Impact Factor: 3.5

Published since January 22, 2014

Diagnosis

Official Journal of the Society to Improve Diagnosis in Medicine (SIDM)

ISSN: 2194-802X

Editors-in-chief: Mark L. Graber, Mario Plebani

About this journal

Objective
Diagnosis is a subscription journal, which focuses on how diagnosis can be advanced, how it is taught, and how and why it can fail, leading to diagnostic errors. The journal welcomes both fundamental and applied works, improvement initiatives, opinions, and debates to encourage new thinking on improving this critical aspect of healthcare quality. Diagnosis is the official journal of the Society to Improve Diagnosis in Medicine.

Please submit your manuscript here

Topics

Factors that promote diagnostic quality and safety
Clinical reasoning
Diagnostic errors in medicine
The factors that contribute to diagnostic error: human factors, cognitive issues, and system-related breakdowns
Improving the value of diagnosis – eliminating waste and unnecessary testing
How culture and removing blame promote awareness of diagnostic errors
Training and education related to clinical reasoning and diagnostic skills
Advances in laboratory testing and imaging that improve diagnostic capability
Local, national and international initiatives to reduce diagnostic error

Article formats

Research Reports – Reports of original research
Short Communications – Reports of early research results and pilot studies
Reviews – Systematic, narrative, and focused reviews. Review articles are normally published by invitation, but suggestions to the Editors are welcome
Opinion Papers and Editorials
Letters to the Editor
Point/Counterpoint Papers
Guidelines and Recommendations
Innovations in diagnostic testing – Advances in laboratory testing or diagnostic imaging are appropriate subjects, or evaluations of recent innovations
Case Reports – Learning from Tragedy – Case reports of diagnostic error or dilemma discussed from a multi-stakeholder perspective; should include the facts of the case, a discussion focused on a root cause analysis, take-away points or action items resulting from the analysis, and whenever possible input from both the affected patients and their providers
Case Reports – Lessons in Clinical Reasoning: Pitfalls, Myths, and Pearls – Case reports in which a clinician discusses their diagnostic approach after clinical information is presented, focusing on a case in which a diagnostic error (or near miss = great catch) occurred
Patient-Focused Articles – Papers in this category should be written in lay language on a topic of interest to the patient stakeholder community
Diagnosis in the News – Brief reports of news-worthy advances in diagnosis, or problems involving diagnostic error

Your Benefits

Indexed in PubMed (all articles since 2014) and other abstracting and indexing services
Peer-reviewed and led by a multi-institutional editorial board
Focused on how the diagnostic process can be advanced to reduce diagnostic errors
Cutting-edge and authoritative contributions
Academic and clinical aspects of quality and safety in healthcare combination
International readership and global reach

History

founded in 2014
volumes 1 and 2 are Open Access

Other publications in the field

Abstracting and Indexing

Diagnosis is covered by the following services:

Baidu Scholar
Cabells Journalytics
Chemical Abstracts Service (CAS) - CAplus
Chemical Abstracts Service (CAS) - SciFinder
CNKI Scholar (China National Knowledge Infrastructure)
CNPIEC - cnpLINKer
Dimensions
EBSCO (relevant databases)
EBSCO Discovery Service
EMBASE
EMCare
Google Scholar
Japan Science and Technology Agency (JST)
J-Gate
JournalTOCs
KESLI-NDSL (Korean National Discovery for Science Leaders)
Medline
MyScienceWork
Naver Academic
Naviga (Softweco)
Primo Central (ExLibris)
Publons
PubMed
QOAM (Quality Open Access Market)
ReadCube
Reaxys
Scilit
SCImago (SJR)
SCOPUS
Semantic Scholar
Sherpa/RoMEO
Summon (ProQuest)
TDNet
Text Mining
Ulrich's Periodicals Directory/ulrichsweb
WanFang Data
Web of Science - Emerging Sources Citation Index
WorldCat (OCLC)
X-MOL
Yewno Discover

Supplementary Materials

Topics

External Links

Volume 10 Issue 4

November 2023

Publicly Available November 28, 2023

Frontmatter

Page range: i-ii

Download PDF

Reviews

August 10, 2023

Diagnostic errors in uncommon conditions: a systematic review of case reports of diagnostic errors

Yukinori Harada, Takashi Watari, Hiroyuki Nagano, Tomoharu Suzuki, Kotaro Kunitomo, Taiju Miyagami, Tetsuro Aita, Kosuke Ishizuka, Mika Maebashi, Taku Harada, Tetsu Sakamoto, Shusaku Tomiyama, Taro Shimizu

Page range: 329-336

Abstract

Objectives To assess the usefulness of case reports as sources for research on diagnostic errors in uncommon diseases and atypical presentations. Content We reviewed 563 case reports of diagnostic error. The commonality of the final diagnoses was classified based on the description in the articles, Orphanet, or epidemiological data on available references; the typicality of presentation was classified based on the description in the articles and the judgment of the physician researchers. Diagnosis Error Evaluation and Research (DEER), Reliable Diagnosis Challenges (RDC), and Generic Diagnostic Pitfalls (GDP) taxonomies were used to assess the factors contributing to diagnostic errors. Summary and outlook Excluding three cases in that commonality could not be classified, 560 cases were classified into four categories: typical presentations of common diseases (60, 10.7 %), atypical presentations of common diseases (35, 6.2 %), typical presentations of uncommon diseases (276, 49.3 %), and atypical presentations of uncommon diseases (189, 33.8 %). The most important DEER taxonomy was “Failure/delay in considering the diagnosis” among the four categories, whereas the most important RDC and GDP taxonomies varied with the categories. Case reports can be a useful data source for research on the diagnostic errors of uncommon diseases with or without atypical presentations.

September 20, 2023

Routine blood test markers for predicting liver disease post HBV infection: precision pathology and pattern recognition

Busayo I. Ajuwon, Katrina Roper, Alice Richardson, Brett A. Lidbury

Page range: 337-347

Abstract

Background Early stages of hepatitis B virus (HBV) infection usually involve inflammation of the liver. Patients with chronic infection have an increased risk of progressive liver fibrosis, cirrhosis, and life-threatening clinical complications of end-stage hepatocellular carcinoma (HCC). Content Early diagnosis of hepatic fibrosis and timely clinical management are critical to controlling disease progression and decreasing the burden of end-stage liver cancer. Fibrosis staging, through its current gold standard, liver biopsy, improves patient outcomes, but the clinical procedure is invasive with unpleasant post-procedural complications. Routine blood test markers offer promising diagnostic potential for early detection of liver disease without biopsy. There is a plethora of candidate routine blood test markers that have gone through phases of biomarker validation and have shown great promise, but their current limitations include a predictive ability that is limited to only a few stages of fibrosis. However, the advent of machine learning, notably pattern recognition, presents an opportunity to refine blood-based non-invasive models of hepatic fibrosis in the future. Summary In this review, we highlight the current landscape of routine blood-based non-invasive models of hepatic fibrosis, and appraise the potential application of machine learning (pattern recognition) algorithms to refining these models and optimising clinical predictions of HBV-associated liver disease. Outlook Machine learning via pattern recognition algorithms takes data analytics to a new realm, and offers the opportunity for enhanced multi-marker fibrosis stage prediction using pathology profile that leverages information across patient routine blood tests.

Opinion Papers

May 15, 2023

The challenge of clinical reasoning in chronic multimorbidity: time and interactions in the Health Issues Network model

Fabrizio Consorti, Dario Torre, Daniela Luzi, Fabrizio Pecoraro, Fabrizio Ricci, Oscar Tamburis

Page range: 348-352

Abstract

The increasing prevalence of multimorbidity requires new theoretical models and educational approaches to develop physicians’ ability to manage multimorbidity patients. The Health Issues Network (HIN) is an educational approach based on a graphical depiction of the evolutions over time of the concurrent health issues of a patient and of their interactions. From a theoretical point of view, the HIN approach is rooted in Prigogine’s vision of the “becoming” of the events and in the concept of knowledge organization, intended as the process of storing and structuring of information in a learner’s mind. The HIN approach allows to design clinical exercises to foster learners’ ability to detect evolutionary paths and interactions among health issues. Recent findings of neuroscience support the expectation that interpreting, completing, and creating diagrams depicting complex clinical cases improves the “sense of time”, as a fundamental competence in the management of multimorbidity. The application of the HIN approach is expected to decrease the risk of errors in the management of multimorbidity patients. The approach is still under validation, both for undergraduate students and for the continuous professional development of physicians.

April 5, 2023

The first diagnostic excellence conference in Japan

Taro Shimizu, Yukinori Harada

Page range: 353-355

Abstract

In February 2023, the first national conference on Diagnostic Excellence was held in Japan. As the conference covered a wide range of academic areas, we placed particular emphasis on topics related to excellence in physicians’ clinical reasoning. This focus reflected the culture of Japanese medical professionals, especially of physicians, who have shown passion for clinical diagnosis for decades, having held non-profit voluntary multi-institutional conferences during off-duty hours. Of the over 1,400 participants who attended the two-day conference, 80% were generalist physicians and residents, 10% were medical students, and the remainder were healthcare professionals and participants from other academic areas. Given the background of Japanese physicians’ passion for clinical diagnosis, the conference organizers believed that focusing on the diagnostic thinking of physicians as part of the Diagnostic Excellence concept would have strong appeal to participants. Simultaneously, the organizers believed that it was important to target participants in their 20s–40s, and made efforts to utilize social networking services and advertising strategies, including creating individual posters with the help of professional designers. On reflection after the conference, consideration of the local characteristics of the population, particularly their interest in the target population, and the expansion of the conference’s focus to include younger participants may have served as drivers of the success of the conference. This outcome of the conference in Asia is an intriguing step in the world deployment strategy of Diagnostic Excellence, and is expected to promote cooperation among Asia and the United States, Europe, and Oceania.

April 10, 2023

Clouds across the new dawn for clinical, diagnostic and biological data: accelerating the development, delivery and uptake of personalized medicine

Denis Horgan, Ettore Capoluongo, France Dube, Dario Trapani, Umberto Malapelle, Vita Rovite, Muhammad Imran Omar, Catherine Alix-Panabières, Piotr Rutkowski, Arnaud Bayle, Allan Hackshaw, Paul Hofman, Vivek Subbiah

Page range: 356-362

Abstract

Growing awareness of the genetic basis of disease is transforming the opportunities for improving patient care by accelerating the development, delivery and uptake of personalised medicine and diseases diagnostics. This can mean more precise treatments reaching the right patients at the right time at the right cost. But it will be possible only with a coherent European Union (EU) approach to regulation. For clinical and biological data, on which the EU is now legislating with its planned European Health Data Space (EHDS), it is crucial that the design of this new system respects the constraints also implicit in the testing which generates data. The current EHDS proposal may fail to meet this requirement. It risks being over-ambitious, while taking insufficient account of the demanding realities of data access in daily practice and current economics/business models. It is marred by imprecision and ambiguity, by overlaps with other EU legislation, and by lack of clarity on funding. This paper identifies key issues where legislators should ensure that the opportunities are not squandered by the adoption of over-hasty or ill-considered provisions that jeopardise the gains that could be made in improved healthcare.

Original Articles

August 11, 2023

Towards diagnostic excellence on academic ward teams: building a conceptual model of team dynamics in the diagnostic process

Justin J. Choi, Michael A. Rosen, Martin F. Shapiro, Monika M. Safford

Page range: 363-374

Abstract

Objectives Achieving diagnostic excellence on medical wards requires teamwork and effective team dynamics. However, the study of ward team dynamics in teaching hospitals is relatively underdeveloped. We aim to enhance understanding of how ward team members interact in the diagnostic process and of the underlying behavioral, psychological, and cognitive mechanisms driving team interactions. Methods We used mixed-methods to develop and refine a conceptual model of how ward team dynamics in an academic medical center influence the diagnostic process. First, we systematically searched existing literature for conceptual models and empirical studies of team dynamics. Then, we conducted field observations with thematic analysis to refine our model. Results We present a conceptual model of how medical ward team dynamics influence the diagnostic process, which serves as a roadmap for future research and interventions in this area. We identified three underexplored areas of team dynamics that are relevant to diagnostic excellence and that merit future investigation (1): ward team structures (e.g., team roles, responsibilities) (2); contextual factors (e.g., time constraints, location of team members, culture, diversity); and (3) emergent states (shared mental models, psychological safety, team trust, and team emotions). Conclusions Optimizing the diagnostic process to achieve diagnostic excellence is likely to depend on addressing all of the potential barriers and facilitators to ward team dynamics presented in our model.

October 5, 2023

Error codes at autopsy to study potential biases in diagnostic error

Bruce I. Goldman, Rajnish Bharadwaj, Michelle Fuller, Tanzy Love, Leon Metlay, Caroline Dignan

Page range: 375-382

Abstract

Objectives Current autopsy practice guidelines do not provide a mechanism to identify potential causes of diagnostic error (DE). We used our autopsy data registry to ask if gender or race were related to the frequency of diagnostic error found at autopsy. Methods Our autopsy reports include International Classification of Diseases (ICD) 9 or ICD 10 diagnostic codes for major diagnoses as well as codes that identify types of error. From 2012 to mid-2015 only 2 codes were used: UNDOC (major undocumented diagnoses) and UNCON (major unconfirmed diagnoses). Major diagnoses contributed to death or would have been treated if known. Since mid-2015, codes included specific diagnoses, i.e. undiagnosed or unconfirmed myocardial infarction, infection, pulmonary thromboembolism, malignancy, or other diagnosis as well as cause of death. Adult autopsy cases from 2012 to 2019 were assessed for DE associated with reported sex or race (nonwhite or white). 528 cases were evaluated between 2012 and 2015 and 699 between 2015 and 2019. Results Major DEs were identified at autopsy in 65.9 % of cases from 2012 to 2015 and in 72.1 % from 2015 to 2019. From 2012 to 2015, female autopsy cases showed a greater frequency in 4 parameters of DE, i.e., in the total number of cases with any error (p=0.0001), in the number of cases with UNDOC errors (p=0.0038) or UNCON errors (p=0.0006), and in the relative proportions of total numbers of errors (p=0.0001). From 2015 to 2019 undocumented malignancy was greater among males (p=0.0065); no other sex-related error was identified. In the same period some DE parameters were greater among nonwhite than among white subjects, including unconfirmed cause of death (p=0.035), and proportion of total error diagnoses (p=0.0003), UNCON diagnoses (p=0.0093), and UNDOC diagnoses (p=0.035). Conclusions Coding for DE at autopsy can identify potential effects of biases on diagnostic error.

June 22, 2023

Multicenter evaluation of a method to identify delayed diagnosis of diabetic ketoacidosis and sepsis in administrative data

Kenneth A. Michelson, Richard G. Bachur, Andrea T. Cruz, Joseph A. Grubenhoff, Scott D. Reeves, Pradip P. Chaudhari, Michael C. Monuteaux, Arianna H. Dart, Jonathan A. Finkelstein

Page range: 383-389

Abstract

Objectives To derive a method of automated identification of delayed diagnosis of two serious pediatric conditions seen in the emergency department (ED): new-onset diabetic ketoacidosis (DKA) and sepsis. Methods Patients under 21 years old from five pediatric EDs were included if they had two encounters within 7 days, the second resulting in a diagnosis of DKA or sepsis. The main outcome was delayed diagnosis based on detailed health record review using a validated rubric. Using logistic regression, we derived a decision rule evaluating the likelihood of delayed diagnosis using only characteristics available in administrative data. Test characteristics at a maximal accuracy threshold were determined. Results Delayed diagnosis was present in 41/46 (89 %) of DKA patients seen twice within 7 days. Because of the high rate of delayed diagnosis, no characteristic we tested added predictive power beyond the presence of a revisit. For sepsis, 109/646 (17 %) of patients were deemed to have a delay in diagnosis. Fewer days between ED encounters was the most important characteristic associated with delayed diagnosis. In sepsis, our final model had a sensitivity for delayed diagnosis of 83.5 % (95 % confidence interval 75.2–89.9) and specificity of 61.3 % (95 % confidence interval 56.0–65.4). Conclusions Children with delayed diagnosis of DKA can be identified by having a revisit within 7 days. Many children with delayed diagnosis of sepsis may be identified using this approach with low specificity, indicating the need for manual case review.

August 17, 2023

Detection of fake papers in the era of artificial intelligence

Mehdi Dadkhah, Marilyn H. Oermann, Mihály Hegedüs, Raghu Raman, Lóránt Dénes Dávid

Page range: 390-397

Abstract

Objectives Paper mills, companies that write scientific papers and gain acceptance for them, then sell authorships of these papers, present a key challenge in medicine and other healthcare fields. This challenge is becoming more acute with artificial intelligence (AI), where AI writes the manuscripts and then the paper mills sell the authorships of these papers. The aim of the current research is to provide a method for detecting fake papers. Methods The method reported in this article uses a machine learning approach to create decision trees to identify fake papers. The data were collected from Web of Science and multiple journals in various fields. Results The article presents a method to identify fake papers based on the results of decision trees. Use of this method in a case study indicated its effectiveness in identifying a fake paper. Conclusions This method to identify fake papers is applicable for authors, editors, and publishers across fields to investigate a single paper or to conduct an analysis of a group of manuscripts. Clinicians and others can use this method to evaluate articles they find in a search to ensure they are not fake articles and instead report actual research that was peer reviewed prior to publication in a journal.

Open Access July 24, 2023

Is language an issue? Accuracy of the German computerized diagnostic decision support system ISABEL and cross-validation with the English counterpart

Thimo Marcin, Ailin Lüthi, Ronny R. Graf, Gert Krummrey, Stefan K. Schauber, Neal Breakey, Wolf E. Hautz, Stefanie C. Hautz

Page range: 398-405

More Download PDF

Abstract

Objectives Existing computerized diagnostic decision support tools (CDDS) accurately return possible differential diagnoses (DDx) based on the clinical information provided. The German versions of the CDDS tools for clinicians (Isabel Pro) and patients (Isabel Symptom Checker) from ISABEL Healthcare have not been validated yet. Methods We entered clinical features of 50 patient vignettes taken from an emergency medical text book and 50 real cases with a confirmed diagnosis derived from the electronic health record (EHR) of a large academic Swiss emergency room into the German versions of Isabel Pro and Isabel Symptom Checker. We analysed the proportion of DDx lists that included the correct diagnosis. Results Isabel Pro and Symptom Checker provided the correct diagnosis in 82 and 71 % of the cases, respectively. Overall, the correct diagnosis was ranked in 71 , 61 and 37 % of the cases within the top 20, 10 and 3 of the provided DDx when using Isabel Pro. In general, accuracy was higher with vignettes than ED cases, i.e. listed the correct diagnosis more often (non-significant) and ranked the diagnosis significantly more often within the top 20, 10 and 3. On average, 38 ± 4.5 DDx were provided by Isabel Pro and Symptom Checker. Conclusions The German versions of Isabel achieved a somewhat lower accuracy compared to previous studies of the English version. The accuracy decreases substantially when the position in the suggested DDx list is taken into account. Whether Isabel Pro is accurate enough to improve diagnostic quality in clinical ED routine needs further investigation.

July 28, 2023

The feasibility of a mystery case curriculum to enhance diagnostic reasoning skills among medical students: a process evaluation

Christopher Snyder, Michael Smith, Kailey Snyder

Page range: 406-411

Abstract

Objectives Within a Hospital Medicine division at a large academic institution, an innovative program has been developed to offer third year medical learners enrolled in their Internal Medicine Clerkship the opportunity to deepen their diagnostic reasoning skills with a weekly case-based learning activity entitled “Hospital Medicine’s Mystery Case of the Week”. The mystery case curriculum has four primary learning objectives (1): To understand the value of employing a multisystem approach to a common presenting problem (2); To apply a diagnostic schema to a clinical problem (3); To apply knowledge of cost appropriate workups to a clinical case and (4) To identify cognitive biases that can influence decision making in the context of treating a clinical problem. Methods A process evaluation of the mystery case curriculum was conducted over a 6-month implementation period. The process evaluation was guided by eight domains of focus: program acceptability, demand, implementation, practicality, adaptation, integration, expansion and limited-efficacy testing. Measures included a pre/post mixed-methods survey, attendance log and timesheet. Pre/post survey data was analyzed via paired samples t-tests and open-ended responses were analyzed via a deductive content analysis. Results Process evaluation findings demonstrated the program had high levels of acceptability and demand. Survey findings suggest the curriculum may increase feelings of preparedness for Internal Medicine exams as well as student interest, comfort and confidence related to diagnostic processes. Conclusions Future evaluations should work to understand the influence this curriculum has on diagnostic accuracy within a clinical setting.

July 21, 2023

Internal medicine intern performance on the gastrointestinal physical exam

Julia R. Gips, Ariella Apfel Stein, Joyce Luckin, Brian T. Garibaldi

Page range: 412-416

Abstract

Objectives The gastrointestinal (GI) physical exam provides critical information about underlying disease states. However, since assessment of physical examination skills is rarely conducted as part of internal medicine residency training, little is known about resident performance on the GI physical exam. Methods During a clinical skills assessment that took place between November 2019 and February 2020, internal medicine interns examined the same patient with chronic liver disease while being observed by faculty preceptors. We compared the exam maneuvers performed with those expected by the faculty evaluators. We noted which maneuvers were performed incorrectly, whether physical exam technique correlated with identification of physical exam findings, and if performance on the physical exam was associated with building an appropriate differential diagnosis. This four-hour assessment was required for internal medicine interns within two different residency programs in the Baltimore area. Results More than half of the 29 participating interns (n=17, 58.6 %) received a “needs improvement” score on their physical exam technique. Technique was highly correlated with identifying the correct physical signs (r=0.88, p<0.0001). The most commonly excluded maneuvers were assessing for splenomegaly and hepatomegaly. The most commonly missed findings were splenomegaly and hepatomegaly. Most interns included chronic liver disease as part of their differential diagnosis even if they received “needs improvement” scores on physical exam technique or identifying physical signs. Conclusions Internal medicine interns would benefit from learning an organized approach to the gastrointestinal exam. This would likely lead to increased identification of important gastrointestinal findings.

August 21, 2023

Scaling up a diagnostic pause at the ICU-to-ward transition: an exploration of barriers and facilitators to implementation of the ICU-PAUSE handoff tool

Ella G. Cornell, Emily Harris, Emma McCune, Elle Fukui, Patrick G. Lyons, Juan C. Rojas, Lekshmi Santhosh

Page range: 417-423

Abstract

Objectives The transition from the intensive care unit (ICU) to the medical ward is a high-risk period due to medical complexity, reduced patient monitoring, and diagnostic uncertainty. Standardized handoff practices reduce errors associated with transitions of care, but little work has been done to standardize the ICU to ward handoff. Further, tools that exist do not focus on preventing diagnostic error. Using Human-Centered Design methods we previously created a novel EHR-based ICU-ward handoff tool (ICU-PAUSE) that embeds a diagnostic pause at the time of transfer. This study aims to explore barriers and facilitators to implementing a diagnostic pause at the ICU-to-ward transition. Methods This is a multi-center qualitative study of semi-structured interviews with intensivists from ten academic medical centers. Interviews were analyzed iteratively through a grounded theory approach. The Sittig-Singh sociotechnical model was used as a unifying conceptual framework. Results Across the eight domains of the model, we identified major benefits and barriers to implementation. The embedded pause to address diagnostic uncertainty was recognized as a key benefit. Participants agreed that standardization of verbal and written handoff would decrease variation in communication. The main barriers fell within the domains of workflow, institutional culture, people, and assessment. Conclusions This study represents a novel application of the Sittig-Singh model in the assessment of a handoff tool. A unique feature of ICU-PAUSE is the explicit acknowledgement of diagnostic uncertainty, a practice that has been shown to reduce medical error and prevent premature closure. Results will be used to inform future multi-site implementation efforts.

Open Access August 14, 2023

Learned cautions regarding antibody testing in mast cell activation syndrome

Lawrence B. Afrin, Tania T. Dempsey, Gerhard J. Molderings

Page range: 424-431

More Download PDF

Abstract

Objectives To describe patterns observed in antibody titer trendlines in patients with mast cell activation syndrome (MCAS, a prevalent but underrecognized chronic multisystem inflammatory disorder of great clinical heterogeneity) and offer clinical lessons learned from such pattern recognition. Methods The available records of 104 MCAS patients drawn from the authors’ practices were reviewed, including all antibody tests therein. Results All patients had positive/elevated antibodies of various sorts at various points, but for most of the antibodies which were found to be positive at least some points, the diseases classically associated with those antibodies were not present, marking such antibodies as clinically insignificant mimickers (likely consequent to inflammatory effects of MCAS on the immune system itself driving spurious/random antibody production) rather than “on-target” and pathogenic antibodies reflecting true disease warranting treatment. We also observed two distinct patterns in trendlines of the titers of the mimickers vs. the trendline pattern expected in a true case of an antibody-associated disease (AAD). Conclusions Our observations suggest most positive antibody tests in MCAS patients represent detection of clinically insignificant mimicking antibodies. As such, to reduce incorrect diagnoses of AADs and inappropriate treatment in MCAS patients, caution is warranted in interpreting positive antibody tests in these patients. Except in clinically urgent/emergent situations, patience in determining the trendline of a positive antibody in an MCAS patient, and more carefully assessing whether the AAD is truly present, is to be preferred.

Open Access September 5, 2023

Diagnostic properties of natriuretic peptides and opportunities for personalized thresholds for detecting heart failure in primary care

Ralf E. Harskamp, Lukas De Clercq, Lieke Veelers, Martijn C. Schut, Henk C.P.M. van Weert, M. Louis Handoko, Eric P. Moll van Charante, Jelle C.L. Himmelreich

Page range: 432-439

More Download PDF

Abstract

Objectives Heart failure (HF) is a prevalent syndrome with considerable disease burden, healthcare utilization and costs. Timely diagnosis is essential to improve outcomes. This study aimed to compare the diagnostic performance of B-type natriuretic peptide (BNP) and N-terminal proBNP (NT-proBNP) in detecting HF in primary care. Our second aim was to explore if personalized thresholds (using age, sex, or other readily available parameters) would further improve diagnostic accuracy over universal thresholds. Methods A retrospective study was performed among patients without prior HF who underwent natriuretic peptide (NP) testing in the Amsterdam General Practice Network between January 2011 and December 2021. HF incidence was based on registration out to 90 days after NP testing. Diagnostic accuracy was evaluated with AUROC, sensitivity and specificity based on guideline-recommended thresholds (125 ng/L for NT-proBNP and 35 ng/L for BNP). We used inverse probability of treatment weighting to adjust for confounding. Results A total of 15,234 patients underwent NP testing, 6,870 with BNP (4.5 % had HF), and 8,364 with NT-proBNP (5.7 % had HF). NT-proBNP was more accurate than BNP, with an AUROC of 89.9 % (95 % CI: 88.4–91.2) vs. 85.9 % (95 % CI 83.5–88.2), with higher sensitivity (95.3 vs. 89.7 %) and specificity (59.1 vs. 58.0 %). Differentiating NP cut-off by clinical variables modestly improved diagnostic accuracy for BNP and NT-proBNP compared with a universal threshold. Conclusions NT-proBNP outperforms BNP for detecting HF in primary care. Personalized instead of universal diagnostic thresholds led to modest improvement.

July 24, 2023

Incomplete filling of spray-dried K₂EDTA evacuated blood tubes: impact on measuring routine hematological parameters on Sysmex XN-10

Giuseppe Lippi, Francesco Dima, Marco Tosi, Giovanni Carpenè, Giovanni Celegon, Emmanuel J. Favaloro, Gian Luca Salvagno

Page range: 440-445

Abstract

Objectives Because there is little published evidence on the effects of incomplete filling of K 2 EDTA evacuated blood tubes on routine hematological testing, this original study aimed to provide updated information on this preanalytical aspect. Methods The study population consisted of 17 ostensibly healthy volunteers. Blood was drawn by venipuncture with a 10 mL syringe and dispensed in varying amounts (0.2, 0.5, 1.0, 2.0, and 3.0 mL) into 3.0 mL blood tubes containing spray-dried 5.4 mg K 2 EDTA. All tubes were gently mixed and used to perform routine hematology tests on the Sysmex XN-10. Clinically significant variations were defined when the limits of desirable specifications of bias derived from biologic variation were exceeded. Results The desirable bias was exceeded in 33 % filled tubes (1.0 mL) for hematocrit and MCV (increased values) and for MCHC (decreased values), while it was exceeded in 17 % filled tubes (0.5 mL) for hemoglobin, hematocrit and MCV (increased values), and for MCHC (decreased values). Finally, the variation of values was higher than the desirable bias for RBC, hemoglobin, hematocrit and MCV (increase), and for MCHC and MPV (decrease) in 7 % filled tubes (0.2 mL). No clinically significant variations were observed in tubes filled up to 67 % of their nominal volume (i.e., 2.0 mL). Conclusions Consideration should be given to reject spray-dried K 2 EDTA blood tubes that contain a blood volume <67 % of the nominal fill volume, as biased laboratory data in these samples may interfere with clinical decision making and care management.

Letters to the Editor

April 27, 2023

The diagnostic accuracy of AI-based predatory journal detectors: an analogy to diagnosis

Jaime A. Teixeira da Silva, Timothy Daly

Page range: 446-447

Open Access June 19, 2023

Explainable AI for gut microbiome-based diagnostics: colorectal cancer as a case study

Animesh Acharjee

Page range: 448-449

Download PDF

May 15, 2023

Restless X syndrome: a new diagnostic family of nocturnal, restless, abnormal sensations of various body parts

Rurika Sato, Daiki Yokokawa, Takanori Uehara, Tomoko Tsukamoto, Kazutaka Noda, Kiyoshi Shikino, Yasutaka Yanagita, Jumpei Kojima, Kosuke Ishizuka, Masatomi Ikusaka

Page range: 450-451

Erratum

Publicly Available October 26, 2023

Retraction of: Establishing a stable platform for the measurement of blood endotoxin levels in the dialysis population

Shyam Dheda, Hongjin Min, David Vesey, Carmel Hawley, David W. Johnson, Magid Fahim

Page range: 452-452

Download PDF

Ahead of Print / Just Accepted

Ahead of Print / Just Accepted

Volume 10 (2023)

Volume 9 (2022)

Volume 8 (2021)

Volume 7 (2020)

Volume 6 (2019)

Volume 5 (2018)

Volume 4 (2017)

Volume 3 (2016)

Volume 2 (2015)

Volume 1 (2014)

Journal Impact Factor	3.5	2022, Journal Citation Reports (Clarivate, 2023)
5-year Journal Impact Factor	3.2	2022, Journal Citation Reports (Clarivate, 2023)
Journal Citation Indicator	0.95	2022, Journal Citation Reports (Clarivate, 2023)
CiteScore	6.9	2022, Scopus (Elsevier B.V., 2023)
SCImago Journal Rank	1.172	2022, SJR (Scimago Lab, 2023; Data Source: Scopus)
Source Normalized Impact per Paper	1.215	2022, CWTS Journal Indicators (CWTS B.V., 2023; Data Source: Scopus)

More information about journal rankings

Submit

Submission
You can easily submit your manuscript online. Simply go to http://mc.manuscriptcentral.com/diagnosis and you will be guided through the whole submission and publishing process.

Your benefits of publishing with us

Rapid publication times
No submission and publication fee
Optional Open Access Publication
Each article published under an open access license is subject to an Article Processing Charge of €2,000.
Free color illustrations
Accepted papers will be published online first as DOI-citable, forward-linked articles for quickest possible visibility for the scientific community
Every article easily discoverable because of SEO and comprehensive abstracting and indexing services
Secure archiving by De Gruyter and the independent archiving service Portico

Submission process

Submission of your manuscript via our submission tool ScholarOne following the Information for Authors
Single-blind peer review process
A decision on your paper is aspired within 2-4 weeks
Accepted articles are published online ahead of print approx. 4 weeks after acceptance

Please note

Manuscripts must be written in clear and concise English
Before submitting your article please have a look at the DIAGNOSIS Submission Checklist, the Publication Ethics Statement and our copyright agreement
As a condition of submission, the Template for Ethical and Legal Declarations must be customized by the submitting author on behalf of all others and uploaded as a separate Word file. Instructions on how to make declarations can be found here
Once your article is accepted you have the option to publish it open access
Our repository policy allows you to distribute 30 PDF copies of your published article to colleagues (the PDF has to include the information that it is an author's copy). Please also feel free to distribute the link to the online abstract
Please also feel free to distribute the link to the online abstract If you have any general questions please visit our FAQ page for authors
For more detailed information please contact the Diagnosis Editorial Office Diagnosis.Editorial@degruyter.com

We look forward to receiving your manuscript!

Hybrid Open Access

In this journal, authors have the option to publish their article under an open access license. Open Access allows you as an author to retain copyright and share your findings with colleagues and interested parties worldwide without any restraints.
Please note that authors from institutions with which we have a transformative agreement can publish open access without paying an article processing charge (APC). More information on the eligible institutions and articles can be found　under the "Funding and Support" tab HERE.

Editorial

Co-Editors
Mark L. Graber, Society to Improve Diagnosis in Medicine (SIDM), Plymouth, MA
Mario Plebani, University Hospital, Padova, Italy

Associate Editors
Christina L. Cifra, Boston Children's Hospital, MA
Giuseppe Lippi, University Hospital of Verona, Verona, Italy
Andrew Olson, University of Minnesota Medical School, Minneapolis, MN
Satid Thammasitboon, Baylor College of Medicine, Texas Children's Hospital, Houston, TX
Dario Torre, Primary Uniformed Services, University of Medicine, Bethesda, MD
Laura Zwaan, Institute of Medical Education Research Rotterdam (iMERR), Erasmus MC, Rotterdam, Netherlands

Section Editors – Case Reports
Andrew Parsons, University of Virginia, Charlottesviille, VA
Melissa Plesac, University of Minnesota Medical Center, Minneapolis, MN
Verity Schaye, New York University School of Medicine, New York, NY

Editorial Board
Daniela Basso, University Hospital of Padova, Padova, Italy
Carmel Crock, Melbourne, Royal Victorian Eye and Ear Hospital, Australia
Pat Croskerry, Dalhousie University, Halifax, Canada
Gurpreet Dhaliwal, San Francisco VA Medical Center, San Francisco, CA
John Ely, University of Iowa Carver College of Medicine, Iowa City, IA
Evangelos Giannitsis, University of Heidelberg, Heidelberg, Germany
Michael Laposata, University of Texas Medical Branch, Galveston, TX
Yoryos Lyratzopoulos, University of Cambridge, Cambridge, United Kingdom
Jason Maude, Isabel Healthcare, Surrey, United Kingdom
David Newman-Toker, Johns Hopkins Hospital, Baltimore, MD
Joseph J. Rencic, Boston University School of Medicine, Boston, MA
Taro Shimizu, Dokkyo Medical University Graduate School of Medicine, Tochigi, Japan
Geeta Singhal, Baylor College of Medicine, Pediatrics, Houston, TX
Dean F. Sittig, University of Texas Health Science Center, Houston, TX
Alexander von Meyer, Weiden, Germany

Editorial Office
Heike Jahnke
Walter de Gruyter GmbH
Genthiner Str. 13
10785 Berlin
Germany
Tel. +49-30-26005-220
E-mail: diagnosis.editorial@degruyter.com

(Deutsch)

Online ISSN: 2194-802X
Type: Journal
Language: English
Publisher: De Gruyter
First published: January 22, 2014
Publication Frequency: 4 Issues per Year
Audience: academics, physicians, educators, healthcare managers and leaders, patients, the diagnostic industry, and policy makers

Diagnosis

Official Journal of the Society to Improve Diagnosis in Medicine (SIDM)

Frontmatter

Diagnostic errors in uncommon conditions: a systematic review of case reports of diagnostic errors

Abstract

Routine blood test markers for predicting liver disease post HBV infection: precision pathology and pattern recognition

Abstract

The challenge of clinical reasoning in chronic multimorbidity: time and interactions in the Health Issues Network model

Abstract

The first diagnostic excellence conference in Japan

Abstract

Clouds across the new dawn for clinical, diagnostic and biological data: accelerating the development, delivery and uptake of personalized medicine

Abstract

Towards diagnostic excellence on academic ward teams: building a conceptual model of team dynamics in the diagnostic process

Abstract

Error codes at autopsy to study potential biases in diagnostic error

Abstract

Multicenter evaluation of a method to identify delayed diagnosis of diabetic ketoacidosis and sepsis in administrative data

Abstract

Detection of fake papers in the era of artificial intelligence

Abstract

Is language an issue? Accuracy of the German computerized diagnostic decision support system ISABEL and cross-validation with the English counterpart

Abstract

The feasibility of a mystery case curriculum to enhance diagnostic reasoning skills among medical students: a process evaluation

Abstract

Internal medicine intern performance on the gastrointestinal physical exam

Abstract

Scaling up a diagnostic pause at the ICU-to-ward transition: an exploration of barriers and facilitators to implementation of the ICU-PAUSE handoff tool

Abstract

Learned cautions regarding antibody testing in mast cell activation syndrome

Abstract

Diagnostic properties of natriuretic peptides and opportunities for personalized thresholds for detecting heart failure in primary care

Abstract

Incomplete filling of spray-dried K2EDTA evacuated blood tubes: impact on measuring routine hematological parameters on Sysmex XN-10

Abstract

The diagnostic accuracy of AI-based predatory journal detectors: an analogy to diagnosis

Explainable AI for gut microbiome-based diagnostics: colorectal cancer as a case study

Restless X syndrome: a new diagnostic family of nocturnal, restless, abnormal sensations of various body parts

Retraction of: Establishing a stable platform for the measurement of blood endotoxin levels in the dialysis population

Incomplete filling of spray-dried K₂EDTA evacuated blood tubes: impact on measuring routine hematological parameters on Sysmex XN-10