Likelihood Ratio, Skull Roentgenograms, and Clinical Decision-Making

PEDIATRICS ◽  
1983 ◽  
Vol 71 (4) ◽  
pp. 673-674
Author(s):  
JOHN C. LEONIDAS ◽  
ANNA BINKIEWICZ ◽  
R. MICHAEL SCOTT ◽  
STEPHEN G. PAUKER
Keyword(s):  
Decision Making ◽  
Likelihood Ratio ◽  
Predictive Value ◽  
Clinical Finding ◽  
Posterior Probability ◽  
Clinical Decision Making ◽  
Skull Fracture ◽  
Clinical Decision ◽  
Negative Finding ◽  
The Individual

In Reply.— We appreciate the thoughtful comments of Leventhal and Lembo and concur with their conclusion that the clinician needs to know "the probability of skull fracture in a patient with head trauma." Unfortunately, their proposed "clinical likelihood ratio" (CR) will not further that end because it compares the predictive value (or, more precisely, the posterior probability) of a skull fracture after a positive clinical finding to the posterior probability after a negative finding. After the patient has been examined, the patient does not have both findings; thus, the CR cannot apply to the individual patient.

Likelihood Ratio, Skull Roentgenograms, and Clinical Decision-Making

PEDIATRICS ◽  
1983 ◽  
Vol 71 (4) ◽  
pp. 672-673
Author(s):  
JOHN M. LEVENTHAL ◽  
ROBERT M. LEMBO
Keyword(s):  
Decision Making ◽  
Likelihood Ratio ◽  
Clinical Finding ◽  
Clinical Decision Making ◽  
Skull Fracture ◽  
Clinical Decision ◽  
Clinical Findings ◽  
Skull Fractures ◽  
Fractures In Children ◽  
The Relationship

To the Editor.— In the February 1982 issue of Pediatrics, Leonidas et al1 examined the relationship between clinical findings and skull fractures in children evaluated with skull roentgenograms to develop reliable criteria for the ordering of roentgenograms in patients with head trauma. In their analysis, the authors used the liklihood ratio (LR) to characterize quantitatively the relationship between a clinical finding and the presence of a skull fracture. As defined by the authors, the LR is that ratio between the probability of a certain clinical finding occurring in the presence of a fracture and the probability of the same clinical finding occurring in the absence of a fracture.

Abstract W P266: A Simple Score for Prediction of Outcome after Cerebral Venous Thrombosis

Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Miguel A Barboza ◽  
Erwin Chiquete ◽  
Antonio Arauz ◽  
Jonathan Colín ◽  
Alejandro Quiroz-Compean ◽  
...  
Keyword(s):  
Decision Making ◽  
Venous Thrombosis ◽  
Predictive Value ◽  
Cerebral Venous Thrombosis ◽  
Goodness Of Fit ◽  
Clinical Decision Making ◽  
Case Fatality ◽  
Clinical Decision ◽  
Classification Systems ◽  
Cox Proportional Hazards Model

Background and purpose: Cerebral venous thrombosis (CVT) not always implies a good prognosis. There is a need for robust and simple classification systems of severity after CVT that help in clinical decision-making. Methods: We studied 467 patients (81.6% women, median age: 29 years, interquartile range: 22-38 years) with CVT who were hospitalized from 1980 to 2014 in two third-level referral hospitals. Bivariate analyses were performed to select variables associated with 30-day mortality to integrate a further multivariate analysis. The resultant model was evaluated with the Hosmer-Lemeshow test for goodness of fit, and on Cox proportional hazards model for reliability of the effect size. After the scale was configured, security and validity were tested for 30-day mortality and modified Rankin scale (mRS) >2. The prognostic performance was compared with that of the CVT risk score (CVT-RS, 0-6 points) as the reference system. Results: The 30-day case fatality rate was 8.7%. The CVT grading scale (CVT-GS, 0-9 points) was integrated by stupor/coma (4 points), parenchymal lesion >6 cm (2 points), mixed (superficial and deep systems) CVT (1 point), meningeal syndrome (1 point) and seizures (1 point). CVT-GS was categorized into mild (0-3 points, 1.1% mortality), moderate (4-6 points, 19.6% mortality) and severe (7-9 points, 61.4% mortality). For 30-day mortality prediction, as compared with CVT-RS (cut-off 4 points), CVT-GS (cut-off 5 points) was globally better in sensitivity (85% vs 37%), specificity (90% vs 95%), positive predictive value (44% vs 40%), negative predictive value (98% vs 94%), and accuracy (94% vs 80%). For 30-day mRS >2 the performance of CVT-GS over CVT-RS was comparably improved. Conclusion: The CVT-GS is a simple and reliable score for predicting outcome that may help in clinical decision-making and that could be used to stratify patients recruited into clinical trials.

scholarly journals QOLP-03. MEASURING CHANGE IN HEALTH-RELATED QUALITY OF LIFE: THE ADDED VALUE OF ANALYSIS ON THE INDIVIDUAL PATIENT LEVEL IN GLIOMA PATIENTS IN CLINICAL DECISION MAKING

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi197-vi198 ◽  
Author(s):  
Marijke Coomans ◽  
Martin Taphoorn ◽  
Neil Aaronson ◽  
Brigitta Baumert ◽  
Martin van den Bent ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Scale Item ◽  
Individual Patient Level ◽  
Patient Level ◽  
Related Quality ◽  
The Individual ◽  
The Impact ◽  
Over Time

Abstract BACKGROUND: Health-related quality of life (HRQoL) is an important outcome in glioma research, reflecting the impact of disease and treatment on a patient’s functioning and wellbeing. Data on changes in HRQoL scores provide important information for clinical decision-making, but different analytical methods may lead to different interpretations of the impact of treatment on HRQoL. This study aimed to study whether different methods to evaluate change in HRQoL result in different interpretations. Methods: HRQoL and sociodemographical/clinical data from 15 randomized clinical trials were combined. Change in HRQoL scores was analyzed: (1)at the group level, comparing mean changes in scale/item scores between treatment arms over time, (2)at the patient level per scale/item by calculating the percentage of patients that deteriorated, improved or remained stable on a scale/item per scale/item, and (3)at the individual patient level combining all scales/items. Results: Data were available for 3727 patients. At the group scale/item level (method 1), only the item ‘hair loss’ showed a significant and clinically relevant change (i.e. ≥10 points) over time, whereas change scores on the other scales/items showed a statistically significant change only (all p< .001, range in change score:0.1–6.2). Analyses on the patient level per scale (method 2) indicated that, while a large proportion of patients had stable HRQoL over time (range:27–84%), many patients deteriorated (range:6–43%) or improved (range:8–32%) on a specific scale/item. At the individual patient level (method 3), the majority of patients (86%) showed both deterioration and improvement, while only 1% of the patients remained stable on all scales. Conclusion: Different analytical methods of changes in HRQoL result in distinct interpretations of treatment effects, all of which may be relevant for clinical decision-making. Additional information about the joint impact of treatment on all outcomes may help patients and physicians to make the best treatment decision.

scholarly journals OS7.2 Measuring change in health-related quality of life: the added value of analysis on the individual patient level in glioma patients in clinical decision making

2019 ◽  
Vol 21 (Supplement_3) ◽  
pp. iii14-iii14
Author(s):  
M Coomans ◽  
M J B Taphoorn ◽  
N Aaronson ◽  
B G Baumert ◽  
M van den Bent ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Scale Item ◽  
Individual Patient Level ◽  
Patient Level ◽  
Related Quality ◽  
The Individual ◽  
The Impact ◽  
Over Time

Abstract BACKGROUND Health-related quality of life (HRQoL) is often used as an outcome in glioma research, reflecting the impact of disease and treatment on a patient’s functioning and wellbeing. Data on changes in HRQoL scores may provide important information for clinical decision-making, but different analytical methods may lead to different interpretations of the impact of treatment on HRQoL. This study aimed to examine three different methods to evaluate change in HRQoL, and to study whether these methods result in different interpretations. MATERIAL AND METHODS HRQoL and sociodemographical/clinical data from 15 randomized clinical trials were combined. Change in HRQoL scores was analyzed in three ways: (1) at the group level, comparing mean changes in scale/item scores between treatment arms over time, (2) at the patient level per scale/item by calculating the percentage of patients that deteriorated, improved or remained stable on a scale/item per scale/item, and (3) at the individual patient level combining all scales/items. RESULTS Baseline and first follow-up HRQoL data were available for 3727 patients. At the group scale/item level (method 1), only the item ‘hair loss’ showed a significant and clinically relevant change (i.e. ≥10 points) over time, whereas change scores on the other scales/items showed a statistically significant change only (all p<.001, range in change score: 0.1–6.2). Analyses on the patient level per scale (method 2) indicated that, while a large proportion of patients had stable HRQoL over time (range 27–84%), many patients deteriorated (range: 6–43%) or improved (range: 8–32%) on a specific scale/item. At the individual patient level (method 3), the majority of patients (86%) showed both deterioration and improvement, while only 1% of the patients remained stable on all scales. Clustering on clinical characteristics (WHO performance status, sex, tumor type, type of resection, newly diagnosed versus recurrent tumor and age) did not identify subgroups of patients with a specific pattern of change in their HRQoL score. CONCLUSION Different analytical methods of changes in HRQoL result in distinct interpretations of treatment effects, all of which may be relevant for clinical decision-making. Additional information about the joint impact of treatment on all outcomes, showing that most patients experience both deterioration and improvement, may help patients and physicians to make the best treatment decision.

Clinical Decision-Making for a Person Centered Medicine: the necessity of casuistic reasoning

2014 ◽  
Vol 2 (1) ◽  
pp. 71
Author(s):  
Mark Tonelli
Keyword(s):  
Decision Making ◽  
Clinical Judgment ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Patient Choice ◽  
Clinical Expertise ◽  
Patient Centered ◽  
Patient Centered Medicine ◽  
The Individual ◽  
Based Medicine

In their call to develop a consistent, coherent and comprehensive notion of person-centered medicine, Miles and Mezzich have elucidated several specific challenges that need to be urgently addressed. One of these foundational tasks is the development of a more complete understanding of person-centered clinical decision-making. Miles and Mezzich note that while the emphasis on clinical research in evidence-based medicine has served to de-emphasize the importance of the individual patient, the alternative of patient-centered medicine has the potential to de-emphasize the judgment of the clinician by making unfettered patient choice paramount. A practice of medicine that reduces professional healers to an informational role only, one where they lay out potential interventions devoid of context and allow patients to choose from amongst them, undervalues clinical expertise and will clearly not lead to better outcomes. Person-centered medicine (PCM), then, must be able to develop and defend a model of clinical judgment and practice that strikes the correct balance between the science of medicine and the personal experience of the individual in search of care.

The predictive value of microbiological findings on teeth, internal and external implant portions in clinical decision making

2016 ◽  
Vol 28 (5) ◽  
pp. 512-519 ◽  
Author(s):  
Luigi Canullo ◽  
Sandro Radovanović ◽  
Boris Delibasic ◽  
Juan Antonio Blaya ◽  
David Penarrocha ◽  
...  
Keyword(s):  
Decision Making ◽  
Predictive Value ◽  
Clinical Decision Making ◽  
Clinical Decision

scholarly journals ADOLESCENT PATIENTS AND THE CLINICAL DECISION ABOUT THEIR HEALTH

2019 ◽  
Vol 37 (4) ◽  
pp. 503-509
Author(s):  
Marlene Pereira Garanito ◽  
Vera Lucia Zaher-Rutherford
Keyword(s):  
Decision Making ◽  
Latin American ◽  
Clinical Decision Making ◽  
Case Reports ◽  
Treatment Decision ◽  
Clinical Decision ◽  
Electronic Library ◽  
Data Synthesis ◽  
Treatment Decision Making ◽  
The Individual

ABSTRACT Objective: To carry out a review of the literature on adolescents’ participation in decision making for their own health. Data sources: Review in the Scientific Electronic Library Online (SciELO), Latin American and Caribbean Health Sciences Literature (LILACS) and PubMed databases. We consider scientific articles and books between 1966 and 2017. Keywords: adolescence, autonomy, bioethics and adolescence, autonomy, ethics, in variants in the English, Portuguese and Spanish languages. Inclusion criteria: scientific articles, books and theses on clinical decision making by the adolescent patient. Exclusion criteria: case reports and articles that did not address the issue. Among 1,590 abstracts, 78 were read in full and 32 were used in this manuscript. Data synthesis: The age at which the individual is able to make decisions is a matter of debate in the literature. The development of a cognitive and psychosocial system is a time-consuming process and the integration of psychological, neuropsychological and neurobiological research in adolescence is fundamental. The ability to mature reflection is not determined by chronological age; in theory, a mature child is able to consent or refuse treatment. Decision-making requires careful and reflective analysis of the main associated factors, and the approach of this problem must occur through the recognition of the maturity and autonomy that exists in the adolescents. To do so, it is necessary to “deliberate” with them. Conclusions: International guidelines recommend that adolescents participate in discussions about their illness, treatment and decision-making. However, there is no universally accepted consensus on how to assess the decision-making ability of these patients. Despite this, when possible, the adolescent should be included in a serious, honest, respectful and sincere process of deliberation.

Affect and Clinical Decision-Making

2018 ◽  
Author(s):  
Jane Heyhoe ◽  
Rebecca Lawton
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Current Knowledge ◽  
Clinical Decision ◽  
Evidence Base ◽  
Empirical Literature ◽  
Affective States ◽  
Psychological Models ◽  
The Individual

In the chapter “Affect and Clinical Decision-Making,” theoretical and empirical literature from within and outside healthcare are drawn on to understand the role of affect in clinical decision-making at the individual and team level. Theories of individual decision-making are summarized and psychological models of decision-making and current knowledge of thought processes are presented to explain the role of affect in judgment and behavior in healthcare settings. Three types of affect: anticipatory affect, incidental affect, and anticipated affect are discussed in detail and used to illustrate how affective states may play a role in different clinical contexts and settings. Gaps in the existing evidence base are identified, and suggestions are made for interventions that might support health professionals to make better decisions.

Can a Discrete Choice Experiment contribute to person-centred healthcare?

2015 ◽  
Vol 3 (4) ◽  
pp. 431 ◽  
Author(s):  
Mette Kjer Kaltoft ◽  
Jesper Bo Neilsen ◽  
Glenn Salkeld ◽  
Jack Dowie
Keyword(s):  
Decision Making ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Clinical Relevance ◽  
Choice Experiment ◽  
Clinical Decision Making ◽  
Individual Preference ◽  
Clinical Decision ◽  
Group Level ◽  
The Individual

In person-centred decision making the relative importance of the considerations that matter to the person is elicited and combined, at the point of decision, with the best estimates available on the performance of the available options on those criteria. Whatever procedure is used to implement this in a clinical decision, average preferences emerging from group or subgroup research cannot contribute directly, since they can have only a statistical relationship with the preferences of the individual person. The precise relationship is knowable by eliciting those of the individual concerned, but there would be little point consulting the averages if this is done. A scan of recent Discrete Choice Experiment (DCE) publications reveals frequent claims that the group-level results can somehow contribute to, or facilitate, better clinical decision making. Typically there are only vague or ambiguous indications of how this could happen, the ambiguity often arising from the use and positioning of the apostrophe in the words persons and patients. Only when the person opts out of preference provision and asks to be treated as ‘average’, can the results of a DCE have clinical relevance in genuinely person-centred healthcare. One cannot derive an ought from an is and one cannot derive an I from a they. DCE researchers should refrain from implying that their results could, let alone should, have any impact on person-centred clinical decisions. Group-level DCE results are clearly conceptually appropriate for health system or service decisions, but the suggestion that they have clinical relevance is a serious deterrent to the development and provision of effective means of individual preference elicitation and specification at the point of decision. Those who wish to foster person-centred care should be alert to the dangers of claims based on group-level analyses such as DCEs.  

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