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By jake coyle, ap film writer
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Noam Galai/Getty Images
WATCH Scarlett Johansson's casting as transgender man draws backlash
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Scarlett Johansson on Friday withdrew from the film "Rub Tug" after her plans to portray a transgender man prompted a backlash.

In a statement to Out.com on Friday, Johansson said she's pulling out from the project "in light of recent ethical questions raised surrounding my casting." Last week, Johansson said she would star as Pittsburgh 1970s and '80s prostitution ring leader Dante "Tex" Gill, who was born Lois Jean Gill but identified as a man.

When transgender actors and advocates questioned the casting, Johansson initially responded with a statement that criticism "can be directed to Jeffrey Tambor, Jared Leto and Felicity Huffman's reps." All are cisgender actors who won acclaim for playing transgender characters.

Figure 1
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Common components contributing to the calculation of robustness.
Common components contributing to the calculation of robustness.

Robustness is generally calculated for a given decision alternative, x i , across a given set of future scenarios S  = { s 1 ,  s 2 , …,  s n } using a particular performance metric f (·). Consequently, the calculation of robustness using a particular metric corresponds to the transformation of the performance of a set of decision alternatives over different scenarios, f ( x i ,  S ) = { f ( x i ,  s 1 ),  f ( x i ,  s 2 ), …,  f ( x i ,  s n )} to the robustness R ( x i ,  S ) of these decision alternatives over this set of scenarios. Although different robustness metrics achieve this transformation in different ways, a unifying framework for the calculation of different robustness metrics can be introduced by representing the overall transformation of f ( x i ,  S ) into R ( x i ,  S ) by three separate transformations: performance value transformation ( T 1 ), scenario subset selection ( T 2 ), and robustness metric calculation ( T 3 ), as shown in Figure 2 . Details of these transformations for a range of commonly used robustness metrics are given in Table 1 and their mathematical implementations are given in Supporting Information S1.

Figure 2
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Unifying framework of components and transformations in the calculation of commonly used robustness metrics.
Unifying framework of components and transformations in the calculation of commonly used robustness metrics.

The performance value transformation ( T 1 ) converts the performance values f ( x i ,  S ) into the type of information f ( x i ,  S ) used in the calculation of the robustness metric R ( x i ,  S ). For some robustness metrics, the absolute performance values (e.g., cost, reliability) are used, in which case T 1 corresponds to the identity transform (i.e., the performance values are not changed). For other robustness metrics, the absolute system performance values are transformed to values that either measure the regret that results from selecting a particular decision alternative rather than the one that performs best had a particular future actually occurred or indicate whether the selection of a decision alternative results in satisfactory system performance or not (i.e., whether required system constraints have been satisfied or not).

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Article Text

Cardiovascular medicine
Protocol
Risk factors for difficult peripheral venous cannulation in hospitalised patients. Protocol for a multicentre case–control study in 48 units of eight public hospitals in Spain

Introduction Patients with difficult venous access experience undesirable effects during healthcare, such as delayed diagnosis and initiation of treatment, stress and pain related to the technique and reduced satisfaction. This study aims to identify risk factors with which to model the appearance of difficulty in achieving peripheral venous puncture in hospital treatment.

Methods and analysis Case–control study. We will include adult patients requiring peripheral venous cannulation in eight public hospitals, excluding those in emergency situations and women in childbirth or during puerperium. The nurse who performs the technique will record in an anonymised register variables related to the intervention. Subsequently, a researcher will extract the health variables from the patient’s medical history. Patients who present one of the following conditions will be assigned to the case group: two or more failed punctures, need for puncture support, need for central access after failure to achieve peripheral access, or decision to reject the technique. The control group will be obtained from records of patients who do not meet the above conditions. It has been stated a minimum sample size of 2070 patients, 207 cases and 1863 controls.

A descriptive analysis will be made of the distribution of the phenomenon. The variables hypothesised to be risk factors for the appearance of difficult venous cannulation will be studied using a logistic regression model.

Ethics and dissemination The study was funded in January 2017 and obtained ethical approval from the Research Ethics Committee of the Balearic Islands. Informed consent will be obtained prior to data collection. Results will be published in a peer-reviewed scientific journal.

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

http://dx.doi.org/10.1136/bmjopen-2017-020420

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Strengths and limitations of this study

To our knowledge, no previous case–control studies have been conducted to identify therisk factors for difficult peripheral cannulation, or to describe this problem in different healthcare settings.

Systematic analysis of an extended sample of the patient's spontaneous (propositional) speech ( Table 2 ) is the single most valuable aspect of the examination. Where little spontaneous conversation is offered, the patient can be asked to describe a scene in a photograph or drawing (an example is shown in Fig. 4 A). This is preferable to asking the patient to recount an event in their daily routine, as it allows speech to be evaluated independently of episodic memory and provides a standard with which to compare speech characteristics in different clinical situations. Examples of scene descriptions produced by patients with canonical speech disorders are presented in Table 3 . Valuable information is often obtained from observing the patient's general behaviour and approach to the clinical interview. The inert patient with a frontal dementia, who offers little speech at all and sits passively throughout the interview, makes a very different impression from the patient with PNFA, who is obviously frustrated by their difficulties and struggles to compensate with an excess of non-verbal gestures, and both contrast with the garrulous patient with semantic dementia (SD), who produces a steady stream of circumlocutory speech.

Fig. 4
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Materials for assessing speech at the bedside. (Reproduced with permission of Professor EK Warrington.) ( A ) A beach scene, illustrating one means of eliciting conversational speech (see examples in Table 3 ). ( B ) A passage for reading aloud (see text).

Fig. 4
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Materials for assessing speech at the bedside. (Reproduced with permission of Professor EK Warrington.) ( A ) A beach scene, illustrating one means of eliciting conversational speech (see examples in Table 3 ). ( B ) A passage for reading aloud (see text).

The classification of aphasias as ‘expressive’ or ‘receptive’ (or ‘motor’ or ‘sensory’) is both overly simplistic and inaccurate (Geschwind, 1971 ): few patients present with either a pure speech production or comprehension deficit. This is true for acute lesions (Brust et al ., 1976 ), but particularly relevant to the categorization of the progressive aphasias. Similarly, classifying speech disturbances as ‘fluent’ or ‘non-fluent’ also oversimplifies the clinical phenomenology and is open to misinterpretation. Fluency describes the flow of speech output, but it is multidimensional: ‘non-fluency’ may be due to a number of different factors, including decreased phrase length, agrammatism, poor articulation or slower speech rate (Hillis, 2007 ). As these impairments tend to occur together, an individual patient's speech can often be reliably categorized as fluent or non-fluent; moreover, certain dimensions (particular motor aspects such as rate and articulation) make a relatively greater contribution to the impression of dysfluency. However, the component processes are dissociable: thus, patients with milder forms of ‘non-fluent’ speech may still produce relatively long phrases or sentences, albeit containing many errors. Even in more advanced cases of ‘non-fluent’ speech, there may be stereotyped phrases comprising several words (e.g. ‘Hello, how are you?’): such phrases can be regarded as an expressive ‘unit’ serving a similar function to a single word. Conversely, patients with ‘fluent’ aphasias generally have empty speech due to an impaired ability to find appropriate content words but commonly also have conversational pauses during which they struggle to find the appropriate word: these gaps tend to reduce the overall number of words produced (‘logopenia’) and thus the fluency of the utterance as a whole. Although it remains clinically useful as a descriptive term, ‘fluency’ is therefore potentially misleading as a criterion for the categorization of speech and language syndromes, which is more usefully based on a combination of features ( Fig. 2 ).

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Condition and disease informationis written and reviewed by the MediResource Clinical Team. The contents of this site are for informational purposes only and are meant to be discussed with your physician or other qualified health care professional before being acted on. Never disregard any advice given to you by your doctor or other qualified health care professional. Always seek the advice of a physician or other licensed health care professional regarding any questions you have about your medical condition(s) and treatment(s).

This site is not a substitute for medical advice. © 1996 - 2018

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