of the self-learning module will be conducted following dissemination of the module throughout the rural Emergency Departments.

Self-assessment of clinical nurse mentors as dimensions of professional development and the capability of developing ethical values among nursing students : A correlational research study

Date of Acceptance: 08/04/2015 The paper presents, in part, the results of a broader non-profit development project entitled “Advance level of knowledge for quality in clinical mentorship — professional ethics and continuously professional development”. The project was financed by the Ministry of Higher Education, Science and Sport of the Republic of Slovenia (contract no. 3211-11-000263, the number of project OP RCV_VS-11-14). The members of the development group of the project were: Brigita Skela-Savič (leader), Karmen Romih, Sanela Pivač, Katja Skinder Savić and Andreja Prebil. The research report for the entire project is available on the online bibliographic database COBIB.si, at the Faculty of Health Care Jesenice and at the Ministry of Higher Education, Science and Sport of the Republic of Slovenia.

Self-assessment of clinical nurse mentors as dimensions of professional development and the capability of developing ethical values among nursing students : A correlational research study

Date of Acceptance: 08/04/2015 The paper presents, in part, the results of a broader non-profit development project entitled “Advance level of knowledge for quality in clinical mentorship — professional ethics and continuously professional development”. The project was financed by the Ministry of Higher Education, Science and Sport of the Republic of Slovenia (contract no. 3211-11-000263, the number of project OP RCV_VS-11-14). The members of the development group of the project were: Brigita Skela-Savič (leader), Karmen Romih, Sanela Pivač, Katja Skinder Savić and Andreja Prebil. The research report for the entire project is available on the online bibliographic database COBIB.si, at the Faculty of Health Care Jesenice and at the Ministry of Higher Education, Science and Sport of the Republic of Slovenia.

Self-assessment of clinical nurse mentors as dimensions of professional development and the capability of developing ethical values among nursing students : A correlational research study

Date of Acceptance: 08/04/2015 The paper presents, in part, the results of a broader non-profit development project entitled “Advance level of knowledge for quality in clinical mentorship — professional ethics and continuously professional development”. The project was financed by the Ministry of Higher Education, Science and Sport of the Republic of Slovenia (contract no. 3211-11-000263, the number of project OP RCV_VS-11-14). The members of the development group of the project were: Brigita Skela-Savič (leader), Karmen Romih, Sanela Pivač, Katja Skinder Savić and Andreja Prebil. The research report for the entire project is available on the online bibliographic database COBIB.si, at the Faculty of Health Care Jesenice and at the Ministry of Higher Education, Science and Sport of the Republic of Slovenia.

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Automated Assessment of Image Quality and Dose Attributes in Clinical CT Images

Computed tomography (CT) is a valuable technology to the healthcare enterprise as evidenced by the more than 70 million CT exams performed every year. As a result, CT has become the largest contributor to population doses amongst all medical imaging modalities that utilize man-made ionizing radiation. Acknowledging the fact that ionizing radiation poses a health risk, there exists the need to strike a balance between diagnostic benefit and radiation dose. Thus, to ensure that CT scanners are optimally used in the clinic, an understanding and characterization of image quality and radiation dose are essential.

The state-of-the-art in both image quality characterization and radiation dose estimation in CT are dependent on phantom based measurements reflective of systems and protocols. For image quality characterization, measurements are performed on inserts imbedded in static phantoms and the results are ascribed to clinical CT images. However, the key objective for image quality assessment should be its quantification in clinical images; that is the only characterization of image quality that clinically matters as it is most directly related to the actual quality of clinical images. Moreover, for dose estimation, phantom based dose metrics, such as CT dose index (CTDI) and size specific dose estimates (SSDE), are measured by the scanner and referenced as an indicator for radiation exposure. However, CTDI and SSDE are surrogates for dose, rather than dose per-se.

Currently there are several software packages that track the CTDI and SSDE associated with individual CT examinations. This is primarily the result of two causes. The first is due to bureaucracies and governments pressuring clinics and hospitals to monitor the radiation exposure to individuals in our society. The second is due to the personal concerns of patients who are curious about the health risks associated with the ionizing radiation exposure they receive as a result of their diagnostic procedures.

An idea that resonates with clinical imaging physicists is that patients come to the clinic to acquire quality images so they can receive a proper diagnosis, not to be exposed to ionizing radiation. Thus, while it is important to monitor the dose to patients undergoing CT examinations, it is equally, if not more important to monitor the image quality of the clinical images generated by the CT scanners throughout the hospital.

The purposes of the work presented in this thesis are threefold: (1) to develop and validate a fully automated technique to measure spatial resolution in clinical CT images, (2) to develop and validate a fully automated technique to measure image contrast in clinical CT images, and (3) to develop a fully automated technique to estimate radiation dose (not surrogates for dose) from a variety of clinical CT protocols.

Situation Background Assessment Recommendation (SBAR): Undergraduate Perspectives

Situation Background Assessment and Recommendation (SBAR): Undergraduate Perspectives C Morgan, L Adams, J Murray, R Dunlop, IK Walsh. Ian K Walsh, Centre for Medical Education, Queen’s University Belfast, Mulhouse Building, Royal Victoria Hospital, Grosvenor Road, Belfast BT12 6DP Background and Purpose: Structured communication tools are used to improve team communication quality.1,2 The Situation Background Assessment and Recommendation (SBAR) tool is widely adopted within patient safety.3 SBAR effectiveness is reportedly equivocal, suggesting use is not sustained beyond initial training.4-6 Understanding perspectives of those using SBAR may further improve clinical communication. We investigated senior medical undergraduate perspectives on SBAR, particularly when communicating with senior colleagues. Methodology: Mixed methods data collection was used. A previously piloted questionnaire with 12 five point Lickert scale questions and 3 open questions was given to all final year medical students. A subgroup also participated in 10 focus groups, deploying strictly structured audio-recorded questions. Selection was by convenience sampling, data gathered by open text questions and comments transcribed verbatim. In-vivo coding (iterative, towards data saturation) preceded thematic analysis. Results: 233 of 255 students (91%) completed the survey. 1. There were clearly contradictory viewpoints on SBAR usage. A recurrent theme was a desire for formal feedback and a relative lack of practice/experience with SBAR. 2. Students reported SBAR as having variable interpretation between individuals; limiting use as a shared mental model. 3. Brief training sessions are insufficient to embed the tool. 4. Most students reported SBAR helping effective communication, especially by providing structure in stressful situations. 5. Only 18.5% of students felt an alternative resource might be needed. Sub analysis of the themes highlighted: A. Lack of clarity regarding what information to include and information placement within the acronym, B. Senior colleague negative response to SBAR C. Lack of conciseness with the tool. Discussion and Conclusions: Despite a wide range of contradictory interpretation of SBAR utility, most students wish to retain the resource. More practice opportunities/feedback may enhance user confidence and understanding. References: (1) Leonard M, Graham S, Bonacum D. The human factor: the critical importance of effective teamwork and communication in providing safe care. Quality & Safety in Health Care 2004 Oct;13(Suppl 1):85-90. (2) d'Agincourt-Canning LG, Kissoon N, Singal M, Pitfield AF. Culture, communication and safety: lessons from the airline industry. Indian J Pediatr 2011 Jun;78(6):703-708. (3) Dunsford J. Structured communication: improving patient safety with SBAR. Nurs Womens Health 2009 Oct;13(5):384-390. (4) Compton J, Copeland K, Flanders S, Cassity C, Spetman M, Xiao Y, et al. Implementing SBAR across a large multihospital health system. Jt Comm J Qual Patient Saf 2012 Jun;38(6):261-268. (5) Ludikhuize J, de Jonge E, Goossens A. Measuring adherence among nurses one year after training in applying the Modified Early Warning Score and Situation-Background-Assessment-Recommendation instruments. Resuscitation 2011 Nov;82(11):1428-1433. (6) Cunningham NJ, Weiland TJ, van Dijk J, Paddle P, Shilkofski N, Cunningham NY. Telephone referrals by junior doctors: a randomised controlled trial assessing the impact of SBAR in a simulated setting. Postgrad Med J 2012 Nov;88(1045):619-626.

Colorimetric Assessment of BCR-ABL1 Transcripts in Clinical Samples Via Gold Nanoprobes

Gold nanoparticles functionalized with thiolated oligonucleotides (Au-nanoprobes) have been used in a range of applications for the detection of bioanalytes of interest, from ions to proteins and DNA targets. These detection strategies are based on the unique optical properties of gold nanoparticles, in particular, the intense color that is subject to modulation by modification of the medium dieletric. Au-nanoprobes have been applied for the detection and characterization of specific DNA sequences of interest, namely pathogens and disease biomarkers. Nevertheless, despite its relevance, only a few reports exist on the detection of RNA targets. Among these strategies, the colorimetric detection of DNA has been proven to work for several different targets in controlled samples but demonstration in real clinical bioanalysis has been elusive. Here, we used a colorimetric method based on Au-nanoprobes for the direct detection of the e14a2 BCR-ABL fusion transcript in myeloid leukemia patient samples without the need for retro-transcription. Au-nanoprobes directly assessed total RNA from 38 clinical samples, and results were validated against reverse transcription-nested polymerase chain reaction (RT-nested PCR) and reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The colorimetric Au-nanoprobe assay is a simple yet reliable strategy to scrutinize myeloid leukemia patients at diagnosis and evaluate progression, with obvious advantages in terms of time and cost, particularly in low- to medium-income countries where molecular screening is not routinely feasible. Graphical abstract Gold nanoprobe for colorimetric detection of BCR-ABL1 fusion transcripts originating from the Philadelphia chromosome.