Added diagnostic value of routinely measured hematology variables in diagnosing immune checkpoint inhibitor mediated toxicity in the emergency department.

BACKGROUND: Immune checkpoint inhibitors (ICI) show remarkable results in cancer treatment, but at the cost of immune-related adverse events (irAE). irAE can be difficult to differentiate from infections or tumor progression, thereby challenging treatment, especially in the emergency department (ED) where time and clinical information are limited. As infections are traceable in blood, we were interested in the added diagnostic value of routinely measured hematological blood cell characteristics in addition to standard diagnostic practice in the ED to aid irAE assessment. METHODS: Hematological variables routinely measured with our hematological analyzer (Abbott CELL-DYN Sapphire) were retrieved from Utrecht Patient Oriented Database (UPOD) for all patients treated with ICI who visited the ED between 2013 and 2020. To assess the added diagnostic value, we developed and compared two models; a base logistic regression model trained on the preliminary diagnosis at the ED, sex, and gender, and an extended model trained with lasso that also assessed the hematology variables. RESULTS: A total of 413 ED visits were used in this analysis. The extended model showed an improvement in performance (area under the receiver operator characteristic curve) over the base model, 0.79 (95% CI 0.75-0.84), and 0.67 (95% CI 0.60-0.73), respectively. Two standard blood count variables (eosinophil granulocyte count and red blood cell count) and two advanced variables (coefficient of variance of neutrophil depolarization and red blood cell distribution width) were associated with irAE. CONCLUSION: Hematological variables are a valuable and inexpensive aid for irAE diagnosis in the ED. Further exploration of the predictive hematological variables could yield new insights into the pathophysiology underlying irAE and in distinguishing irAE from other inflammatory conditions.

Shorter laboratory turnaround time is associated with shorter emergency department length of stay: a retrospective cohort study.

BACKGROUND: A longer emergency department length of stay (EDLOS) is associated with poor outcomes. Shortening EDLOS is difficult, due to its multifactorial nature. A potential way to improve EDLOS is through shorter turnaround times for diagnostic testing. This study aimed to investigate whether a shorter laboratory turnaround time (TAT) and time to testing (TTT) were associated with a shorter EDLOS. METHODS: A retrospective cohort study was performed, including all visits to the emergency department (ED) of an academic teaching hospital from 2017 to 2020 during which a standardized panel of laboratory tests had been ordered. TTT was calculated as the time from arrival in the ED to the ordering of laboratory testing. TAT was calculated as the time from test ordering to the reporting of the results, and was divided into a clinical and a laboratory stage. The outcome was EDLOS in minutes. The effect of TTT and TAT on EDLOS was estimated through a linear regression model. RESULTS: In total, 23,718 ED visits were included in the analysis. Median EDLOS was 199.0 minutes (interquartile range [IQR] 146.0-268.0). Median TTT was 7.0 minutes (IQR 2.0-12.0) and median TAT was 51.1 minutes (IQR 41.1-65.0). Both TTT and TAT were positively associated with EDLOS. The laboratory stage comprised a median of 69% (IQR 59-78%) of total TAT. CONCLUSION: Longer TTT and TAT are independently associated with longer EDLOS. As the laboratory stage predominantly determines TAT, it provides a promising target for interventions to reduce EDLOS and ED crowding.

A Wolf in Sheep's Clothing: Reuse of Routinely Obtained Laboratory Data in Research.

Electronic health records (EHRs) contain valuable data for reuse in science, quality evaluations, and clinical decision support. Because routinely obtained laboratory data are abundantly present, often numeric, generated by certified laboratories, and stored in a structured way, one may assume that they are immediately fit for (re)use in research. However, behind each test result lies an extensive context of choices and considerations, made by both humans and machines, that introduces hidden patterns in the data. If they are unaware, researchers reusing routine laboratory data may eventually draw incorrect conclusions. In this paper, after discussing health care system characteristics on both the macro and micro level, we introduce the reader to hidden aspects of generating structured routine laboratory data in 4 steps (ordering, preanalysis, analysis, and postanalysis) and explain how each of these steps may interfere with the reuse of routine laboratory data. As researchers reusing these data, we underline the importance of domain knowledge of the health care professional, laboratory specialist, data manager, and patient to turn routine laboratory data into meaningful data sets to help obtain relevant insights that create value for clinical care.

Redundant laboratory testing on referral from general practice to the outpatient clinic: a post-hoc analysis.

BACKGROUND: Inappropriately repeated laboratory testing is a commonly occurring problem. However, this has not been studied extensively in the outpatient clinic after referral by GPs. AIM: The aim of this study was to investigate how often laboratory tests ordered by the GP were repeated on referral to the outpatient clinic, and how many of the normal test results remained normal on repetition. DESIGN & SETTING: This is a post-hoc analysis of a study on laboratory testing strategies in patients newly referred to the outpatient clinic between April 2015 and April 2017. METHOD: All patients who had a referral letter including laboratory test results ordered by the GP were included. These results were compared with the laboratory test results ordered in the outpatient clinic. RESULTS: Data were available for 295 patients, 191 of which had post-visit testing done. In this group, 56% of tests ordered by the GP were repeated. Tests with abnormal results were repeated more frequently than tests with normal results (65% versus 53%; P<0.001). A longer test interval was associated with slightly smaller odds of tests being repeated (odds ratio [OR] 0.97, 95% confidence interval [CI] = 0.95 to 0.99; P = 0.003). Of the tests with normal test results that were repeated, 90% remained normal. This was independent of testing interval or testing strategy. CONCLUSION: Laboratory tests ordered by the GP are commonly repeated on referral to the outpatient clinic. The number of test results remaining normal on repetition suggests a high level of redundancy in laboratory test repetition.

Association of a Multifaceted Intervention With Ordering of Unnecessary Laboratory Tests Among Caregivers in Internal Medicine Departments.

Importance: Inappropriate use of laboratory testing is a challenging problem. Estimated overuse rates of approximately 20% have been reported. Effective, sustainable solutions to stimulate optimal use are needed. Objective: To determine the association of a multifaceted intervention with laboratory test volume. Design, Setting, and Participants: A before-after quality improvement study was performed between August 1, 2016, and April 30, 2018, in the internal medicine departments of 4 teaching hospitals in the Netherlands. Data on laboratory order volumes from 19 comparable hospitals were used as controls. The participants were clinicians ordering laboratory tests. Interventions: The intervention included creating awareness through education and feedback, intensified supervision of residents, and changes in order entry systems. Interventions were performed by local project teams and guided by a central project team during a 6-month period. Sustainability was investigated during an 8-month follow-up period. Main Outcomes and Measures: The primary outcome was the change in slope for laboratory test volume. Secondary outcomes were change in slope for laboratory expenditure, order volumes and expenditure for other diagnostic procedures, and clinical outcomes. Data were collected on duration of hospital stay, rate of repeated outpatient visits, 30-day readmission rate, and rate of unexpected prolonged duration of hospital stay for patients admitted for pneumonia. Results: The numbers of internists and residents ordering tests in hospitals 1 to 4 were 16 and 30, 18 and 20, 13 and 17, and 21 and 60, respectively. Statistically significant changes in slope for laboratory test volume per patient contact were found at hospital 1 (change in slope, -1.55; 95% CI, -1.98 to -1.11; P < .001), hospital 3 (change in slope, -0.74; 95% CI, -1.42 to -0.07; P = .03), and hospital 4 (change in slope, -2.18; 95% CI, -3.27 to -1.08; P < .001). At hospital 2, the change in slope was not statistically significant (-0.34; 95% CI, -2.27 to 1.58; P = .73). Laboratory test volume per patient contact decreased by 11.4%, whereas the volume increased by 2.4% in 19 comparable hospitals. Statistically significant changes in slopes for laboratory costs and volumes and costs for other diagnostic procedures were also observed. Clinical outcomes were not associated with negative changes. Important facilitators were education, continuous attention for overuse, feedback, and residents' involvement. Important barriers were difficulties in data retrieval, difficulty in incorporation of principles in daily practice, and high resident turnover. Conclusions and relevance: A set of interventions aimed at changing caregivers' mindset was associated with a reduction in the laboratory test volume in all departments, whereas the volume increased in comparable hospitals in the Netherlands. This study provides a framework for nationwide implementation of interventions to reduce unnecessary laboratory testing.

Unbound Fraction of Clozapine Significantly Decreases with Elevated Plasma Concentrations of the Inflammatory Acute-Phase Protein Alpha-1-Acid Glycoprotein.

BACKGROUND: During inflammation, elevated total (unbound plus protein-bound) clozapine plasma concentrations have been observed. Elevated alpha-1-acid glycoprotein concentrations during inflammation are suggested to cause increased plasma clozapine-alpha-1-acid glycoprotein binding, resulting in elevated total clozapine plasma concentrations without significant changes in unbound concentrations. Here, we investigated the association between alpha-1-acid glycoprotein plasma concentrations and clozapine unbound fraction. METHODS: First, 25 and 60 µL of alpha-1-acid glycoprotein solution (20 mg/mL) were added to plasma samples (n = 3) of clozapine users (spiking experiment). Second, the association between alpha-1-acid glycoprotein plasma concentration and clozapine unbound fraction was assessed in patient samples (patient study). Samples were determined by liquid chromatography-tandem mass spectrometry. Data were analyzed with a paired t test (spiking experiment) and an unpaired t test (patient study). RESULTS: The spiking experiment showed significantly lower mean unbound fractions following 25- and 60-µL alpha-1-acid glycoprotein spikes (relative reductions of 28.3%, p = 0.032 and 43.4%, p = 0.048). In the patient study, total clozapine plasma concentrations were 10% higher in elevated (n = 6) compared with normal alpha-1-acid glycoprotein (n = 20) samples [525 µg/L vs. 479 µg/L, mean difference = 47 µg/L (95% confidence interval -217 to 310), p = 0.72]. Elevated alpha-1-acid glycoprotein samples had a 26% lower mean unbound fraction compared with normal samples [1.22% vs. 1.65%, mean difference = -0.43% (95% confidence interval -0.816 to -0.0443), p = 0.03]. CONCLUSIONS: Both the spiking experiment and patient study showed a significant association between elevated alpha-1-acid glycoprotein plasma concentrations and a lower clozapine unbound fraction. Future studies should include clinical data to examine whether this association is clinically relevant, suggesting any clozapine dose adjustments.

A Human(e) Factor in Clinical Decision Support Systems.

The overwhelming amount, production speed, multidimensionality, and potential value of data currently available-often simplified and referred to as big data -exceed the limits of understanding of the human brain. At the same time, developments in data analytics and computational power provide the opportunity to obtain new insights and transfer data-provided added value to clinical practice in real time. What is the role of the health care professional in collaboration with the data scientist in the changing landscape of modern care? We discuss how health care professionals should provide expert knowledge in each of the stages of clinical decision support design: data level, algorithm level, and decision support level. Including various ethical considerations, we advocate for health care professionals to responsibly initiate and guide interprofessional teams, including patients, and embrace novel analytic technologies to translate big data into patient benefit driven by human(e) values.

Routine Blood Tests Do Not Predict Survival in Patients with Glioblastoma-Multivariable Analysis of 497 Patients.

BACKGROUND: Multiple reports have attributed a prognostic value to routine blood tests results for patients with glioblastoma. However, these studies have reported conflicting results and have often had small sample sizes. We sought to validate the prognostic value of the described tests in an independent glioblastoma patient population. METHODS: We performed a retrospective single-center multivariable analysis of 497 patients with glioblastoma who had postoperatively undergone radiotherapy and/or chemotherapy to identify the prognostic value for median overall survival of hemoglobin, white blood cell, monocyte, neutrophil, leukocyte, and platelet counts, neutrophil/lymphocyte ratio, C-reactive protein, erythrocyte sedimentation rate, activated partial thromboplastin time, prothrombin time, and lactate dehydrogenase. We also evaluated known prognostic factors for survival such as patient age, intervention type, IDH1 status, Karnofsky clinical performance status, and postoperative treatment modality. RESULTS: In a multivariable model, after correcting for multiple testing bias, biopsy alone (hazard ratio, 0.35; 95% confidence interval, 0.26-0.49; false discovery rate-adjusted P < 0.001) and monotherapy after surgery (hazard ratio, 0.46; 95% confidence interval, 0.33-0.66; false discovery rate-adjusted P < 0.001) remained significantly associated with worse median overall survival. Patient age and Karnofsky performance status score ≥70 did not significantly influence survival in the multivariable model. No routine blood test included in the multivariable analysis was significantly associated with survival. CONCLUSIONS: In the present study, hemoglobin, white blood cell, monocyte, neutrophil, leukocyte, and platelet counts, neutrophil/lymphocyte ratio, C-reactive protein, erythrocyte sedimentation rate, activated partial thromboplastin time, prothrombin time, and lactate dehydrogenase levels did not independently predict for overall survival in patients with glioblastoma.

[Data-driven integrated diagnostics: the natural evolution of clinical chemistry?] / Data-gedreven integrale diagnostiek.

In the near future, making a correct medical diagnosis will be increasingly supported by artificial intelligence. The development of algorithms that integrate all data from an individual into the diagnostic process calls for a multidisciplinary approach that includes not only healthcare professionals and patients, but also data scientists. Because of the position of the clinical chemist in the current health care process, this medical specialist is naturally suited to initiate the development of self-learning diagnostic algorithms and to take the lead in the process to take big data to the next level and create value for health care.

Improving home haemodialysis: Stability evaluation of routine clinical chemistry analytes in blood samples of haemodialysis patients.

INTRODUCTION: A growing number of dialysis patients is treated with home haemodialysis. Our current pre-analytical protocols require patients to centrifuge the blood sample and transfer the plasma into a new tube at home. This procedure is prone to errors and precludes accurate bicarbonate measurement, required for determining dialysate bicarbonate concentration and maintaining acid-base status. We therefore evaluated whether cooled overnight storage of gel separated plasma is an acceptable alternative. MATERIALS AND METHODS: Venous blood of 34 haemodialysis patients was collected in 2 lithium heparin blood collection tubes with gel separator (LH PSTTM II, REF 367374; Becton Dickinson, New Jersey, USA). One tube was analysed directly for measurement of bicarbonate, potassium, calcium, phosphate, glucose, urea, lactate, aspartate aminotransferase (AST), and lactate dehydrogenase (LD); whereas the other was centrifuged and stored unopened at 4 °C and analysed 24 h later. To measure analyte stability after 24 h of storage, the mean difference was calculated and compared to the total allowable error (TEa) which was used as acceptance limit. RESULTS: Potassium (Z = - 4.28, P < 0.001), phosphate (Z = - 3.26, P = 0.001), lactate (Z = - 5.11, P < 0.001) and AST (Z = - 2.71, P = 0.007) concentrations were higher, whereas glucose (Z = 4.00, P < 0.001) and LD (Z = 3.13, P = 0.002) showed a reduction. All mean differences were smaller than the TEa and thus not clinically relevant. Bicarbonate (Z = 0.69, P = 0.491), calcium (Z = - 0.23, P = 0.815) and urea (Z = 0.81, P =0.415) concentrations were stable. CONCLUSIONS: Our less complex, user-friendly pre-analytical procedure resulted in at least 24 h stability of analytes relevant for monitoring haemodialysis, including bicarbonate. This allows shipment and analysis the next day.

A Multicenter Before-After Study on Reducing Unnecessary Diagnostics by Changing the Attitude of Caregivers: Protocol for the RODEO Project.

BACKGROUND: Appropriate use of diagnostic laboratory tests is challenging, and estimates of 20% for overutilization and 45% for underutilization have been reported. Introducing effective and sustainable solutions to stimulate optimal use of laboratory testing in clinical practice is a challenge. A recent pilot study from our group, focusing on increasing the awareness about appropriate laboratory testing with the aim of changing the mindset of health care workers, has shown promising results. In this project, we aim to extend this multistep intervention to the internal medicine departments of 4 large Dutch hospitals. We aim to reduce unnecessary laboratory testing by 5%. OBJECTIVE: Our primary objective is to determine the effect of our intervention on diagnostic laboratory test order volume. Our secondary objectives are to determine the effect of our intervention on laboratory expenditure and order volumes, expenditures for other diagnostic modalities, and clinical patient outcomes. We will also analyze the barriers and facilitators for deimplementation of unnecessary laboratory testing. METHODS: The main interventions of this before-after study will be an intensified supervision of residents by experienced physicians regarding test ordering, creating awareness through education and monthly feedback on ordering patterns, and changes in (computerized) order entry systems. RESULTS: At the time of publication of this protocol, the project is in the phase of data collection. We expect to present data on reduction early in the fourth quarter of 2018. CONCLUSIONS: In this project, we aim to reduce the unnecessary diagnostic testing in the internal medicine departments of 4 teaching hospitals. Although the main interventions will be similar, each clinic is given the opportunity to focus on the specific facets of the interventions as deemed useful according to the local situation. If effective, the study provides a framework for a nationwide initiative for reducing inappropriate laboratory testing. REGISTERED REPORT IDENTIFIER: RR1-10.2106/10473.

Commonly available hematological biomarkers are associated with the extent of coronary calcifications.

BACKGROUND AND AIMS: We aimed to improve the understanding of potential associations between commonly available hematological biomarkers and the coronary artery calcification (CAC) score, which may help unravel the pathophysiology of coronary calcifications and subclinical coronary artery disease. METHODS: A cross-sectional study was performed within the Utrecht Patient Oriented Database (UPOD). Patients with suspected or known coronary artery disease who underwent CT CAC scoring as well as standard hematology analysis that was part of routine clinical care (within 3 months of CT acquisition) were included. Complete hematology datasets were extracted from hematology analyzers. Linear regression adjusted for potential confounders was used to assess if hematological biomarkers were related to the CAC score. RESULTS: In total, 1504 patients were included, of whom 43% (n = 647) had a CAC score of 0. Mean age (±SD) was 53 ±â€¯13 years, and 34% of patients were women. Red blood cell distribution width (RDW, ß = 0.20 [0.05-0.36], p=0.007), the fraction of immature reticulocytes (ß = 0.97 [0.10-6.43], p=0.004), coefficient of variation of neutrophil lobularity (ß = 0.13 [0.01-0.25], p=0.040) and mean lymphocyte cell size (ß = 0.21 [0.08-0.34], p=0.001) were positively associated with the CAC score after adjustment for age, sex, body mass index (BMI), diabetes, glomerular filtration rate (GFR) and high-density lipoprotein (HDL). CONCLUSIONS: This study confirms the known association of RDW with the CAC score, and presents the fraction of immature reticulocytes, coefficient of variation of neutrophil lobularity, and mean lymphocyte cell size as new markers associated with a higher CAC score.

Reducing Test Utilization in Hospital Settings: A Narrative Review.

BACKGROUND: Studies addressing the appropriateness of laboratory testing have revealed approximately 20% overutilization. We conducted a narrative review to (1) describe current interventions aimed at reducing unnecessary laboratory testing, specifically in hospital settings, and (2) provide estimates of their efficacy in reducing test order volume and improving patient-related clinical outcomes. METHODS: The PubMed, Embase, Scopus, Web of Science, and Canadian Agency for Drugs and Technologies in Health-Health Technology Assessment databases were searched for studies describing the effects of interventions aimed at reducing unnecessary laboratory tests. Data on test order volume and clinical outcomes were extracted by one reviewer, while uncertainties were discussed with two other reviewers. Because of the heterogeneity of interventions and outcomes, no meta-analysis was performed. RESULTS: Eighty-four studies were included. Interventions were categorized into educational, (computerized) provider order entry [(C)POE], audit and feedback, or other interventions. Nearly all studies reported a reduction in test order volume. Only 15 assessed sustainability up to two years. Patient-related clinical outcomes were reported in 45 studies, two of which found negative effects. CONCLUSIONS: Interventions from all categories have the potential to reduce unnecessary laboratory testing, although long-term sustainability is questionable. Owing to the heterogeneity of the interventions studied, it is difficult to conclude which approach was most successful, and for which tests. Most studies had methodological limitations, such as the absence of a control arm. Therefore, well-designed, controlled trials using clearly described interventions and relevant clinical outcomes are needed.

Effect of Monocyte-to-Lymphocyte Ratio on Heart Failure Characteristics and Hospitalizations in a Coronary Angiography Cohort.

Inflammation is a shared mechanism in coronary artery disease (CAD) and subsequent heart failure (HF), and circulating monocyte and lymphocyte counts predict CAD severity and outcomes. We investigated whether the monocyte-to-lymphocyte ratio (MLR) correlates with biomarkers of HF and extent of CAD, as well as future HF hospitalizations in patients undergoing coronary angiography. Therefore, we studied 1754 patients undergoing coronary angiography for stable CAD, unstable angina, or myocardial infarction. MLR was determined at blood draw before angiography and related cross-sectionally to HF biomarkers (ejection fraction, N-terminal pro-B-type natriuretic peptide [NTproBNP] levels) and CAD severity, as well as longitudinally with risk of HF hospitalizations during follow-up. In the entire cohort, median (interquartile range) MLR was 0.32 (0.24 to 0.43). High MLR was defined as the upper quartile and significantly associated with nonstable CAD (unstable angina; odds ratio [OR] 1.13, 95% confidence interval 1.06 to 1.21] or myocardial infarction [OR 1.10, 1.04 to 1.16]), more severe CAD (OR 1.39, 1.15 to 1.68), poorer ejection fraction (OR 1.63, 1.29 to 2.05), and higher NTproBNP levels (ß 0.78, 0.59 to 0.96), all p <0.001. The associations with nonstable CAD and NTproBNP remained highly significant after covariate adjustment. Over a mean follow-up of 1.3 years, 46 HF hospitalizations occurred. A high MLR was significantly and independently predictive of HF hospitalizations during follow-up (hazard ratio 2.1 [1.1 to 4.1], p = 0.039) after adjustment for covariates and addition of MLR to the basic model significantly improved reclassification. In conclusion, MLR is strongly related to HF markers and predicts HF hospitalizations during follow-up in patients with CAD.

White blood cell count and new-onset atrial fibrillation after cardiac surgery.

BACKGROUND: Postoperative new-onset atrial fibrillation (PNAF) is the most common complication following cardiac surgery. The inflammatory response, as a potential underlying mechanism, has been extensively studied. In small studies, the white blood cell count (WBC) has been shown to be the only consistent inflammatory marker associated with PNAF. This study aimed to determine the association between perioperative WBC response and PNAF in a larger study cohort. METHODS: Patients ≥18years, undergoing elective cardiac surgery with a preoperative sinus rhythm were included. WBC was routinely measured preoperatively, and daily during the first four postoperative days. Main outcomes were the difference between peak postoperative WBC and neutrophil/lymphocyte ratio (N/L ratio) and preoperative WBC and N/L ratio (ΔWBC and ΔN/L ratio respectively). Development of PNAF was evaluated in all patients with continuous 12-lead ECG monitoring. RESULTS: 657 patients were included and 277 (42%) developed PNAF. Univariable analyses showed a statistically significant relationship between ΔWBC (P=0.030) and ΔN/L ratio (P=0.002), and PNAF. In multivariable analysis no significant relationship was found between ΔWBC (OR: 1.14 per 1×109/L increase; 95% CI: 0.65-2.03; P=0.645), ΔN/L ratio (OR: 1.65 per 1×109/L increase; 95% CI: 0.94-2.90; P=0.089), and PNAF. Increasing age (OR: 1.08 per year; 95% CI: 1.01-1.16; P=0.022) and (additional) valve surgery (versus CABG) (OR: 4.96; 95% CI: 2.07-6.91; P≤0.001) were associated with PNAF. CONCLUSIONS: The perioperative WBC response and its components were not associated with the development of PNAF.

Routinely analyzed leukocyte characteristics improve prediction of mortality after coronary angiography.

BACKGROUND: Inflammation and leukocyte infiltration are hallmarks of atherosclerosis. Clinically routine hematology analyzers mostly perform an entire differential blood count by default, irrespective of the requested parameter. We hypothesize that these normally unreported leukocyte characteristics associate with coronary artery disease (CAD) severity and can improve prediction of mortality in coronary angiography patients. METHODS: We studied coronary angiography patients suspected of CAD (n = 1015) from the Utrecht Coronary Biobank cohort. Leukocyte characteristics were routinely assessed in blood drawn directly prior to angiography using an automated hematology analyzer and extracted from the Utrecht patient oriented database (UPOD) database. Patients were followed up for a median duration of 805 days, during which 65 patients died. We evaluated the association of leukocyte characteristics with synergy between PCI with taxus and cardiac surgery (SYNTAX) score as a measure of CAD severity, all-cause and cardiovascular mortality and major adverse cardiovascular events (MACEs). In order to determine the improvement of risk prediction, we calculated continuous net reclassification improvement (cNRI) and integrated discrimination improvement (IDI). RESULTS: Monocyte percentage showed strong independent predictive value for all-cause mortality (hazard ratio (HR) 1.44 (1.19-1.74), p < 0.001), and the monocyte-to-lymphocyte ratio performed best for cardiovascular mortality (HR 1.42 (1.11-1.81), p = 0.005). The cNRIs and IDIs of leukocyte characteristics for all-cause mortality confirmed the improvement in mortality risk prediction. No significantly predictive leukocyte characteristics were found for MACEs. CONCLUSION: Readily available yet unreported leukocyte characteristics from routine hematology analyzers significantly improved prediction of mortality in coronary angiography patients on top of clinical characteristics.

Methodologies for evaluating strategies to reduce diagnostic error: report from the research summit at the 7th International Diagnostic Error in Medicine Conference.

In this article we review current evidence on strategies to evaluate diagnostic error solutions, discuss the methodological challenges that exist in investigating the value of these strategies in patient care, and provide recommendations for methods that can be applied in investigating potential solutions to diagnostic errors. These recommendations were developed iteratively by the authors based upon initial discussions held during the Research Summit of the 7th Annual Diagnostic Error in Medicine Conference in September 2014. The recommendations include the following elements for designing studies of diagnostic research solutions: (1) Select direct and indirect outcomes measures of importance to patients, while also practical for the particular solution; (2) Develop a clearly-stated logic model for the solution to be tested; (3) Use rapid, iterative prototyping in the early phases of solution testing; (4) Use cluster-randomized clinical trials where feasible; (5) Avoid simple pre-post designs, in favor of stepped wedge and interrupted time series; (6) Leverage best practices for patient safety research and engage experts from relevant domains; and (7) Consider sources of bias and design studies and their analyses to minimize selection and information bias and control for confounding. Areas of diagnostic error mitigation research identified for further attention include: role of competing diagnoses, understanding the impacts of organizational culture, timing of diagnosis, and sequencing of research studies. Future research will likely require novel clinical, health services, and qualitative research methods to address the age-old problem of arriving at an accurate diagnosis.