Band 6, Heft 3

Skeletal myopathies have been suggested as a non-cardiac cause of elevations of cardiac troponin (cTn), particularly cardiac troponin T (cTnT). This is of major clinical relevance and concern as cTn plays a major role in the early diagnosis of myocardial infarction (MI). While both the incidence as well as the true pathophysiology (cardiac versus non-cardiac) underlying elevations in cTn in skeletal myopathies remain largely unknown, re-expression of cTnT in regenerating adult skeletal muscle has been suggested as a possible contributor. However, unequivocal protein characterization in skeletal muscle and quantification of the relative amounts of this possible signal versus the cTn signal derived from true cardiomyocyte injury remains elusive. Alternatively, minor cross-reactivity of the cTnT (and possibly at times also cTnI) detection and capture antibodies used in current monoclonal immunoassays with the skeletal troponin T or I isoform may be considered. Both would represent “false positive” elevations from a clinical perspective and would need to be reliably differentiated from “true positive elevations” from subclinical cardiomyocyte injury not detectable by currently available imaging techniques such as echocardiography and contrast enhanced magnetic resonance imaging (MRI), which have at least a 5 times lower sensitivity for cardiomyocyte injury. This review aims to explore the currently available data, its methodological limitations and provide guidance to clinicians to avoid misinterpretation of cTn concentrations.

The toughest challenge OMICs face is that they provide extremely high molecular resolution but poor spatial information. Understanding the cellular/histological context of the overwhelming genetic data is critical for a full understanding of the clinical behavior of a malignant tumor. Digital pathology can add an extra layer of information to help visualize in a spatial and microenvironmental context the molecular information of cancer. Thus, histo-genomics provide a unique chance for data integration. In the era of a precision medicine, a four-dimensional (4D) (temporal/spatial) analysis of cancer aided by digital pathology can be a critical step to understand the evolution/progression of different cancers and consequently tailor individual treatment plans. For instance, the integration of molecular biomarkers expression into a three-dimensional (3D) image of a digitally scanned tumor can offer a better understanding of its subtype, behavior, host immune response and prognosis. Using advanced digital image analysis, a larger spectrum of parameters can be analyzed as potential predictors of clinical behavior. Correlation between morphological features and host immune response can be also performed with therapeutic implications. Radio-histomics, or the interface of radiological images and histology is another emerging exciting field which encompasses the integration of radiological imaging with digital pathological images, genomics, and clinical data to portray a more holistic approach to understating and treating disease. These advances in digital slide scanning are not without technical challenges, which will be addressed carefully in this review with quick peek at its future.

Error resulting from missed, delayed, or wrong diagnoses is estimated to occur in 10–15% of ambulatory and inpatient encounters, leading to serious harm in around half of such cases. When it comes to conceptualizing diagnostic error, most research has focused on factors pertaining to: (a) physician cognition and (b) ergonomic or systems factors related to the physician’s working environment. A third factor – the role of patients in diagnostic processes – remains relatively under-investigated. Yet, as a growing number of researchers acknowledge, patients hold unique knowledge about themselves and their healthcare experience, and may be the most underutilized resource for mitigating diagnostic error. This opinion article examines recent findings from patient surveys about sharing visit notes with patients online. Drawing on these survey results, we suggest three ways in which sharing visit notes with patients might enhance diagnostic processes: (1) avoid delays and missed diagnoses by enhancing timely follow up of recommended tests, results, and referrals; (2) identify documentation errors that may undermine diagnostic accuracy; and (3) strengthen patient-clinician relationships thereby creating stronger bidirectional diagnostic partnerships. We also consider the potential pitfalls or unintended consequences of note transparency, and highlight areas in need of further research.

Unlike many other areas of laboratory medicine, laboratory hemostasis has some peculiarities, which makes it one of the most complex diagnostic domains in clinical medicine. The inherent complexity of the hemostasis process, the components of which have not yet been thoroughly unravelled, is mirrored by a large number of hemostasis disturbances, which can involve single or multiple components. Although laboratory diagnostics represents an unavoidable part of the diagnostic reasoning in patients with bleeding or thrombotic disorders, the basic concept beneath the assumption that in many human pathologies, one single test may be sufficient for the diagnosis, does not hold true in hemostasis. There are in fact many aspects that would lead us to conclude that laboratory hemostasis can be considered a very challenging arena for many clinicians and perhaps also for some laboratory professionals. The most challenging aspects typically include the following concepts; that hemostasis is an intricate and multifaceted process, that more than one test is typically needed to achieve a final diagnosis, that results of screening tests depend on many biological factors and do not allow making a final diagnosis, that harmonization of techniques is still an unmet target, and that the calculations used vary widely among laboratories. This article is hence aimed at discussing many of these aspects, with the hope of presenting a useful contribution to better understand the “philosophy” of laboratory hemostasis.

Background Diagnostic errors cause substantial preventable harm, but national estimates vary widely from 40,000 to 4 million annually. This cross-sectional analysis of a large medical malpractice claims database was the first phase of a three-phase project to estimate the US burden of serious misdiagnosis-related harms. Methods We sought to identify diseases accounting for the majority of serious misdiagnosis-related harms (morbidity/mortality). Diagnostic error cases were identified from Controlled Risk Insurance Company (CRICO)’s Comparative Benchmarking System (CBS) database (2006–2015), representing 28.7% of all US malpractice claims. Diseases were grouped according to the Agency for Healthcare Research and Quality (AHRQ) Clinical Classifications Software (CCS) that aggregates the International Classification of Diseases diagnostic codes into clinically sensible groupings. We analyzed vascular events, infections, and cancers (the “Big Three”), including frequency, severity, and settings. High-severity (serious) harms were defined by scores of 6–9 (serious, permanent disability, or death) on the National Association of Insurance Commissioners (NAIC) Severity of Injury Scale. Results From 55,377 closed claims, we analyzed 11,592 diagnostic error cases [median age 49, interquartile range (IQR) 36–60; 51.7% female]. These included 7379 with high-severity harms (53.0% death). The Big Three diseases accounted for 74.1% of high-severity cases (vascular events 22.8%, infections 13.5%, and cancers 37.8%). In aggregate, the top five from each category (n = 15 diseases) accounted for 47.1% of high-severity cases. The most frequent disease in each category, respectively, was stroke, sepsis, and lung cancer. Causes were disproportionately clinical judgment factors (85.7%) across categories (range 82.0–88.8%). Conclusions The Big Three diseases account for about three-fourths of serious misdiagnosis-related harms. Initial efforts to improve diagnosis should focus on vascular events, infections, and cancers.

Background Diagnosis requires that clinicians communicate and share patient information in an efficient manner. Advances in electronic health records (EHRs) and health information technologies have created both challenges and opportunities for such communication. Methods We conducted a multi-method, focused ethnographic study of physicians on general medicine inpatient units in two teaching hospitals. Physician teams were observed during and after morning rounds to understand workflow, data sharing and communication during diagnosis. To validate findings, interviews and focus groups were conducted with physicians. Field notes and interview/focus group transcripts were reviewed and themes identified using content analysis. Results Existing communication technologies and EHR-based data sharing processes were perceived as barriers to diagnosis. In particular, reliance on paging systems and lack of face-to-face communication among clinicians created obstacles to sustained thinking and discussion of diagnostic decision-making. Further, the EHR created data overload and data fragmentation, making integration for diagnosis difficult. To improve diagnosis, physicians recommended replacing pagers with two-way communication devices, restructuring the EHR to facilitate access to key information and improving training on EHR systems. Conclusions As advances in health information technology evolve, challenges in the way clinicians share information during the diagnostic process will rise. To improve diagnosis, changes to both the technology and the way in which we use it may be necessary.

Background Heuristics and cognitive biases are thought to play an important role in diagnostic medical error. How to systematically determine and capture these kinds of errors remains unclear. Morbidity and mortality rounds (MMRs) are generally focused on reducing medical error by identifying and correcting systems failures. However, they may also provide an educational platform for recognizing and raising awareness on cognitive errors. Methods A total of 49 MMR cases spanning the period 2008–2015 in our pathology department were examined for the presence of cognitive errors and/or systems failures by eight study participant raters who were trained on a subset of 16 of these MMR cases (excluded from the main study analysis) to identify such errors. The Delphi method was used to obtain group consensus on error classification on the remaining 33 study cases. Cases with <75% inter-rater agreement were subjected to subsequent rounds of Delphi analysis. Inter-rater agreement at each round was determined by Fleiss’ kappa values. Results Thirty-six percent of the cases presented at our pathology MMRs over an 8-year period were found to contain errors likely due to cognitive bias. Conclusions These data suggest that the errors identified in our pathology MMRs represent not only systems failures but may also be composed of a significant proportion of cognitive errors. Teaching trainees and health professionals to correctly identify different types of cognitive errors may present an opportunity for quality improvement interventions in the interests of patient safety.

Background Diagnostic intuition is a rapid, non-analytic, unconscious mode of reasoning. A small body of evidence points to the ubiquity of intuition, and its usefulness in generating diagnostic hypotheses and ascertaining severity of illness. Little is known about how experienced physicians understand this phenomenon, and how they work with it in clinical practice. Methods Descriptions of how experienced physicians perceive their use of diagnostic intuition in clinical practice were elicited through interviews conducted with 30 physicians in emergency, internal and family medicine. Each participant was asked to share stories of diagnostic intuition, including times when intuition was both correct and incorrect. Multiple coders conducted descriptive analysis to analyze the salient aspects of these stories. Results Physicians provided descriptions of what diagnostic intuition is, when it occurs and what type of activity it prompts. From stories of correct intuition, a typology of four different types of intuition was identified: Sick/Not Sick, Something Not Right, Frame-shifting and Abduction. Most physician accounts of diagnostic intuition linked this phenomenon to non-analytic reasoning and emphasized the importance of experience in developing a trustworthy sense of intuition that can be used to effectively engage analytic reasoning to evaluate clinical evidence. Conclusions The participants recounted myriad stories of diagnostic intuition that alerted them to unusual diagnoses, previous diagnostic error or deleterious trajectories. While this qualitative study can offer no conclusions about the representativeness of these stories, it suggests that physicians perceive clinical intuition as beneficial for correcting and advancing diagnoses of both common and rare conditions.

Background Communication and handoff failures are common causes of diagnostic errors in hospital. Human quest for certainty can increase the likelihood of premature closure in decision-making, the most common phenomenon in misdiagnosis. Little research exists on whether language choice in handoffs affects physicians’ sense of uncertainty. Methods Medical students from a large US medical school were randomized to receive one of four language variations describing a presumed diagnosis in hypothetical handoffs from emergency department (ED) to inpatient ward. The control language arm used the word ‘diagnosis’; experimental arms replaced this word with either ‘hypothesis’, ‘probability of 60%’, or ‘working diagnosis’ with a short differential. Outcome measures were students’ anxiety due to uncertainty (range 5–30; higher scores indicating higher stress from uncertainty) and clinical uncertainty about the ED provider’s presumed diagnosis. Results Mean anxiety due to uncertainty was significantly higher in subjects receiving the ‘hypothesis’ language arm compared to those receiving the control ‘diagnosis’ language [19.2 (4.6) vs. 15.5 (3.4); p<0.008]. Differences between subjects who received the probability language [17.2 (5.8) vs. 15.5 (3.4); p=0.26] and ‘working diagnosis’ language [16 (5) vs. 15.5 (3.4); p=0.69] were not statistically significant. There was no difference in items assessing clinical uncertainty after each scenario. Conclusions The word ‘hypothesis’ increased anxiety due to uncertainty compared to the word ‘diagnosis’, but did not change assessments of clinical uncertainty. Further research is needed to assess how use of language in clinical handoffs may influence perceptions and anxiety related to uncertainty and whether optimal language can be identified that leads to recognition of uncertainty without maladaptive stress or anxiety due to uncertainty.

Background Clinical evidence indicates that genetic variations may interfere with the mechanism of drug action. Recently, it has been reported that the single nucleotide polymorphisms (SNPs) of STAT4 , PTPN2 , PSORS1C1 and TRAF3IP2RA genes are associated with the clinical efficacy of tumor necrosis factor (TNF) inhibitors in the treatment of rheumatoid arthritis (RA) patients. Therefore, the detection of the SNPs linked with TNF inhibitor efficacy may provide an important basis for the treatment of RA. This study intended to establish molecular diagnostic methods for genotyping the linked SNPs based on high resolution melting (HRM) curve analysis. Methods The polymerase chain reaction-HRM (PCR-HRM) curve analysis detecting systems were established by designing the primers of the four SNPs, rs7574865 G>T , rs7234029 A>G , rs2233945 C>A and rs33980500 C>T , and the performance and clinical applicability of which were evaluated by using the Sanger sequencing method and genotyping test for 208 clinical samples. Results The self-developed molecular diagnostic methods of PCR-HRM were confirmed to be able to correctly genotype the four SNPs, the sensitivity and specificity of which were 100% in this study. The repeatability and reproducibility tests showed that there is little variable in intra-assay and inter-assay (the coefficient of variation ranged from 0.01% to 0.07%). The slight changes of DNA template and primer concentrations, PCR cycle number and reaction system volume had no significant effect on the genotyping performance of the method. The PCR-HRM assays were also applied to other PCR thermocyclers with HRM function and use different saturation fluorescent dyes. Conclusions The PCR-HRM genotyping method established in this study can be applied to the routine molecular diagnosis of rs7574865, rs7234029, rs2233945 and rs33980500.

Background Acute rejection (AR) is one of the most frequent complications after kidney transplantation (KT). Scientific evidence reports that some single-nucleotide polymorphisms (SNPs) located in genes involved in the immune response and in the pharmacokinetics and pharmacodynamics of immunosuppressive drugs are associated with rejection in renal transplant patients. The aim of this study was to evaluate some SNPs located in six genes: interleukin-10 ( IL-10 ), tumor necrosis factor ( TNF ), adenosine triphosphate-binding cassette sub-family B member 1 ( ABCB1 ), uridine diphosphate glucuronosyltransferase family 1 member A9 ( UGT1A9 ), inosine monophosphate dehydrogenase 1 ( IMPDH1 ) and IMPDH2 . Methods We enrolled cases with at least one AR after KT and two groups of controls: patients without any AR after KT and healthy blood donors. Genetic analysis on DNA was performed. The heterozygosity (HET) was determined and the Hardy-Weinberg equilibrium (HWE) test was performed for each SNP. The sample size was calculated using the QUANTO program and the genetic associations were calculated using the SAS program (SAS Institute Inc., Cary, NC, USA). Results In our previous preliminary study (sample size was not reached for cases), the results showed that patients with the C allele in the SNP rs1045642 and the A allele in the SNP rs2032582 of the ABCB1 gene had more frequent AR. In contrast, with the achievement of sample size, the trend of the previous data was not confirmed. Conclusions Our study highlights a fundamental aspect of scientific research that is generally presumed, i.e. the sample size of groups enrolled for a scientific study. We believe that our study will make a significant contribution to the scientific community in the discussion of the importance of the analysis and the achievement of sample size to evaluate the associations between SNPs and the studied event.

We report the case of a morbidly obese 49-year-old female found to have a 16×14×10 cm high grade myxoid liposarcoma of the thigh initially diagnosed as a hematoma. Recent initiation of rivaroxaban for a coincident ipsilateral popliteal vein thrombosis placed hematoma high in the differential diagnosis. Despite its large size, the mass was not directly appreciable on physical exam due to excess adjacent adipose tissue. Diagnostic success was achieved only after anchoring bias was abandoned and adaptive expertise was applied.

The isoenzyme creatine kinase muscle/brain (CK-MB) still plays an important role for the differential diagnosis of CK elevations and the clarification of their origin from heart or skeletal muscle. Therefore, it is necessary to know the diagnostic pitfalls in interpreting CK-MB results. We demonstrate a case of macro-CK type 2 in a 75-year-old patient with metastatic castration-resistant prostate cancer and its identification by isoenzyme electrophoresis, which can be typical for cancer diseases.