Against diagnosis

The impact of changing the cut-off threshold of the interferon-gamma (IFN-γ) assay for diagnosing bovine tuberculosis in Ireland

In Ireland, the interferon-gamma (IFN-γ) assay is routinely used as an ancillary test interpreted in parallel with the single intradermal comparative tuberculin test (SICTT) to maximize the detection of bovine tuberculosis (bTB) infected animals. Up until 2018, a positive test result was recorded in the IFN-γ ELISA assay following whole blood stimulation with purified protein derivative (PPD)-bovine (B), PPD-avian (A) and nil sample (N), using the interpretation criteria, B-N > 50 optical density units (OD), B > 100 and B-A > 0. Following a review of available data, the threshold of the B-A component changed to B-A > 80. As predicting the impact of changing the cut-off thresholds for the IFN-γ test de novo is challenging, the aims of this study were to follow animals that initially tested negative using the new IFN-γ assay interpretation criteria and investigate their future risk of disclosure with bTB, with a focus on animals that otherwise would have been removed when using the older interpretation criteria (0 < B-A ≤ 80). Enrolled animals (n = 28,669 cattle from 527 herds) were followed up for two years (2019-2021), or to point of bTB detection or death. At the end of follow-up, 1151 (4.0%) of enrolled animals were bTB cases. The majority of these cases were diagnosed using SICTT (80.5%). The cumulative number of positive animals that would have been removed if the old cut-off (0 < B-A ≤ 80) was used amounted to 1680 cattle (5.9% of the enrolled cohort). Of these, 127 (7.5%) were diagnosed with bTB during follow-up. In contrast, 1024 of the 1151 cattle which subsequently tested positive during the study period following a negative IFN-γ test would not have been identified with the old or new IFN-γ cut-off criteria. Survival analysis showed that animals that would have been removed under the old interpretation criteria were at increased risk of a positive diagnosis with bTB during follow-up compared to other test negative animals. A newly developed risk prediction model (using a Cox proportional hazard model) showed that age, animal number of SICTT tests, number of inconclusive SICTT tests, B-A (IFN-γ assay), B-N (IFN-γ assay), animals from store herds and the percentage of the rest of the herd that were positive during the breakdown were statistically significantly associated with bTB detection. However, inclusion of the IFN-γ OD variables did not show added value in terms of prediction performance of the model.

On the Ethics of Withholding and Withdrawing Unwarranted Diagnoses

The number of diagnoses and the number of persons having diagnoses have increased substantially, and studies indicate that diagnoses are given or upheld even if they are unwarranted, that is, that they do not satisfy professionally accepted diagnostic criteria. In this article, the authors investigate the ethics of withholding and withdrawing unwarranted diagnoses. First, they investigate ethical aspects that make it difficult to withhold and to withdraw such diagnoses. Second, they scrutinize whether there are psychological factors, both in persons/patients and healthcare professionals, making it difficult to withdraw and withhold unwarranted diagnoses. Lastly, they use recent elements of the withholding-versus-withdrawing treatment debate in medical ethics to investigate whether there are any differences between withholding and withdrawing treatment and withdrawing and withholding unwarranted diagnoses. The authors conclude that it is crucial to acknowledge and address all these issues to reduce and avoid unwarranted diagnoses.

Mastering Prognostic Tools: An Opportunity to Enhance Personalized Care and to Optimize Clinical Outcomes in Physical Therapy

In health care, clinical decision making is typically based on diagnostic findings. Rehabilitation clinicians commonly rely on pathoanatomical diagnoses to guide treatment and define prognosis. Targeting prognostic factors is a promising way for rehabilitation clinicians to enhance treatment decision-making processes, personalize rehabilitation approaches, and ultimately improve patient outcomes. This can be achieved by using prognostic tools that provide accurate estimates of the probability of future outcomes for a patient in clinical practice. Most literature reviews of prognostic tools in rehabilitation have focused on prescriptive clinical prediction rules. These studies highlight notable methodological issues and conclude that these tools are neither valid nor useful for clinical practice. This has raised the need to open the scope of research to understand what makes a quality prognostic tool that can be used in clinical practice. Methodological guidance in prognosis research has emerged in the last decade, encompassing exploratory studies on the development of prognosis and prognostic models. Methodological rigor is essential to develop prognostic tools, because only prognostic models developed and validated through a rigorous methodological process should guide clinical decision making. This Perspective argues that rehabilitation clinicians need to master the identification and use of prognostic tools to enhance their capacity to provide personalized rehabilitation. It is time for prognosis research to look for prognostic models that were developed and validated following a comprehensive process before being simplified into suitable tools for clinical practice. New models, or rigorous validation of current models, are needed. The approach discussed in this Perspective offers a promising way to overcome the limitations of most models and provide clinicians with quality tools for personalized rehabilitation approaches.

IMPACT

Prognostic research can be applied to clinical rehabilitation; this Perspective proposes solutions to develop high-quality prognostic models to optimize patient outcomes.

Dediagnosing - a novel framework for making people less ill

Diagnosing constitutes a substantial part of healthcare work and triggers a wide range of actions including the prescription of medicines. Dediagnosing is proposed as a novel framework for removing diagnoses that do not contribute to the reduction of persons' suffering and should be introduced to make people less ill. Dediagnosing comes together with other efforts to reduce overuse, such as deimplementation, deprescribing, decommissioning, and disinvestment. Because diagnoses may influence identity construction and social rights, dediagnosing must be conducted in close collaboration with the patient.

The accuracy of ACTH as a biomarker for pituitary pars intermedia dysfunction in horses: A systematic review and meta-analysis

BACKGROUND

Accuracy of baseline ACTH for the diagnosis of PPID in horses varies between studies.

OBJECTIVES

To estimate the diagnostic accuracy of ACTH as a biomarker for PPID in adult horses and appraise potential causes of heterogeneity.

STUDY DESIGN

Systematic review and meta-analysis.

METHODS

A literature review identified studies reporting diagnostic accuracy data for extraction. Risk of bias was evaluated using QUADAS-2. Two random-effects models, the hierarchical summary receiver operating curve (HSROC) and the bivariate binomial normal model (BBN) were used to pool accuracy measurements. We performed meta-regression using study-level variables. The impact of diagnostic test accuracy on the frequency of false-positive and false-negative results at various pretest probabilities was calculated using the BBN model's accuracy results.

RESULTS

Patient selection and index test evaluation demonstrated significant risk of bias. Mean and 95% confidence intervals for sensitivity and specificity for all studies (n = 11) based upon the HSROC model were (0.72, 95% CI: 0.62 to 0.82) and (0.88, 95% CI: 0.79 to 0.93), respectively. When studies with a common positivity threshold of 35 pg/mL ACTH were evaluated (n = 6), sensitivity and specificity were (0.66, 95% CI:0.54 to 0.77) and (0.87, 95% CI: 0.74 to 0.94). In a hypothetical group of one thousand horses with PPID prevalence of 2%, 20%, and 90%, the frequency of resulting false-positive and false-negatives would be (127 and 7), (104 and 68) and (13 and 306), respectively. Factors leading to increased accuracy were case-control design, clinical reference standard and data-driven choice of ACTH threshold.

MAIN LIMITATIONS

A small number of primary studies (n = 11) were available, demonstrating significant biases.

CONCLUSIONS

Less biased studies examining diagnostic accuracy of ACTH are needed. In horses with a high pretest probability of PPID, ACTH may be a functional "rule-in" test. Baseline ACTH is not recommended for screening purposes or use in horses without clinical signs of PPID.

Subgroups of Long-Term Sick-Listed Based on Prognostic Return to Work Factors Across Diagnoses: A Cross-Sectional Latent Class Analysis

Comorbidity is common among long-term sick-listed and many prognostic factors for return to work (RTW) are shared across diagnoses. RTW interventions have small effects, possibly due to being averaged across heterogeneous samples. Identifying subgroups based on prognostic RTW factors independent of diagnoses might help stratify interventions. The aim of this study was to identify and describe subgroups of long-term sick-listed workers, independent of diagnoses, based on prognostic factors for RTW. Latent class analysis of 532 workers sick-listed for eight weeks was used to identify subgroups based on seven prognostic RTW factors (self-reported health, anxiety and depressive symptoms, pain, self-efficacy, work ability, RTW expectations) and four covariates (age, gender, education, physical work). Four classes were identified: Class 1 (45% of participants) was characterized by favorable scores on the prognostic factors; Class 2 (22%) by high anxiety and depressive symptoms, younger age and higher education; Class 3 (16%) by overall poor scores including high pain levels; Class 4 (17%) by physical work and lack of workplace adjustments. Class 2 included more individuals with a psychological diagnosis, while diagnoses were distributed more proportionate to the sample in the other classes. The identified classes illustrate common subgroups of RTW prognosis among long-term sick-listed individuals largely independent of diagnosis. These classes could in the future assist RTW services to provide appropriate type and extent of follow-up, however more research is needed to validate the class structure and examine how these classes predict outcomes and respond to interventions.

A typology of clinical conditions

In the philosophy of medicine, great attention has been paid to defining disease, yet less attention has been paid to the classification of clinical conditions. These include conditions that look like diseases but are not; conditions that are diseases but that (currently) have no diagnostic criteria; and other types, including those relating to risk for disease. I present a typology of clinical conditions by examining factors important for characterizing clinical conditions. By attending to the types of clinical conditions possible on the basis of these key factors (symptomaticity, dysfunction, and the meeting of diagnostic criteria), I draw attention to how diseases and other clinical conditions as currently classified can be better categorized, highlighting the issues pertaining to certain typology categories. Through detailed analysis of a wide variety of clinical examples, including Alzheimer disease as a test case, I show how nosology, research, and decisions about diagnostic criteria should include normative as well as naturalistically describable factors.

Defining remission of type 2 diabetes in research studies: A systematic scoping review

BACKGROUND

Remission has been identified as a top priority by people with type 2 diabetes. Remission is commonly used as an outcome in research studies; however, a widely accepted definition of remission of type 2 diabetes is lacking. A report on defining remission was published (but not formally endorsed) in Diabetes Care, an American Diabetes Association (ADA) journal. This Diabetes Care report remains widely used. It was the first to suggest 3 components necessary to define the presence of remission: (1) absence of glucose-lowering therapy (GLT); (2) normoglycaemia; and (3) for duration ≥1 year. Our aim is to systematically review how remission of type 2 diabetes has been defined by observational and interventional studies since publication of the 2009 report.

METHODS AND FINDINGS

Four databases (MEDLINE, EMBASE, Cochrane Library, and CINAHL) were searched for studies published from 1 September 2009 to 18 July 2020 involving at least 100 participants with type 2 diabetes in their remission analysis, which examined an outcome of type 2 diabetes remission in adults ≥18 years and which had been published in English since 2009. Remission definitions were extracted and categorised by glucose-lowering therapy, glycaemic thresholds, and duration. A total of 8,966 titles/abstracts were screened, and 178 studies (165 observational and 13 interventional) from 33 countries were included. These contributed 266 definitions, of which 96 were unique. The 2009 report was referenced in 121 (45%) definitions. In total, 247 (93%) definitions required the absence of GLT, and 232 (87%) definitions specified numeric glycaemic thresholds. The most frequently used threshold was HbA1c<42 mmol/mol (6.0%) in 47 (20%) definitions. Time was frequently omitted. In this study, a total of 104 (39%) definitions defined time as a duration. The main limitations of this systematic review lie in the restriction to published studies written in English with sample sizes of over 100. Grey literature was not included in the search.

CONCLUSIONS

We found that there is substantial heterogeneity in the definition of type 2 diabetes remission in research studies published since 2009, at least partly reflecting ambiguity in the 2009 report. This complicates interpretation of previous research on remission of type 2 diabetes and the implications for people with type 2 diabetes. Any new consensus definition of remission should include unambiguous glycaemic thresholds and emphasise duration. Until an international consensus is reached, studies describing remission should clearly define all 3 components of remission.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42019144619.

Screening strategies to identify sepsis in the prehospital setting: a validation study

BACKGROUND

In the prehospital setting, differentiating patients who have sepsis from those who have infection but no organ dysfunction is important to initiate sepsis treatments appropriately. We aimed to identify which published screening strategies for paramedics to use in identifying patients with sepsis provide the most certainty for prehospital diagnosis.

METHODS

We identified published strategies for screening by paramedics through a literature search. We then conducted a validation study in Alberta, Canada, from April 2015 to March 2016. For adult patients (≥ 18 yr) who were transferred by ambulance, we linked records to an administrative database and then restricted the search to patients with infection diagnosed in the emergency department. For each patient, the classification from each strategy was determined and compared with the diagnosis recorded in the emergency department. For all strategies that generated numeric scores, we constructed diagnostic prediction models to estimate the probability of sepsis being diagnosed in the emergency department.

RESULTS

We identified 21 unique prehospital screening strategies, 14 of which had numeric scores. We linked a total of 131 745 eligible patients to hospital databases. No single strategy had both high sensitivity (overall range 0.02-0.85) and high specificity (overall range 0.38-0.99) for classifying sepsis. However, the Critical Illness Prediction (CIP) score, the National Early Warning Score (NEWS) and the Quick Sepsis-Related Organ Failure Assessment (qSOFA) score predicted a low to high probability of a sepsis diagnosis at different scores. The qSOFA identified patients with a 7% (lowest score) to 87% (highest score) probability of sepsis diagnosis.

INTERPRETATION

The CIP, NEWS and qSOFA scores are tools with good predictive ability for sepsis diagnosis in the prehospital setting. The qSOFA score is simple to calculate and may be useful to paramedics in screening patients with possible sepsis.

The Care of Patients With Complex Mood Disorders

This article focuses on some common dilemmas facing clinicians, patients, and families in managing the treatment of complicated mood disorders. Specifically, this article reviews the interaction of depressive states, including unipolar, bipolar, and mixed, with other adversities, including comorbid physical and psychological disorders, personality vulnerabilities, misuse of drugs and alcohol, and social and family problems. These issues are not always clearly differentiated from the depressive illness. Each of these adversities can worsen an existing mood disorder and influence the patient's resolve to persist with a treatment plan. Although this article is not focused strictly on treatment-resistant depression, these coexisting issues make depressive states harder to manage therapeutically. For brevity, the aim of this article has been limited to discussion of some complex situations that psychiatrists in general practice may encounter.

Association Between 6-Week Postdischarge Risk Classification and 12-Month Outcomes After Orthopedic Trauma

Importance

Numerous studies have demonstrated that long-term outcomes after orthopedic trauma are associated with psychosocial and behavioral health factors evident early in the patient's recovery. Little is known about how to identify clinically actionable subgroups within this population.

Objectives

To examine whether risk and protective factors measured at 6 weeks after injury could classify individuals into risk clusters and evaluate whether these clusters explain variations in 12-month outcomes.

Design, Setting, and Participants

A prospective observational study was conducted between July 16, 2013, and January 15, 2016, among 352 patients with severe orthopedic injuries at 6 US level I trauma centers. Statistical analysis was conducted from October 9, 2017, to July 13, 2018.

Main Outcomes and Measures

At 6 weeks after discharge, patients completed standardized measures for 5 risk factors (pain intensity, depression, posttraumatic stress disorder, alcohol abuse, and tobacco use) and 4 protective factors (resilience, social support, self-efficacy for return to usual activity, and self-efficacy for managing the financial demands of recovery). Latent class analysis was used to classify participants into clusters, which were evaluated against measures of function, depression, posttraumatic stress disorder, and self-rated health collected at 12 months.

Results

Among the 352 patients (121 women and 231 men; mean [SD] age, 37.6 [12.5] years), latent class analysis identified 6 distinct patient clusters as the optimal solution. For clinical use, these clusters can be collapsed into 4 groups, sorted from low risk and high protection (best) to high risk and low protection (worst). All outcomes worsened across the 4 clinical groupings. Bayesian analysis shows that the mean Short Musculoskeletal Function Assessment dysfunction scores at 12 months differed by 7.8 points (95% CI, 3.0-12.6) between the best and second groups, by 10.3 points (95% CI, 1.6-20.2) between the second and third groups, and by 18.4 points (95% CI, 7.7-28.0) between the third and worst groups.

Conclusions and Relevance

This study demonstrates that during early recovery, patients with orthopedic trauma can be classified into risk and protective clusters that account for a substantial amount of the variance in 12-month functional and health outcomes. Early screening and classification may allow a personalized approach to postsurgical care that conserves resources and targets appropriate levels of care to more patients.

Diagnosing Middle Ear Pathology in 6- to 9-Month-Old Infants Using Wideband Absorbance: A Risk Prediction Model

PURPOSE

The aim of this study was to develop a risk prediction model for detecting middle ear pathology in 6- to 9-month-old infants using wideband absorbance measures.

METHOD

Two hundred forty-nine infants aged 23-39 weeks (Mdn = 28 weeks) participated in the study. Distortion product otoacoustic emissions and high-frequency tympanometry were tested in both ears of each infant to assess middle ear function. Wideband absorbance was measured at ambient pressure in each participant from 226 to 8000 Hz. Absorbance results from 1 ear of each infant were used to predict middle ear dysfunction, using logistic regression. To develop a model likely to generalize to new infants, the number of variables was reduced using principal component analysis, and a penalty was applied when fitting the model. The model was validated using the opposite ears and with bootstrap resampling. Model performance was evaluated through measures of discrimination and calibration. Discrimination was assessed with the area under the receiver operating characteristic curve (AUC); and calibration, with calibration curves, which plotted actual against predicted probabilities.

RESULTS

AUC of the fitted model was 0.887. The model validated adequately when applied to the opposite ears (AUC = 0.852) and with bootstrap resampling (AUC = 0.874). Calibration was satisfactory, with high agreement between predictions and observed results.

CONCLUSIONS

The risk prediction model had accurate discrimination and satisfactory calibration. Validation results indicate that it may generalize well to new infants. The model could potentially be used in diagnostic and screening settings. In the context of screening, probabilities provide an intuitive and flexible mechanism for setting the referral threshold that is sensitive to the costs associated with true and false-positive outcomes. In a diagnostic setting, predictions could be used to supplement visual inspection of absorbance for individualized diagnoses. Further research assessing the performance and impact of the model in these contexts is warranted.

Progress in Defining Disease: Improved Approaches and Increased Impact

In a series of recent papers, I have made three arguments about how to define "disease" and evaluate and apply possible definitions. First, I have argued that definitions should not be seen as traditional conceptual analyses, but instead as proposals about how to define and use the term "disease" in the future. Second, I have pointed out and attempted to address a challenge for dysfunction-requiring accounts of disease that I call the "line-drawing" problem: distinguishing between low-normal functioning and dysfunctioning. Finally, I have used a dysfunction-requiring approach to argue that some extremely prevalent conditions, such as high blood pressure, high cholesterol, and ductal carcinoma in situ, are not diseases, but instead are risk factors. Four of the papers in this issue directly engage my previous work. In this commentary, I applaud the advances these authors make, address points of disagreement, and make suggestions about where the discussion should go next.

Biological age as a health index for mortality and major age-related disease incidence in Koreans: National Health Insurance Service - Health screening 11-year follow-up study

Purpose

A comprehensive health index is needed to measure an individual's overall health and aging status and predict the risk of death and age-related disease incidence, and evaluate the effect of a health management program. The purpose of this study is to demonstrate the validity of estimated biological age (BA) in relation to all-cause mortality and age-related disease incidence based on National Sample Cohort database.

Patients and methods

This study was based on National Sample Cohort database of the National Health Insurance Service - Eligibility database and the National Health Insurance Service - Medical and Health Examination database of the year 2002 through 2013. BA model was developed based on the National Health Insurance Service - National Sample Cohort (NHIS - NSC) database and Cox proportional hazard analysis was done for mortality and major age-related disease incidence.

Results

For every 1 year increase of the calculated BA and chronological age difference, the hazard ratio for mortality significantly increased by 1.6% (1.5% in men and 2.0% in women) and also for hypertension, diabetes mellitus, heart disease, stroke, and cancer incidence by 2.5%, 4.2%, 1.3%, 1.6%, and 0.4%, respectively (p<0.001).

Conclusion

Estimated BA by the developed BA model based on NHIS - NSC database is expected to be used not only as an index for assessing health and aging status and predicting mortality and major age-related disease incidence, but can also be applied to various health care fields.

Models for estimating the metabolic syndrome biological age as the new index for evaluation and management of metabolic syndrome

Purpose

This study aims to propose a metabolic syndrome (MS) biological age model, through which overall evaluation and management of the health status and aging state in MS can be done easily. Through this model, we hope to provide a novel evaluation and management health index that can be utilized in various health care fields.

Patient and methods

MS parameters from American Heart Association/National Heart, Lung, and Blood Institute guidelines in 2005 were used as biomarkers for the estimation of MS biological age. MS biological age model development was done by analyzing data of 263,828 participants and clinical application of the developed MS biological age was assessed by analyzing the data of 188,886 subjects.

Results

The principal component accounted for 36.1% in male and 38.9% in female of the total variance in the battery of five variables. The correlation coefficient between corrected biological age and chronological age in males and females were 0.711 and 0.737, respectively. Significant difference for mean MS biological age and chronological age between the three groups, normal, at risk and MS, was seen (P<0.001).

Conclusion

For the comprehensive approach in MS management, MS biological age is expected to be additionally utilized as a novel evaluation and management index along with the traditional MS diagnosis.

An integral approach to health science and healthcare

Defining disease and delineating its boundaries is a contested area in contemporary philosophy of medicine. The leading naturalistic theory faces a new round of difficulties related to defining a normal environment alongside normal organismic functioning and to delineating a discrete boundary between risk factors and disease. Normative theories face ongoing and seemingly intractable difficulties related to value pluralism and the problematic relation between theory and practice. In this article, I argue for an integral-as opposed to a hybrid-philosophy of health based on Bernard Lonergan's notion of generalized empirical method that provides a way to settle these difficulties dynamically and comprehensively, both in theory, by orienting functional and statistical investigation toward an explanatory ecological viewpoint, and in practice, by framing critiques in relation to the normativity intrinsic to all human inquiry.

Validation of EGCRISC for Chronic Hepatitis C Infection Screening and Risk Assessment in the Egyptian Population

Chronic HCV infection, a highly endemic disease in Egypt, is usually asymptomatic for decades after infection. Prediction questionnaire tool was proofed to be a valuable, feasible and efficient instrument for the screening of several diseases. We previously developed an Egyptian HCV risk screening tool (EGCRISC). This study aims to validate/modify EGCRISC. A cross-sectional study testing 4579 individuals by EGCRISC as well as ELISA/PCR was performed. The sample was a stratified cluster sampling from urban and rural areas in Upper and Lower Egypt using a proportional allocation technique. The degree of agreement and positive and negative posttest probabilities were calculated. ROC curve was done and the cutoff points were customized for best performance. The total score was further classified into three levels according to the risk load. The mean age of the participants was 41.1±12.2 in whom HCV prevalence was 8.6%. EGCRISC, particularly after modifying the cutoff points, has a good discriminating ability. The degree of agreement was at least 68.1% and the positive posttest probability ranged from 5% to 37.2% whereas the negative posttest probability was in the range 1% to 17%. We conclude that EGCRISC is a valid tool that can potentially screen for HCV infection risk in Egypt and could diminish the demand for mass serologic screening in those apparently at minimal risk. Extensive use of electronic and self- or interviewer-administered risk-based screening strategy may simplify and promote overall screening and detection of HCV dissimilar communities.

Deciding on Interferon-Free Treatment for Chronic Hepatitis C: Updating Liver Stiffness Cut-Off Values to Maximize Benefit

Introduction

In a perspective of economic constraints the prioritizing of patients to IFN-free regimens is mainly based on the determination of liver stiffness by transient elastography (TE). Being a continuous variable the interpretation of TE results requires the identification of cut-off values, to date set to maximize diagnostic accuracy even if such values should be better based on more helpful outcome prediction endpoints.

Aim

To define the TE cut-off values in different clinical scenarios, including new IFN-free regimens, and to balance the clinical benefits versus harms in treated and untreated patients.

Methods

We assessed the accuracy of TE in staging 728 consecutive HCV patients and the distribution of TE values in 1,001 blood donors. Ten experts quantified the expected harm/benefit ratio for 6 scenarios resulting from 2 stages of liver disease (F≥2 or F≥3) and 3 treatment regimens: PEGIFN+ribavirin, PEGIFN+RBV+first-generation protease inhibitor, and IFN-free regimens. The optimal TE cut-off values were identified using the Metz equation.

Results

The estimated mean expected harm/benefit ratio for IFN-free regimens was 1/8.3 in patients with F≥2 and 1/10 in those with F≥3. The resulting optimal cut-off values were respectively 4.5 kPa with sensitivity at 99% and specificity at 12%, and 6.8 kPa with sensitivity at 94% and specificity at 41%. These cut-off values are lower than those maximizing accuracy and allow to reduce the number of false negative results.

Conclusions

The optimal TE cut-off values to prioritize patients for IFN-free regimens, are sensibly lower than those used to maximize diagnostic accuracy.

Integrating Experience, Evidence and Expertise in the Crop Protection Decision Process

Generically, farm-scale crop protection decision making may be characterized as a process beginning with an initial assessment of disease risk followed by the accumulation of evidence related to current risk factors, leading to a risk prediction. What action is then taken depends on the response of the decision owner, taking into account previous experience, advice from trusted sources, alongside policy or legislative constraints on crop protection practice that are intended to mitigate any impacts that may transcend the farm scale. This process has commonalities with decision-making in the strategy of preventive medicine. This article delves into the clinical literature in order to provide a perspective on some recent discussions of shared decision making presented there, discussions that relate to issues also faced in sustainable crop protection.

The science of clinical practice: disease diagnosis or patient prognosis? Evidence about "what is likely to happen" should shape clinical practice

BACKGROUND

Diagnosis is the traditional basis for decision-making in clinical practice. Evidence is often lacking about future benefits and harms of these decisions for patients diagnosed with and without disease. We propose that a model of clinical practice focused on patient prognosis and predicting the likelihood of future outcomes may be more useful.

DISCUSSION

Disease diagnosis can provide crucial information for clinical decisions that influence outcome in serious acute illness. However, the central role of diagnosis in clinical practice is challenged by evidence that it does not always benefit patients and that factors other than disease are important in determining patient outcome. The concept of disease as a dichotomous 'yes' or 'no' is challenged by the frequent use of diagnostic indicators with continuous distributions, such as blood sugar, which are better understood as contributing information about the probability of a patient's future outcome. Moreover, many illnesses, such as chronic fatigue, cannot usefully be labelled from a disease-diagnosis perspective. In such cases, a prognostic model provides an alternative framework for clinical practice that extends beyond disease and diagnosis and incorporates a wide range of information to predict future patient outcomes and to guide decisions to improve them. Such information embraces non-disease factors and genetic and other biomarkers which influence outcome.

SUMMARY

Patient prognosis can provide the framework for modern clinical practice to integrate information from the expanding biological, social, and clinical database for more effective and efficient care.

The value of personalised risk information: a qualitative study of the perceptions of patients with prostate cancer

OBJECTIVE

To explore the experiences of patients with prostate cancer with risk information and their perceptions of the value of personalised risk information in treatment decisions.

DESIGN

A qualitative study was conducted using focus groups. Semistructured interviews explored participants' experiences with using risk information, and their perceptions of the potential value of personalised risk information produced by clinical prediction models.

PARTICIPANTS

English-speaking patients, ages 54-82, diagnosed with prostate cancer within the past 3 years, residing in rural and non-rural geographic locations in Maine (USA), and attending prostate cancer patient support groups.

SETTING

6 focus groups were conducted with 27 patients; separate groups were held for patients with low-risk, medium-risk and high-risk disease defined by National Comprehensive Cancer Network guidelines.

RESULTS

Several participants reported receiving risk information that was imprecise rather than precise, qualitative rather than quantitative, indirect rather than direct and focused on biomarker values rather than clinical outcomes. Some participants felt that personalised risk information could be useful in helping them make better informed decisions, but expressed scepticism about its value. Many participants favoured decision-making strategies that were heuristic-based and intuitive rather than risk-based and deliberative, and perceived other forms of evidence-emotions, recommendations of trusted physicians, personal narratives-as more reliable and valuable in treatment decisions.

CONCLUSIONS

Patients with prostate cancer appear to have little experience using personalised risk information, may favour heuristic-based over risk-based decision-making strategies and may perceive personalised risk information as less valuable than other types of evidence. These decision-making approaches and perceptions represent potential barriers to the clinical use of personalised risk information. Overcoming these barriers will require providing patients with greater exposure to risk information, education about the nature and value of personalised risk information and training in deliberative decision-making strategies. More research is needed to confirm these findings and address these needs.

"What, diagnosis?" Between Bayes and biases

I conducted a personal survey, completely informal, asking groups of doctors during training courses to give me in writing, in a strictly anonymous fashion, a brief operative description of diagnosis. The majority were unfocused and confusing regarding the process and nobody mentioned any probability-based criteria. Objectively, diagnosis is a difficult concept and rich with implications: this is the heart of medical activity and few doctors are able to define it correctly. There exist well-founded reasons to ask ourselves what diagnosis means and how many are the implications and the many environments in which the concept might be declined. We have to accept that even at the end of a complete and exhaustive diagnostic workup, it might not be possible to reach a diagnosis and it is much wiser to admit it rather than giving the patient a label that will abandon them only with extreme difficulty. Whether or not we like it, we behave, even unconsciously, like convinced Bayesians and we should be aware of the fact that the predictive value of your test will vary on how high or low is the presence of the illness. With a very low prevalence, even a very sensitive test might produce an unacceptably high number of false positives. Naturally, it is not necessary to supply a definition of diagnosis to be a good doctor. What counts is that we are aware that the diagnostic process is based on probability and not certainty, we are prone to biases, diagnostic tests can have false positives and false negatives, and having reached a certain threshold of probability and trust in diagnosis we should decide, with our patients, what to do or not do.

Using an emic and etic ethnographic technique in a grounded theory study of information use by practice nurses in New Zealand

This paper draws lessons from the use of an emic–etic ethnographical technique in a grounded theory study of how New Zealand practice nurses use information. The technique was used to heighten theoretical sensitivity in this study. As a nurse practitioner, I (the lead author) could not step out of my emic perspective to provide an etic perspective of my own general practice. From my emic embodied subjectivity I constructed my work environment to fit with best practice. Conversely, in four other general practices, my lack of personal connection protected an etic sense of disembodiment. New insights into mental models guiding the emic and etic roles of ethnography are suggested. Emic and etic perspectives, along with embodied and disembodied feelings, are not binary opposites but rather sit along a philosophical continuum. Their position on this continuum depends on the role and relationships of the researcher(s) in the social and cultural context of the area of inquiry.

Developing and validating a scoring tool for identifying people who inject drugs at increased risk of hepatitis C virus infection

Objectives To develop and validate a scoring tool based on demographic and injecting risk behaviours to identify those who require additional, non-routine serological screening for hepatitis C virus (HCV) by assessing their personal risk. Design Cross-sectional and prospective cohorts. Setting People who inject drugs (PWID) and attended Needle and Syringe Programs (NSP) in Australia during the period from 1998 to 2008. Participants Cross-sectional data included 16 127 PWID who attended NSP in Australia. Prospective data included 215 HCV-negative PWID who were recruited through street-based outreach, methadone clinics in Australia. Primary and secondary outcome measures HCV seroprevalence in the cross-sectional and HCV seroconversions in the prospective data sets. Results Current study included 16 127 PWID who attended NSP in Australia. Type of drug last injected, frequency and duration of injecting, sharing needles and syringes or other injecting equipment and imprisonment history were associated with HCV infection in all age groups. Strong relationships between an individual's 'HCV score' and their risk of testing HCV antibody positive were observed. An estimated 78% (95% CI 75% to 81%), 82% (95% CI 80% to 84%), 80% (95% CI 78% to 82%) and 80% (95% CI 77% to 82%) of HCV infections across the age groups (<25, 25-29, 30-39 and ≥40 years) would be avoided if participants in the upper four quintiles of HCV scores fell instead into the lowest quintile. Conclusions Knowledge of HCV status has important implications for public health and care and treatment. Risk assessment strategies may assist in alerting PWID who are at increased risk of HCV infection to present for testing.

Addressing the ethical, policy, and social challenges of preclinical Alzheimer disease

Research suggests that Alzheimer disease (AD) pathophysiology begins prior to the clinical expression of the disease and that biomarker measures may provide direct evidence of this process. As a result, it may be possible to uncouple the diagnosis of AD from the clinical expression of the disease. The shifting boundaries between normal brain aging and disease present 3 challenges: 1) establishing guidelines for researchers and clinicians to safely and effectively communicate the diagnosis of preclinical AD, 2) setting up a process that effectively translates this diagnosis into practice and policy, and 3) adapting laws, regulations, and professional practices to the diagnosis of preclinical AD. The field of genetic testing for AD suggests how to balance a patient's desire to know his or her risk of developing dementia with a clinician's desire to mitigate the potential harms of that information. The development of diagnostic and treatment guidelines for other diseases of aging, such as cardiovascular disease, suggests the need for a National Alzheimer's Education Program to develop policies and procedures to translate preclinical AD into both clinical practice and policy. Revisions are needed to laws, regulations, and professional practices governing driving, financial management and planning, and privacy and confidentiality.

Predisease: when does it make sense?

Screening often leads to finding conditions that are not at the stage or level that would classify them as disease but, at the same time, are not at a stage or level at which people can be declared entirely disease free. These "in-between" states have sometimes been designated as "predisease." Examples include precancerous lesions, increased intraocular pressure ("preglaucoma"), prediabetes, and prehypertension. When the goal of preventing adverse health outcomes is kept in mind, this review poses the idea that "predisease" as a category on which to act makes sense only if the following 3 conditions are met. First, the people designated as having predisease must be far more likely to develop disease than those not so designated. Second, there must be a feasible intervention that, when targeted to people with predisease, effectively reduces the likelihood of developing disease. Third, the benefits of intervening on predisease must outweigh the harms in the population. A systematic review of screening guidelines (published in 2003-2010) for 4 sample conditions (cervical cancer, glaucoma, diabetes, and hypertension) is included to assess whether they address these issues, followed by a discussion of the framework questions as they pertain to each condition.

Checklists to reduce diagnostic errors

Diagnostic errors are common and can often be traced to physicians' cognitive biases and failed heuristics (mental shortcuts). A great deal is known about how these faulty thinking processes lead to error, but little is known about how to prevent them. Faulty thinking plagues other high-risk, high-reliability professions, such as airline pilots and nuclear plant operators, but these professions have reduced errors by using checklists. Recently, checklists have gained acceptance in medical settings, such as operating rooms and intensive care units. This article extends the checklist concept to diagnosis and describes three types of checklists: (1) a general checklist that prompts physicians to optimize their cognitive approach, (2) a differential diagnosis checklist to help physicians avoid the most common cause of diagnostic error--failure to consider the correct diagnosis as a possibility, and (3) a checklist of common pitfalls and cognitive forcing functions to improve evaluation of selected diseases. These checklists were developed informally and have not been subjected to rigorous evaluation. The purpose of this article is to argue for the further investigation and revision of these initial attempts to apply checklists to the diagnostic process. The basic idea behind checklists is to provide an alternative to reliance on intuition and memory in clinical problem solving. This kind of solution is demanded by the complexity of diagnostic reasoning, which often involves sense-making under conditions of great uncertainty and limited time.

Developing and validating a risk scoring tool for chlamydia infection among sexual health clinic attendees in Australia: a simple algorithm to identify those at high risk of chlamydia infection

OBJECTIVE

To develop and validate a risk scoring tool to identify those who are at increased risk of chlamydia infection.

METHODS

We used demographic data, sexual behaviour information and chlamydia positivity results from more than 45,000 individuals who attended Sydney Sexual Health Centre between 1998 and 2009. Participants were randomly allocated to either the development or internal validation data set. Using logistic regression, we created a prediction model and weighted scoring system using the development data set and calculated the odds ratio of chlamydia positivity for participants in successively higher quintiles of score. The internal validation data set was used to evaluate the performance characteristics of the model for five quintiles of risk scores including population attributable risk, sensitivity and specificity.

RESULTS

In the prediction model, inconsistent condom use, increased number of sexual partners in last 3 months, genital or anal symptoms and presenting to the clinic for sexually transmitted infections screening or being a contact of a sexually transmitted infection case were consistently associated with increased risk of chlamydia positivity in all groups. High scores (upper quintiles) were significantly associated with increased risk of chlamydia infection. A cut-point score of 20 or higher distinguished a increased risk group with a sensitivity of 95%, 67% and 79% among heterosexual men, women and men who have sex with men (MSM), respectively.

CONCLUSION

The scoring tool may be included as part of a health promotion and/or clinic website to prompt those who are at increased risk of chlamydia infection, which may potentially lead to increased uptake and frequency of testing.

Successful holistic management of type 2 diabetes with depression: a very personal story

We used illness narrative methods to evaluate the retrospective illness story of a bereaved woman who has recovered from type 2 diabetes and depression with comorbid hypertension, hyperlipidemia, vertigo, and obesity. Her spoken illness story was obtained with a single interview question: What happened? Our findings show that the patient searched for and found personal meaning in her illness. The finding of meaning in her illness appears to have supported her efforts to adopt more positive health beliefs and health behaviors. Although she received excellent health care throughout her illness, she attributes her return to good health to spiritual growth. We discuss the practice implications of this patient's illness story for clinicians who seek new insights into patients who have complex illness stories.

Perspective: Whither the problem list? Organ-based documentation and deficient synthesis by medical trainees

The author argues that the well-formulated problem list is essential for both organizing and evaluating diagnostic thinking. He considers evidence of deficiencies in problem lists in the medical record. He observes a trend among medical trainees toward organizing notes in the medical record according to lists of organ systems or medical subspecialties and hypothesizes that system-based documentation may undermine the art of problem formulation and diagnostic synthesis. Citing research linking more sophisticated problem representation with diagnostic success, he suggests that documentation style and clinical reasoning are closely connected and that organ-based documentation may predispose trainees to several varieties of cognitive diagnostic error and deficient synthesis. These include framing error, premature or absent closure, failure to integrate related findings, and failure to recognize the level of diagnostic resolution attained for a given problem. He acknowledges the pitfalls of higher-order diagnostic resolution, including the application of labels unsupported by firm evidence, while maintaining that diagnostic resolution as far as evidence permits is essential to both rational care of patients and rigorous education of learners. He proposes further research, including comparison of diagnostic efficiency between organ- and problem-oriented thinkers. He hypothesizes that the subspecialty-based structure of academic medical services helps perpetuate organ-system-based thinking, and calls on clinical educators to renew their emphasis on the formulation and documentation of complete and precise problem lists and progressively refined diagnoses by trainees.

Perspective: Uses and misuses of thresholds in diagnostic decision making

The concept of thresholds plays a vital role in decisions involving the initiation, continuation, and completion of diagnostic testing. Much research has focused on the development of explicit thresholds, in the form of practice guidelines and decision analyses. However, these tools are used infrequently; most medical decisions are made at the bedside, using implicit thresholds. Study of these thresholds can lead to a deeper understanding of clinical decision making. The authors examine some factors constituting individual clinicians' implicit thresholds. They propose a model for static thresholds using the concept of situational gravity to explain why some thresholds are high, and some low. Next, they consider the hypothetical effects of incorrect placement of thresholds (miscalibration) and changes to thresholds during diagnosis (manipulation). They demonstrate these concepts using common clinical scenarios. Through analysis of miscalibration of thresholds, the authors demonstrate some common maladaptive clinical behaviors, which are nevertheless internally consistent. They then explain how manipulation of thresholds gives rise to common cognitive heuristics including premature closure and anchoring. They also discuss the case where no threshold has been exceeded despite exhaustive collection of data, which commonly leads to application of the availability or representativeness heuristics. Awareness of implicit thresholds allows for a more effective understanding of the processes of medical decision making and, possibly, to the avoidance of detrimental heuristics and their associated medical errors. Research toward accurately defining these thresholds for individual physicians and toward determining their dynamic properties during the diagnostic process may yield valuable insights.

The trivialization of diagnosis

Although it is widely recognized that diagnosis plays a central role in clinical medicine, in recent years the primacy of diagnosis has come under attack from several sources. 1. "Billable terms" are replacing traditional medical diagnoses. The former are based on International Classification of Diseases lists, which include many non-diagnoses such as symptoms and signs. 2. Diagnosis often gets short shrift because of the perceived urgency of discharge. 3. The problem oriented record, in practice, has frequently led to a shift in emphasis from synthesis of findings to fragmentation of problems. 4. Presumptive diagnoses frequently metamorphose into established diagnoses in medical records, even if incorrect. 5. A number of authors have apparently disparaged the importance of diagnosis. Nonetheless, it is clear that diagnosis must continue to play a central role in clinical medicine. We propose several ways by which we can resist these forces and assure that diagnosis retains its appropriate position of primacy.

Development and validation of a patient self-assessment score for diabetes risk

BACKGROUND

National guidelines disagree on who should be screened for undiagnosed diabetes. No existing diabetes risk score is highly generalizable or widely followed.

OBJECTIVE

To develop a new diabetes screening score and compare it with other available screening instruments (Centers for Disease Control and Prevention, American Diabetes Association, and U.S. Preventive Services Task Force guidelines; 2 American Diabetes Association risk questionnaires; and the Rotterdam model).

DESIGN

Cross-sectional data.

SETTING

NHANES (National Health and Nutrition Examination Survey) 1999 to 2004 for model development and 2005 to 2006, plus a combined cohort of 2 community studies, ARIC (Atherosclerosis Risk in Communities) Study and CHS (Cardiovascular Health Study), for validation.

PARTICIPANTS

U.S. adults aged 20 years or older.

MEASUREMENTS

A risk-scoring algorithm for undiagnosed diabetes, defined as fasting plasma glucose level of 7.0 mmol/L (126 mg/dL) or greater without known diabetes, was developed in the development data set. Logistic regression was used to determine which participant characteristics were independently associated with undiagnosed diabetes. The new algorithm and other methods were evaluated by standard diagnostic and feasibility measures.

RESULTS

Age, sex, family history of diabetes, history of hypertension, obesity, and physical activity were associated with undiagnosed diabetes. In NHANES (ARIC/CHS), the cut-point of 5 or more points selected 35% (40%) of persons for diabetes screening and yielded a sensitivity of 79% (72%), specificity of 67% (62%), positive predictive value of 10% (10%), and positive likelihood ratio of 2.39 (1.89). In contrast, the comparison scores yielded a sensitivity of 44% to 100%, specificity of 10% to 73%, positive predictive value of 5% to 8%, and positive likelihood ratio of 1.11 to 1.98.

LIMITATION

Data during pregnancy were not available.

CONCLUSION

This easy-to-implement diabetes screening score seems to demonstrate improvements over existing methods. Studies are needed to evaluate it in diverse populations in real-world settings.

PRIMARY FUNDING SOURCE

Clinical and Translational Science Center at Weill Cornell Medical College.

Development and validation of a patient self-assessment score for diabetes risk

BACKGROUND

National guidelines disagree on who should be screened for undiagnosed diabetes. No existing diabetes risk score is highly generalizable or widely followed.

OBJECTIVE

To develop a new diabetes screening score and compare it with other available screening instruments (Centers for Disease Control and Prevention, American Diabetes Association, and U.S. Preventive Services Task Force guidelines; 2 American Diabetes Association risk questionnaires; and the Rotterdam model).

DESIGN

Cross-sectional data.

SETTING

NHANES (National Health and Nutrition Examination Survey) 1999 to 2004 for model development and 2005 to 2006, plus a combined cohort of 2 community studies, ARIC (Atherosclerosis Risk in Communities) Study and CHS (Cardiovascular Health Study), for validation.

PARTICIPANTS

U.S. adults aged 20 years or older.

MEASUREMENTS

A risk-scoring algorithm for undiagnosed diabetes, defined as fasting plasma glucose level of 7.0 mmol/L (126 mg/dL) or greater without known diabetes, was developed in the development data set. Logistic regression was used to determine which participant characteristics were independently associated with undiagnosed diabetes. The new algorithm and other methods were evaluated by standard diagnostic and feasibility measures.

RESULTS

Age, sex, family history of diabetes, history of hypertension, obesity, and physical activity were associated with undiagnosed diabetes. In NHANES (ARIC/CHS), the cut-point of 5 or more points selected 35% (40%) of persons for diabetes screening and yielded a sensitivity of 79% (72%), specificity of 67% (62%), positive predictive value of 10% (10%), and positive likelihood ratio of 2.39 (1.89). In contrast, the comparison scores yielded a sensitivity of 44% to 100%, specificity of 10% to 73%, positive predictive value of 5% to 8%, and positive likelihood ratio of 1.11 to 1.98.

LIMITATION

Data during pregnancy were not available.

CONCLUSION

This easy-to-implement diabetes screening score seems to demonstrate improvements over existing methods. Studies are needed to evaluate it in diverse populations in real-world settings.

PRIMARY FUNDING SOURCE

Clinical and Translational Science Center at Weill Cornell Medical College.

A theory of health science and the healing arts based on the philosophy of Bernard Lonergan

This paper represents a preliminary investigation relating Bernard Lonergan's thought to health science and the healing arts. First, I provide background for basic elements of Lonergan's theoretical terminology that I employ. As inquiry is the engine of Lonergan's method, next I specify two questions that underlie medical insights and define several terms, including health, disease, and illness, in relation to these questions. Then I expand the frame of reference to include all disciplines involved in the cycle of clinical interaction under the heading health science and the healing arts. Finally, I analyze the cycle of clinical interaction in terms of Lonergan's cognitive theory. I compare and contrast my analysis, based on Lonergan, with that of Pellegrino, Thomasma and Sulmasy as I proceed. In closing, I comment briefly on the next stage of this project regarding Lonergan's theory of the human good in relation to the practice of the healing arts.