[Diagnostic approach to prolonged fevers amongst adults in primary care]. / Approche diagnostique des fièvres traînantes de l'adulte en médecine de première ligne.

The article seeks to explore: (1) the necessity to import hospital-based fever management tactics into general practice; and (2) the soundness of the principle of parsimony in clinical medicine. The discussion expands on the obstacles leading to an unexplained fever by emphasising on White's Law and the limitations of academic definitions. The article tries to keep a practical orientation by recalling the difficulty of "functional hyperthermia" as well as the choice of routine diagnostic examinations. The discussion also focuses on the modes of inference in general medicine, on clinical inertia and "substantialism" as a standard of care.

L'article s'interroge : (1) sur la nécessité d'importer ou non en médecine générale les tactiques hospitalières de prise en charge de la fièvre; (2) sur le bien-fondé du principe d'économie des hypothèses en médecine clinique. La discussion s'étend sur les obstacles permettant de conclure à une fièvre inexpliquée en insistant sur la loi de White et sur les limites des définitions académiques. L'article essaye de conserver une orientation pratique en rappelant la difficulté que constituent les «hyperthermies fonctionnelles¼ tout comme le choix des examens diagnostiques. La discussion porte également sur les modes d'inférences en médecine générale, l'inertie clinique et le «substantialisme¼ comme norme de soin.

How practitioners integrate decision triggers with existing metrics in conservation monitoring.

Decision triggers are defined thresholds in the status of monitored variables that indicate when to undertake management, and avoid undesirable ecosystem change. Decision triggers are frequently recommended to conservation practitioners as a tool to facilitate evidence-based management practices, but there has been limited attention paid to how practitioners are integrating decision triggers into existing monitoring programs. We sought to understand whether conservation practitioners' use of decision triggers was influenced by the type of variables in their monitoring programs. We investigated this question using a practitioner-focused workshop involving a structured discussion and review of eight monitoring programs. Among our case studies, direct measures of biodiversity (e.g. native species) were more commonly monitored, but less likely to be linked to decision triggers (10% with triggers) than measures being used as surrogates (54% with triggers) for program objectives. This was because decision triggers were associated with management of threatening processes, which were often monitored as a surrogate for a biodiversity asset of interest. By contrast, direct measures of biodiversity were more commonly associated with informal decision processes that led to activities such as management reviews or external consultation. Workshop participants were in favor of including more formalized decision triggers in their programs, but were limited by incomplete ecological knowledge, lack of appropriately skilled staff, funding constraints, and/or uncertainty regarding intervention effectiveness. We recommend that practitioners consider including decision triggers for discussion activities (such as external consultation) in their programs as more than just early warning points for future interventions, particularly for direct measures. Decision triggers for discussions should be recognized as a critical feature of monitoring programs where information and operational limitations inhibit the use of decision triggers for interventions.

Reasoning in psychosis: risky but not necessarily hasty.

INTRODUCTION: A liberal acceptance (LA) threshold for hypotheses has been put forward to explain the well-replicated "jumping to conclusions" (JTC) bias in psychosis, particularly in patients with paranoid symptoms. According to this account, schizophrenia patients rest their decisions on lower subjective probability estimates. The initial formulation of the LA account also predicts an absence of the JTC bias under high task ambiguity (i.e., if more than one response option surpasses the subjective acceptance threshold). METHODS: Schizophrenia patients (n = 62) with current or former delusions and healthy controls (n = 30) were compared on six scenarios of a variant of the beads task paradigm. Decision-making was assessed under low and high task ambiguity. Along with decision judgments (optional), participants were required to provide probability estimates for each option in order to determine decision thresholds (i.e., the probability the individual deems sufficient for a decision). RESULTS: In line with the LA account, schizophrenia patients showed a lowered decision threshold compared to controls (82% vs. 93%) which predicted both more errors and less draws to decisions. Group differences on thresholds were comparable across conditions. At the same time, patients did not show hasty decision-making, reflecting overall lowered probability estimates in patients. CONCLUSIONS: Results confirm core predictions derived from the LA account. Our results may (partly) explain why hasty decision-making is sometimes aggravated and sometimes abolished in psychosis. The proneness to make risky decisions may contribute to the pathogenesis of psychosis. A revised LA account is put forward.

One-class model with two decision thresholds for the rapid detection of cashew nuts adulteration by other nuts.

A green screening method to determine cashew nut adulteration with Brazilian nut, pecan nut, macadamia nut and peanut was proposed. The method was based on the development of a one-class soft independent modelling of class analogy (SIMCA) model for non-adulterated cashew nuts using near-infrared (NIR) spectra obtained with portable equipment. Once the model is established, the assignment of unknown samples depends on the threshold established for the authentic class, which is a key aspect in any screening approach. The authors propose innovatively to define two thresholds: lower model distance limit and upper model distance limit. Samples with distances below the lower threshold are assigned as non-adulterated with a 100% probability; samples with distance values greater than the upper threshold are assigned as adulterated with a 100% probability; and samples with distances within these two thresholds will be considered uncertain and should be submitted to a confirmatory analysis. Thus, the possibility of error in the sample assignment significantly decreases. In the present study, when just one threshold was defined, values greater than 95% for the optimized threshold were obtained for both selectivity and specificity. When two class thresholds were defined, the percentage of samples with uncertain assignment changes according to the adulterant considered, highlighting the case of peanuts, in which 0% of uncertain samples was obtained. Considering all adulterants, the number of samples that were submitted to a confirmatory analysis was quite low, 5 of 224 adulterated samples and 3 of 56 non-adulterated samples.

Decision thresholds with genetic testing.

A genetic test is a test for the presence or absence of a genetic mutation. A positive test outcome that reveals a mutation associated with increased risk for a disease may lead a patient to seek preventive treatment provided that the penetrance (probability of developing the disease given the mutation) is sufficiently high. We derive the test threshold and the test-treatment threshold, which confine the mutation probability interval for the use of the genetic test. Test and treatment costs as well as a low penetrance rate of the mutation narrow this interval. We illustrate the model with parameters of the test for BRCA1 and BRCA2 genes as well as of preventive treatment options for breast cancer.

The impact of a rapid home test on telehealth decision-making for influenza: a clinical vignette study.

BACKGROUND: Home testing for influenza has the potential to aid triage and management decisions for patients with influenza-like illness. As yet, little is known about the effect of the home influenza testing on clinical decision-making via telehealth. The goal of this study was to determine the clinicians' decision thresholds for influenza and whether the availability of a home influenza test affects clinical decisions. METHODS: We identified primary care physicians at 4 different sites in the US, largely via in-person continuing education meetings. Clinicians were asked for each vignette whether to treat empirically ("rule in"), ask the patient come to the clinic for further evaluation ("test"), or neither test nor treat ("rule out"). They were then given the results of a home influenza test, and were again asked to select from these three options. We measured the agreement of physician estimates of the likelihood of influenza with the probability based on a clinical prediction model. The test and treatment thresholds of influenza were determined based on mixed-effect logistic regressions. RESULTS: In total, 202 clinicians made 570 sets of clinical decisions. Agreement between estimated and actual probability of influenza was fair. The test and treatment thresholds were 24% (95% CI: 22% to 25%) and 63% (95% CI: 58% to 65%) before revealing the actual likelihood of influenza. After providing the results of a home flu test the thresholds were similar, 26% (95% CI: 24% to 29%) and 59% (95% CI: 56% to 62%). However, approximately half of clinicians changed their cliical management decision after being given the home influenza test result, largely by categorizing more patients in the "rule out" and "rule in" groups, and reducing the need for in-person evaluation from 41% of patients to only 20%. CONCLUSION: In the context of a telehealth visit for a patient with influenza-like illness, we identified a test threshold of approximately 25% and a treatment threshold of approximately 60%. Adding the home influenza test results reduced uncertainty and significantly decreased the need for in-person visits.

Decision Thresholds for Medical Tests Under Ambiguity Aversion.

We consider medical decision-making under diagnostic and therapeutic uncertainty and analyze how ambiguity aversion affects the decisions to test and treat, thereby contributing to the understanding of the observed heterogeneity of such decisions. We show that under diagnostic ambiguity (i.e., the probability of disease is ambiguous), prior testing becomes more attractive if the default option is no treatment and less so if the default option is treatment. Conversely, with therapeutic ambiguity (i.e., the probability of a successful treatment is ambiguous), ambiguity aversion reduces the tolerance toward treatment failure so that the test option is chosen at a lower probability of failure. We differentiate between conditional and unconditional ambiguity aversion and show that this differentiation has implications for the propensity to test. We conclude by discussing the normative scope of ambiguity aversion for the recommendations and decisions of regulatory bodies.

Application of Noninvasive Tools to Decide the Need for Beta-Blockers for Variceal Bleeding Prophylaxis in Compensated Advanced Liver Disease: A Decision Curve Analysis.

Background and aims: Noninvasive tools (NITs) reliably categorise patients with compensated advanced chronic liver disease (cACLD) into high-risk and low-risk group for harbouring varices needing treatment. Here, we assess the ability of these NITs to predict the need for nonselective beta-blockers at baseline based on risk of variceal bleeding (VB) on follow-up. Methods: This was a retrospective multicentre analysis of patients with cACLD categorised at baseline into different risk groups by NITs (Baveno-VI, expanded Baveno-VI, platelet-albumin, platelet-model for end-stage liver disease (MELD) and anticipate study platelet criteria) and by endoscopy (high risk vs low risk/no varices). VB event rates on follow-up were estimated in different risk strata. Decision curve analysis (DCA) was used to estimate the benefit of administering nonselective beta-blockers (NSBB) using NITs over endoscopic classification at different threshold probabilities of VB event rates and estimating the number needed to treat (NNT) to identify one additional bleeder over endoscopy. Results: A total of 1284 patients (mean age: 44.7 ± 13.5 years, 72.4% males) of hepatitis B (29.2%), nonalcoholic fatty liver disease (24.9%), hepatitis C (20.1%), and alcohol (17.5%)-related cACLD were included with 323 (25.2%) having high-risk varices. Ninety-eight (7.6%) patients developed VB over a median follow-up of 20 (9-35) months. The 1-year and 3-year rate of VB with all NITs was 5.7-7.4% and 13.2-16.4% among high-risk and 0-2.3% and 0-5% among low-risk subgroups, respectively (P < 0.001) in both viral and nonviral aetiologies. Among patients classified as low risk on Baveno-VI criteria, none developed VB on follow-up. At thresholds of <3% event rate of VB, Baveno-VI (NNT-176), platelet-albumin (NNT-576) and anticipate platelet (NNT-233) criteria were superior, whereas endoscopic stratification was superior above this event rate on DCA. Conclusions: The use of both elastography and blood-based NITs at baseline can accurately identify the need for NSBB for VB prophylaxis in patients of cACLD on follow-up.

The treatment decision under uncertainty: The effects of health, wealth and the probability of death.

Medical treatment reduces diagnostic risk, increases therapeutic risk and lowers the probability of death. This paper analyzes the effects of initial health, wealth and the probability of death on the propensity to treat under diagnostic and therapeutic risk. It shows that treatment propensity increases with the probability of death, but can decrease with the severity of illness. The effect of wealth depends on the cross-derivative of the utility function with respect to health and wealth. These results have implications for treatment decisions at the end of life.

Threshold analysis in the presence of both the diagnostic and the therapeutic risk.

The well-established a priori probability of illness threshold in medical decision making, introduced by Pauker and Kassirer (N Engl J Med 293:229-234, 1975; N Engl J Med 302:1109-1117, 1980), involves the diagnostic risk only. We generalize the threshold analysis by adding the therapeutic risk, i.e., in accounting for the risk that a treatment might sometimes fail. We derive a priori probability of illness threshold as a function of the probability of successful treatment, as well as the inverted function, where the successful treatment probability threshold is a function of the a priori probability of illness. The thresholds in the general model are higher than those in the special cases where one of the two risks is absent. Applications show that the changes in the thresholds can be substantial. Our general model might explain empirical findings of much higher thresholds than the Pauker-Kassirer model suggests.

Diagnosis and treatment of community-acquired pneumonia in patients with acute cough: a quantitative study of decision thresholds in primary care.

BACKGROUND: Test and treatment thresholds have not yet been described for decision-making regarding the likelihood of pneumonia in patients with acute cough. AIM: To determine decision thresholds in the management of patients with acute cough. DESIGN AND SETTING: Set among primary care physicians attending meetings in the US and Switzerland, using data from a prospective cohort of primary care patients. METHOD: Clinical vignettes were used to study the clinical decisions of physicians regarding eight patients with cough that varied by six signs and symptoms. The probability of community-acquired pneumonia (CAP) was determined for each vignette based on a multivariate model. A previously published approach based on logistic regression was used to determine test and treatment thresholds. RESULTS: In total, 256 physicians made 764 clinical decisions. Initial physician estimates systematically overestimated the likelihood of CAP; 75% estimating a higher probability than that predicted by the multivariate model. Given the probability of CAP from a multivariate model, 16.7% (125 of 749) changed their decision from 'treat' to 'test' or 'test' to 'rule out', whereas only 3.5% (26/749) changed their decision from 'rule out' to 'test' or 'test' to 'treat'. Test and treatment thresholds were 9.5% (95% confidence interval (CI) = 8.7 to 10.5) and 43.1% (95% CI = 40.1 to 46.4) and were updated to 12.7% (95% CI = 11.7 to 13.8) and 51.3% (95% CI = 48.3 to 54.9) once the true probability of CAP was given. Test thresholds were consistent between subgroups. Treatment thresholds were higher if radiography was available, for Swiss physicians, and for non-primary care physicians. CONCLUSION: Test and treatment thresholds for CAP in patients with acute cough were 9.5% and 43.1%, respectively. Physicians tended to overestimate the likelihood of CAP, and providing information from a clinical decision rule (CDR) changed about 1 in 6 clinical decisions.

Distinct mechanisms mediate speed-accuracy adjustments in cortico-subthalamic networks.

Optimal decision-making requires balancing fast but error-prone and more accurate but slower decisions through adjustments of decision thresholds. Here, we demonstrate two distinct correlates of such speed-accuracy adjustments by recording subthalamic nucleus (STN) activity and electroencephalography in 11 Parkinson's disease patients during a perceptual decision-making task; STN low-frequency oscillatory (LFO) activity (2-8 Hz), coupled to activity at prefrontal electrode Fz, and STN beta activity (13-30 Hz) coupled to electrodes C3/C4 close to motor cortex. These two correlates differed not only in their cortical topography and spectral characteristics but also in the relative timing of recruitment and in their precise relationship with decision thresholds. Increases of STN LFO power preceding the response predicted increased thresholds only after accuracy instructions, while cue-induced reductions of STN beta power decreased thresholds irrespective of instructions. These findings indicate that distinct neural mechanisms determine whether a decision will be made in haste or with caution.