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This paper considers the phenomenon of waiting lists in a healthcare setting, which is characterised by limitations on the national expenditure, to explore the potentials of an operations management perspective. A reference framework for waiting list management is described, distinguishing different levels of planning in healthcare--national, regional, hospital and process--that each contributes to the existence of waiting lists through managerial decision making. In addition, different underlying mechanisms in demand and supply are distinguished, which together explain the development of waiting lists. It is our contention that within this framework a series of situation specific models should be designed to support communication and decision making. This is illustrated by the modelling of the demand for cataract treatment in a regional setting in the south-eastern part of the Netherlands. An input-output model was developed to support decisions regarding waiting lists. The model projects the demand for treatment at a regional level and makes it possible to evaluate waiting list impacts for different scenarios to meet this demand. [ABSTRACT FROM AUTHOR]

The article offers information on the report on Autosomal dominant polycystic kidney disease (ADPKD). Topics discussed include information on the characterization of the ADPKD by the presence of multiple cysts residing in the kidneys and liver; discussions on the study reveals that pharmacokinetic suitability of ciprofloxacin for treatment of hepatic cyst infections; and the information on the study on cyst infection, confirmed by cyst fluid culture for E. coli and Klebsiella pneumoniae.

Objectives: Iron deficiency anemia is a significant global health concern, diagnosed by measuring hemoglobin concentrations in combination with plasma ferritin concentration. This study investigated the variability in ferritin reference intervals among laboratories in the Netherlands and examined how this affects the identification of iron-related disorders., Methods: Ferritin reference intervals from 52 Dutch ISO15189-certified medical laboratories were collected. Ferritin, hemoglobin and mean corpuscular volume data of non-anemic apparently healthy primary care patients, measured by four laboratory platforms (Beckman, Abbott, Siemens, and Roche), were collected (n=397,548). Median ferritin levels were determined per platform, stratified by sex and age. The proportion of ferritin measurements outside of the reference interval was calculated using the reference intervals from the 52 laboratories (using a total of n=1,093,442 ferritin measurements). Lastly, ferritin data from 3,699 patients as captured in general practitioner (GP) data from the PHARMO Data Network were used to assess the variation of abnormal ferritin measurements per GP., Results: Median plasma ferritin concentrations were approximately four times higher in men and twice as high in postmenopausal women compared to premenopausal women. Moreover, there are substantial differences in the median plasma ferritin concentration between the four platforms. However, even among laboratories using the same platform, ferritin reference intervals differ widely. This leads to significant differences in the percentages of measurements classified as abnormal, with the percentage of ferritin measurements below the reference limit in premenopausal women ranging from 11 to 53 %, in postmenopausal women from 3 to 37 %, and in men from 2 to 19 %. The percentage of ferritin measurements above the reference limit in premenopausal women ranged from 0.2 to 11 %, in postmenopausal women from 3 to 36 % and in men from 7 to 32 %., Conclusions: The lack of harmonization in ferritin measurement and the disagreement in plasma ferritin reference intervals significantly impact the interpretation of the iron status of patients and thereby the number of iron disorder diagnoses made. Standardization or harmonization of the ferritin assays and establishing uniform reference intervals and medical decision limits are essential to reduce the substantial variability in clinical interpretations of ferritin results., (© 2024 Walter de Gruyter GmbH, Berlin/Boston.)

Background: Hemoglobinopathies, the most common inherited blood disorder, are frequently underdiagnosed. Early identification of carriers is important for genetic counseling of couples at risk. The aim of this study was to develop and validate a novel machine learning model on a multicenter data set, covering a wide spectrum of hemoglobinopathies based on routine complete blood count (CBC) testing., Methods: Hemoglobinopathy test results from 10 322 adults were extracted retrospectively from 8 Dutch laboratories. eXtreme Gradient Boosting (XGB) and logistic regression models were developed to differentiate negative from positive hemoglobinopathy cases, using 7 routine CBC parameters. External validation was conducted on a data set from an independent Dutch laboratory, with an additional external validation on a Spanish data set (n = 2629) specifically for differentiating thalassemia from iron deficiency anemia (IDA)., Results: The XGB and logistic regression models achieved an area under the receiver operating characteristic (AUROC) of 0.88 and 0.84, respectively, in distinguishing negative from positive hemoglobinopathy cases in the independent external validation set. Subclass analysis showed that the XGB model reached an AUROC of 0.97 for β-thalassemia, 0.98 for α0-thalassemia, 0.95 for homozygous α+-thalassemia, 0.78 for heterozygous α+-thalassemia, and 0.94 for the structural hemoglobin variants Hemoglobin C, Hemoglobin D, Hemoglobin E. Both models attained AUROCs of 0.95 in differentiating IDA from thalassemia., Conclusions: Both the XGB and logistic regression model demonstrate high accuracy in predicting a broad range of hemoglobinopathies and are effective in differentiating hemoglobinopathies from IDA. Integration of these models into the laboratory information system facilitates automated hemoglobinopathy detection using routine CBC parameters., (© Association for Diagnostics & Laboratory Medicine 2024. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Clinical judgement in primary care is more often decisive than in the hospital. Clinical decision rules (CDRs) can help general practitioners facilitating the work-through of differentials that follows an initial suspicion, resulting in a concrete 'course of action': a 'rule-out' without further testing, a need for further testing, or a specific treatment. However, in daily primary care, the use of CDRs is limited to only a few isolated rules. In this paper, we aimed to provide insight into the laborious path required to implement a viable CDR. At the same time, we noted that the limited use of CDRs in primary care cannot be explained by implementation barriers alone. Through the case study of the Oudega rule for the exclusion of deep vein thrombosis, we concluded that primary care CDRs come out best if they are tailor-made, taking into consideration the specific context of primary health care. Current CDRs should be evaluated frequently, and future decision rules should anticipate the latest developments such as the use of point-of-care (POC) tests. Hence, such new powerful diagnostic CDRs could improve and expand the possibilities for patient-oriented primary care.

Background: Diabetes mellitus, cardiovascular diseases, chronic kidney disease, and thyroid diseases are chronic diseases that require regular monitoring through blood tests. This paper first investigates the experiences of chronic care patients with venipuncture and their expectations of an at-home blood-sampling device, and then assesses the impact on societal costs of implementing such a device in current practice., Methods: An online survey was distributed among chronic care patients to gain insight into their experience of blood sampling in current practice, and their expectations of an at-home blood-sampling device. The survey results were used as input parameters in a patient-level monte carlo analysis developed to represent a hypothetical cohort of Dutch chronically ill patients to investigate the impact on societal costs compared to usual care., Results: In total, 1311 patients participated in the survey, of which 31% experience the time spent on the phlebotomy appointment as a burden. Of all respondents, 71% prefer to use an at-home blood-sampling device to monitor their chronic disease. The cost analysis indicated that implementing an at-home blood-sampling device increases the cost of phlebotomy itself by €27.25 per patient per year, but it reduces the overall societal costs by €24.86 per patient per year, mainly due to limiting productivity loss., Conclusions: Patients consider an at-home blood-sampling device to be more user-friendly than venous phlebotomy on location. Long waiting times and crowded locations can be avoided by using an at-home blood-sampling device. Implementing such a device is likely cost-saving as it is expected to reduce societal costs., (© 2022. The Author(s).)

Background: In some countries, such as the Netherlands and Norway, point-of-care testing (POCT) is more widely implemented in general practice compared to countries such as England and Australia. To comprehend what is necessary to realize the benefits of POCT, regarding its integration in primary care, it would be beneficial to have an overview of the structure of healthcare operations and the transactions between stakeholders (also referred to as value networks). The aim of this paper is to identify the current value networks in place applying to POCT implementation at general practices in England, Australia, Norway and the Netherlands and to compare these networks in terms of seven previously published factors that support the successful implementation, sustainability and scale-up of innovations., Methods: The value networks were described based on formal guidelines and standards published by the respective governments, organizational bodies and affiliates. The value network of each country was validated by at least two relevant stakeholders from the respective country., Results: The analysis revealed that the biggest challenge for countries with low POCT uptake was the lack of effective communication between the several organizations involved with POCT as well as the high workload for general practitioners (GPs) aiming to implement POCT. It is observed that countries with a single national authority responsible for POCT have a better uptake as they can govern the task of POCT roll-out and management and reduce the workload for GPs by assisting with set-up, quality control, training and support., Conclusion: Setting up a single national authority may be an effective step towards realizing the full benefits of POCT. Although it is possible for day-to-day operations to fall under the responsibility of the GP, this is only feasible if support and guidance are readily available to ensure that the workload associated with POCT is limited and as low as possible., (© 2022 The Author(s); Published by Kerman University of Medical Sciences This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.)

Background: Point-of-care testing (POCT) has shown promising results in the primary care setting to improve antibiotic therapy in respiratory tract infections and it might also aid general practitioners (GPs) to decide if patients should be referred to a hospital in cases of suspected sepsis. We aimed to assess whether biomarkers with possible POCT use can improve the recognition of sepsis in adults in the primary care setting., Methods: We prospectively included adult patients with suspected severe infections during out-of-hours home visits. Relevant clinical signs and symptoms were recorded, as well as the biomarkers C-reactive protein, lactate, procalcitonin, high-sensitive troponin I, N-terminal pro b-type natriuretic peptide, creatinine, urea, and pancreatic stone protein. We used a POCT device for lactate only, and the remaining biomarkers were measured in a laboratory from stored blood samples. The primary outcome was sepsis within 72 h of inclusion. The potential of biomarkers to either rule in or rule out sepsis was tested for individual biomarkers combined with a model consisting of signs and symptoms. Net reclassification indices were also calculated., Results: In total, 336 patients, with a median age of 80 years, were included. One hundred forty-one patients (42%) were diagnosed with sepsis. The C statistic for the model with clinical symptoms and signs was 0.84 (95% CI 0.79-0.88). Both lactate and procalcitonin increased the C statistic to 0.85, but none of the biomarkers significantly changed the net reclassification index., Conclusions: We do not advocate the routine use of POCT in general practice for any of the tested biomarkers of suspected sepsis., Competing Interests: Authors’ Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest: Employment or Leadership: A.R.H. Van Zanten, the Netherlands Society Internal Medicine and NESPEN; R.M. Hopstaken, Chair of Special Interest Group Global Family Doctor Organization WONCA. Consultant or Advisory Role: A.R.H. Van Zanten, Baxter, Cardinal Health, Danone-Nutricia, DIM3, Fresenius Kabi, Mermaid, Lyric, and Nestlé-Novartis; R.M. Hopstaken, Lumiradx, Photondelta, and Abbott. Stock Ownership: None declared. Honoraria: A.R.H. Van Zanten, Baxter, Cardinal Health, Danone-Nutricia, DIM3, Fresenius Kabi, Mermaid, Lyric, and Nestlé-Novartis; R.M. Hopstaken, Lumiradx, Photondelta, and Abbott. Research Funding: This study was funded by ZonMw (grant number 843001811). Abionic and Star-shl provided additional funding. The following manufacturers provided in-kind funding of materials: Philips, Nova Biomedical, and ThermoFisher. T.J.M. Verheij participated in studies that were funded by the EU and partly by Biomerieux, Becton Dickinson, Janssen Pharmaceuticals, and Abbott (IMI projects). A.R.H. van Zanten, Danone-Nutricia, Mermaid Care, Cardinal Health, and Lyric. Expert Testimony: None declared. Patents: None declared. Other Remuneration: A.R.H. Van Zanten, travel expenses from Baxter, Cardinal Health, Danone-Nutricia, DIM3, Fresenius Kabi, Mermaid, Lyric, and Nestlé-Novartis., (© American Association for Clinical Chemistry 2022.)

Objective: To externally validate various prognostic models and scoring rules for predicting short term mortality in patients admitted to hospital for covid-19., Design: Two stage individual participant data meta-analysis., Setting: Secondary and tertiary care., Participants: 46 914 patients across 18 countries, admitted to a hospital with polymerase chain reaction confirmed covid-19 from November 2019 to April 2021., Data Sources: Multiple (clustered) cohorts in Brazil, Belgium, China, Czech Republic, Egypt, France, Iran, Israel, Italy, Mexico, Netherlands, Portugal, Russia, Saudi Arabia, Spain, Sweden, United Kingdom, and United States previously identified by a living systematic review of covid-19 prediction models published in The BMJ , and through PROSPERO, reference checking, and expert knowledge., Model Selection and Eligibility Criteria: Prognostic models identified by the living systematic review and through contacting experts. A priori models were excluded that had a high risk of bias in the participant domain of PROBAST (prediction model study risk of bias assessment tool) or for which the applicability was deemed poor., Methods: Eight prognostic models with diverse predictors were identified and validated. A two stage individual participant data meta-analysis was performed of the estimated model concordance (C) statistic, calibration slope, calibration-in-the-large, and observed to expected ratio (O:E) across the included clusters., Main Outcome Measures: 30 day mortality or in-hospital mortality., Results: Datasets included 27 clusters from 18 different countries and contained data on 46 914patients. The pooled estimates ranged from 0.67 to 0.80 (C statistic), 0.22 to 1.22 (calibration slope), and 0.18 to 2.59 (O:E ratio) and were prone to substantial between study heterogeneity. The 4C Mortality Score by Knight et al (pooled C statistic 0.80, 95% confidence interval 0.75 to 0.84, 95% prediction interval 0.72 to 0.86) and clinical model by Wang et al (0.77, 0.73 to 0.80, 0.63 to 0.87) had the highest discriminative ability. On average, 29% fewer deaths were observed than predicted by the 4C Mortality Score (pooled O:E 0.71, 95% confidence interval 0.45 to 1.11, 95% prediction interval 0.21 to 2.39), 35% fewer than predicted by the Wang clinical model (0.65, 0.52 to 0.82, 0.23 to 1.89), and 4% fewer than predicted by Xie et al's model (0.96, 0.59 to 1.55, 0.21 to 4.28)., Conclusion: The prognostic value of the included models varied greatly between the data sources. Although the Knight 4C Mortality Score and Wang clinical model appeared most promising, recalibration (intercept and slope updates) is needed before implementation in routine care., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at https://www.icmje.org/disclosure-of-interest/ and declare: funding from the European Union’s Horizon 2020 research and innovation programme. ML and FWA have received grants from the Dutch Heart Foundation and ZonMw; FWA has received grants from Novartis Global, Sanofi Genzyme Europe, EuroQol Research Foundation, Novo Nordisk Nederland, Servier Nederland, and Daiichi Sankyo Nederland, and MM has received grants from Czech Ministry of Education, Youth and Sports for the submitted work; RKG has received grants from National Institute for Health and Care Research; FS has received an AWS DDI grant and grants from University of Sheffield and DBCLS; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; TD works with International Societiy for Pharmacoepidemiology Comparative Effectiveness Research Special Interest Group (ISPE CER SIG) on methodological topics related to covid-19 (non-financial); no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Recognising patients who need immediate hospital treatment for sepsis while simultaneously limiting unnecessary referrals is challenging for GPs., Aim: To develop and validate a sepsis prediction model for adult patients in primary care., Design and Setting: This was a prospective cohort study in four out-of-hours primary care services in the Netherlands, conducted between June 2018 and March 2020., Method: Adult patients who were acutely ill and received home visits were included. A total of nine clinical variables were selected as candidate predictors, next to the biomarkers C-reactive protein, procalcitonin, and lactate. The primary endpoint was sepsis within 72 hours of inclusion, as established by an expert panel. Multivariable logistic regression with backwards selection was used to design an optimal model with continuous clinical variables. The added value of the biomarkers was evaluated. Subsequently, a simple model using single cut-off points of continuous variables was developed and externally validated in two emergency department populations., Results: A total of 357 patients were included with a median age of 80 years (interquartile range 71-86), of which 151 (42%) were diagnosed with sepsis. A model based on a simple count of one point for each of six variables (aged >65 years; temperature >38°C; systolic blood pressure ≤110 mmHg; heart rate >110/min; saturation ≤95%; and altered mental status) had good discrimination and calibration (C-statistic of 0.80 [95% confidence interval = 0.75 to 0.84]; Brier score 0.175). Biomarkers did not improve the performance of the model and were therefore not included. The model was robust during external validation., Conclusion: Based on this study's GP out-of-hours population, a simple model can accurately predict sepsis in acutely ill adult patients using readily available clinical parameters., (© The Authors.)

Background: Elevated levels of Chromogranin A (CgA) may be indicative of a neuroendocrine tumour (NET), but increased levels are also observed after intake of proton pump inhibitors (PPIs). The incidence of diagnostic confusion because of this drug-laboratory test interaction (DLTI) was examined., Methods: Medical records of 238 patients with elevated CgA concentrations were obtained from three hospitals. The following data were extracted: PPI prescription at the time of CgA measurement, medical decision making based on elevated CgA concentrations, final diagnosis, comorbidity and other prescribed drugs., Results: From 238 patients with elevated CgA concentrations, 132 used PPIs. Of these patients, 57 patients did not have a NET. In 9 of these 57 patients (16%), diagnostic work up revealed no medical cause of an elevated CgA concentration. Somatostatin receptor imaging was ordered in 4 out of 9 cases, with no abnormalities observed. In 6 out of 9 cases, CgA measurement was repeated after PPI discontinuation resulting in normalisation of CgA concentrations., Conclusion: In this retrospective patient record study we observed that part of the elevated CgA concentrations in patients could be caused by the usage of PPIs causing unnecessary diagnostic work-up for the exclusion of a NET. These observations illustrate the need for better DLTI awareness., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Objectives: Computational algorithms for the interpretation of laboratory test results can support physicians and specialists in laboratory medicine. The aim of this study was to develop, implement and evaluate a machine learning algorithm that automatically assesses the risk of low body iron storage, reflected by low ferritin plasma levels, in anemic primary care patients using a minimal set of basic laboratory tests, namely complete blood count and C-reactive protein (CRP)., Methods: Laboratory measurements of anemic primary care patients were used to develop and validate a machine learning algorithm. The performance of the algorithm was compared to twelve specialists in laboratory medicine from three large teaching hospitals, who predicted if patients with anemia have low ferritin levels based on laboratory test reports (complete blood count and CRP). In a second round of assessments the algorithm outcome was provided to the specialists in laboratory medicine as a decision support tool., Results: Two separate algorithms to predict low ferritin concentrations were developed based on two different chemistry analyzers, with an area under the curve of the ROC of 0.92 (Siemens) and 0.90 (Roche). The specialists in laboratory medicine were less accurate in predicting low ferritin concentrations compared to the algorithms, even when knowing the output of the algorithms as support tool. Implementation of the algorithm in the laboratory system resulted in one new iron deficiency diagnosis on average per day., Conclusions: Low ferritin levels in anemic patients can be accurately predicted using a machine learning algorithm based on routine laboratory test results. Moreover, implementation of the algorithm in the laboratory system reduces the number of otherwise unrecognized iron deficiencies., (© 2022 Walter de Gruyter GmbH, Berlin/Boston.)

Background: In primary care, D-dimer-combined with a clinical assessment-is recommended for ruling-out venous thromboembolism (VTE). However, D-dimer testing frequently yields false-positive results, notably in the elderly, and the search for novel biomarkers thus continues. We assessed the added diagnostic value of 4 promising laboratory tests., Methods: Plasma samples from 256 primary care patients suspected of VTE were collected. We explored added value (beyond D-dimer) of C-reactive protein (CRP), procalcitonin (PCT), thrombin-antithrombin III complex (TAT-c), and factor VIII (FVIII). Diagnostic performance of these biomarkers was assessed univariably and by estimating their area under the receiver operating curve (AUC). Added diagnostic potential beyond D-dimer testing was assessed using multivariable logistic regression., Results: Plasma samples of 237 VTE-suspected patients were available for analysis-36 patients (25%) confirmed deep vein thrombosis, 11 patients (12%) pulmonary embolism. Apart from D-dimer, only CRP, and FVIII levels appeared to be higher in patients with VTE compared to patients without VTE. The AUCs for these 3 markers were 0.76 (95% CI: 0.69-0.84) and 0.75 (95% CI: 0.68-0.83), respectively, whereas the AUC for D-dimer was 0.90 (95% CI: 0.86-0.94). Combining these biomarkers in a multivariable logistic model with D-dimer did not improve these AUCs meaningfully., Conclusions: In our dataset, we were unable to demonstrate any added diagnostic performance beyond D-dimer testing of novel biomarkers in patients suspected of VTE in primary care. As such, D-dimer testing appears to remain the best choice in the exclusion of clinically suspected VTE in this setting., Trial Registration: Netherlands Trial Register NL5974. (METC protocol number: 16-356/M; NL56475.041.16.)., (© American Association for Clinical Chemistry 2021.)

Objectives: For the correct interpretation of test results, it is important to be aware of drug-laboratory test interactions (DLTIs). If DLTIs are not taken into account by clinicians, erroneous interpretation of test results may lead to a delayed or incorrect diagnosis, unnecessary diagnostic testing or therapy with possible harm for patients. A DLTI alert accompanying a laboratory test result could be a solution. The aim of this study was to test a multicentre proof of concept of an electronic clinical decision support system (CDSS) for real-time monitoring of DLTIs., Methods: CDSS was implemented in three Dutch hospitals. So-called 'clinical rules' were programmed to alert medical specialists for possible DLTIs based on laboratory test results outside the reference range in combination with prescribed drugs. A selection of interactions from the DLTI database of the Dutch society of clinical chemistry and laboratory medicine were integrated in 43 clinical rules, including 24 tests and 25 drugs. During the period of one month all generated DTLI alerts were registered in the laboratory information system., Results: Approximately 65 DLTI alerts per day were detected in each hospital. Most DLTI alerts were generated in patients from the internal medicine and intensive care departments. The most frequently reported DLTI alerts were potassium-proton pump inhibitors (16%), potassium-beta blockers (11%) and creatine kinase-statins (11%)., Conclusions: This study shows that it is possible to alert for potential DLTIs in real-time with a CDSS. The CDSS was successfully implemented in three hospitals. Further research must reveal its usefulness in clinical practice., (© 2021 Walter de Gruyter GmbH, Berlin/Boston.)

Background: Hypercholesterolemia (plasma cholesterol concentration ≥5.2 mmol/L) is a risk factor for cardiovascular disease and stroke. Many different cholesterol self-tests are readily available at general stores, pharmacies and web shops. However, there is limited information on their analytical and diagnostic performance., Methods: We included 62 adult patients who required a lipid panel measurement (cholesterol, high-density lipoprotein (HDL), triglycerides and LDL calc ) for routine care. The performance of five different cholesterol self-tests, three quantitative meters ( Roche Accutrend Plus , Mission 3-in-1 and Qucare ) and two semi-quantitative strip tests ( Veroval and Mylan MyTest ), was assessed according to the manufacturers' protocol., Results: The average plasma cholesterol concentration was 5.2 ± 1.2 mmol/L. The mean absolute relative difference (MARD) of the five cholesterol self-tests ranged from 6 ± 5% ( Accutrend Plus ) to 20 ± 12% ( Mylan Mytest ). The Accutrend Plus cholesterol meter showed the best diagnostic performance with a 92% sensitivity and 89% specificity. The Qucare and Mission 3-in-1 are able to measure HDL concentrations and can thus provide a cholesterol:HDL ratio. The Passing-Bablok regression analyses for the ratio showed poor performance in both self-tests ( Mission 3-in-1 : y = 1.62x-1.20; Qucare : y = 0.61x + 1.75). The Accutrend Plus is unable to measure the plasma high-density lipoprotein concentration.Conclusions/interpretation: The Accutrend Plus cholesterol meter (Roche) had excellent diagnostic and analytic performance. However, several of the commercially-available self-tests had considerably poor accuracy and diagnostic performance and therefore do not meet the required qualifications, potentially leading to erroneous results. Better regulation, standardization and harmonization of cholesterol self-tests is warranted.

Objectives: Knowledge of possible drug-laboratory test interactions (DLTIs) is important for the interpretation of laboratory test results. Failure to recognize these interactions may lead to misinterpretation, a delayed or erroneous diagnosis, or unnecessary extra diagnostic tests or therapy, which may harm patients. The aim of this multicentre survey was to evaluate the clinical value of DLTI alerts., Methods: A survey was designed with six predefined clinical cases selected from the clinical laboratory practice with a potential DLTI. Physicians from several departments, including internal medicine, cardiology, intensive care, surgery and geriatrics in six participating hospitals were recruited to fill in the survey. The survey addressed their knowledge of DLTIs, motivation to receive an alert and opinion on the potential influence on medical decision making., Results: A total of 210 physicians completed the survey. Of these respondents 93% had a positive attitude towards receiving DLTI alerts; however, the reported value differed per case and per respondent's background. In each clinical case, medical decision making was influenced as a consequence of the reported DLTI message (ranging from 3 to 45% of respondents per case)., Conclusions: In this multicentre survey, most physicians stated DLTI messages to be useful in laboratory test interpretation. Medical decision making was influenced by reporting DLTI alerts in each case. Alerts should be adjusted according to the needs and preferences of the receiving physicians., (© 2021 Walter de Gruyter GmbH, Berlin/Boston.)

The use of artificial intelligence (AI) in a variety of research fields is speeding up multiple digital revolutions, from shifting paradigms in healthcare, precision medicine and wearable sensing, to public services and education offered to the masses around the world, to future cities made optimally efficient by autonomous driving. When a revolution happens, the consequences are not obvious straight away, and to date, there is no uniformly adapted framework to guide AI research to ensure a sustainable societal transition. To answer this need, here we analyze three key challenges to interdisciplinary AI research, and deliver three broad conclusions: 1) future development of AI should not only impact other scientific domains but should also take inspiration and benefit from other fields of science, 2) AI research must be accompanied by decision explainability, dataset bias transparency as well as development of evaluation methodologies and creation of regulatory agencies to ensure responsibility, and 3) AI education should receive more attention, efforts and innovation from the educational and scientific communities. Our analysis is of interest not only to AI practitioners but also to other researchers and the general public as it offers ways to guide the emerging collaborations and interactions toward the most fruitful outcomes., Competing Interests: Authors LT and DQ are employed by the company Nokia Bell Labs. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Kusters, Misevic, Berry, Cully, Cunff, Dandoy, Díaz-Rodríguez, Ficher, Grizou, Othmani, Palpanas, Komorowski, Loiseau, Frier, Nanini, Quercia, Sebag, Fogelman, Taleb, Tupikina, Sahu, Vie and Wehbi.)

Heterodimeric capping protein (CP) binds the rapidly growing barbed ends of actin filaments and prevents the addition (or loss) of subunits. Capping activity is generally considered to be essential for actin-based motility induced by Arp2/3 complex nucleation. By stopping barbed end growth, CP favors nucleation of daughter filaments at the functionalized surface where the Arp2/3 complex is activated, thus creating polarized network growth, which is necessary for movement. However, here using an in vitro assay where Arp2/3 complex-based actin polymerization is induced on bead surfaces in the absence of CP, we produce robust polarized actin growth and motility. This is achieved either by adding the actin polymerase Ena/VASP or by boosting Arp2/3 complex activity at the surface. Another actin polymerase, the formin FMNL2, cannot substitute for CP, showing that polymerase activity alone is not enough to override the need for CP. Interfering with the polymerase activity of Ena/VASP, its surface recruitment or its bundling activity all reduce Ena/VASP's ability to maintain polarized network growth in the absence of CP. Taken together, our findings show that CP is dispensable for polarized actin growth and motility in situations where surface-directed polymerization is favored by whatever means over the growth of barbed ends in the network., Competing Interests: Conflict of interest—The authors declare that they have no conflicts of interest with the contents of this article., (© 2020 Abou-Ghali et al.)

D-dimer testing combined with a clinical assessment has become a standard pathway for ruling-out venous thromboembolism (VTE). Recently, novel Point-of-Care (POC) D-dimer assays have been introduced, enabling low-volume blood sampling for rapid exclusion of VTE in a one-step procedure. We assessed the analytical validity and user-friendliness of a set of these novel POC D-dimer assays, and compared the results with a standard laboratory assay. Plasma samples were run on our reference assay (STA-Liatest D-di PLUS ® ) and five POC assays: Nano-Checker 710 ® , AFIAS-1 ® ; iChroma-II ® ; Standard F200 ® and Hipro AFS/1 ® ). After evaluating imprecision, Pearson Product-Moment correlation coefficients were calculated, Passing Bablok regression was performed and Bland-Altman plots were generated. User-friendliness was evaluated using the System Usability Scale (SUS). A set of 238 plasma samples of patients clinically suspected of VTE in general practice was available for analysis. Only one POC D-dimer assay (Nano-Checker 710) demonstrated an insufficient degree of imprecision. Pearson correlation coefficients and mean biases ranged from 0.68 to 0.93 and -165 to -53 μg/L respectively, and concordance with our reference assay varied from 71.8% to 89.5% using a 500 μg/L cut-off point. While we found considerable variation in overall user-friendliness, most devices were judged easy to use. In view of our findings regarding analytical performance and user-friendliness, we consider most of the novel POC D-dimer assays can be used in settings outside of the laboratory such as general practice, combining the possibility of multi-testing with low-volume capillary blood sampling and processing times of less than 15 min.

Background: More information is often thought to improve medical decision-making, which may lead to test overuse. This study assesses which out of 15 laboratory tests contribute to diagnosing the underlying cause of anaemia by general practitioners (GPs) and determines a potentially more efficient subset of tests for setting the correct diagnosis., Methods: Logistic regression was performed to determine the impact of individual tests on the (correct) diagnosis. The statistically optimal test subset for diagnosing a (correct) underlying cause of anaemia by GPs was determined using data from a previous survey including cases of real-world anaemia patients., Results: Only 9 (60%) of the laboratory tests, and patient age, contributed significantly to the GPs' ability to diagnose an underlying cause of anaemia (CRP, ESR, ferritin, folic acid, haemoglobin, leukocytes, eGFR/MDRD, reticulocytes and serum iron). Diagnosing the correct underlying cause may require just five (33%) tests (CRP, ferritin, folic acid, MCV and transferrin), and patient age., Conclusions: In diagnosing the underlying cause of anaemia a subset of five tests has most added value. The real-world impact of using only this subset should be further investigated. As illustrated in this case study, a statistical approach to assessing the added value of tests may reduce test overuse.

Objectives: The novel coronavirus disease 19 (COVID-19), caused by SARS-CoV-2, spreads rapidly across the world. The exponential increase in the number of cases has resulted in overcrowding of emergency departments (ED). Detection of SARS-CoV-2 is based on an RT-PCR of nasopharyngeal swab material. However, RT-PCR testing is time-consuming and many hospitals deal with a shortage of testing materials. Therefore, we aimed to develop an algorithm to rapidly evaluate an individual's risk of SARS-CoV-2 infection at the ED., Methods: In this multicenter retrospective study, routine laboratory parameters (C-reactive protein, lactate dehydrogenase, ferritin, absolute neutrophil and lymphocyte counts), demographic data and the chest X-ray/CT result from 967 patients entering the ED with respiratory symptoms were collected. Using these parameters, an easy-to-use point-based algorithm, called the corona-score, was developed to discriminate between patients that tested positive for SARS-CoV-2 by RT-PCR and those testing negative. Computational sampling was used to optimize the corona-score. Validation of the model was performed using data from 592 patients., Results: The corona-score model yielded an area under the receiver operating characteristic curve of 0.91 in the validation population. Patients testing negative for SARS-CoV-2 showed a median corona-score of 3 vs. 11 (scale 0-14) in patients testing positive for SARS-CoV-2 (p<0.001). Using cut-off values of 4 and 11 the model has a sensitivity and specificity of 96 and 95%, respectively., Conclusions: The corona-score effectively predicts SARS-CoV-2 RT-PCR outcome based on routine parameters. This algorithm provides the means for medical professionals to rapidly evaluate SARS-CoV-2 infection status of patients presenting at the ED with respiratory symptoms.

Global changes of cell shape under mechanical or osmotic external stresses are mostly controlled by the mechanics of the cortical actin cytoskeleton underlying the cell membrane. Some aspects of this process can be recapitulated in vitro on reconstituted actin-and-membrane systems. In this paper, we investigate how the mechanical properties of a branched actin network shell, polymerized at the surface of a liposome, control membrane shape when the volume is reduced. We observe a variety of membrane shapes depending on the actin thickness. Thin shells undergo buckling, characterized by a cup-shape deformation of the membrane that coincides with the one of the actin network. Thick shells produce membrane wrinkles, but do not deform their outer layer. For intermediate micrometer-thick shells, wrinkling of the membrane is observed, and the actin layer is slightly deformed. Confronting our experimental results with a theoretical description, we determine the transition between buckling and wrinkling, which depends on the thickness of the actin shell and the size of the liposome. We thus unveil the generic mechanism by which biomembranes are able to accommodate their shape against mechanical compression, through thickness adaptation of their cortical cytoskeleton.

The regulation of actin dynamics is essential for various cellular processes. Former evidence suggests a correlation between the function of non-conventional myosin motors and actin dynamics. Here we investigate the contribution of myosin 1b to actin dynamics using sliding motility assays. We observe that sliding on myosin 1b immobilized or bound to a fluid bilayer enhances actin depolymerization at the barbed end, while sliding on myosin II, although 5 times faster, has no effect. This work reveals a non-conventional myosin motor as another type of depolymerase and points to its singular interactions with the actin barbed end.

Objectives: There are numerous point-of-care tests (POCTs) available on the market, but many of these are not used. This study reviewed literature pertaining to the evaluation/usage of POCTs in primary care, to investigate whether outcomes being reported reflect aspects previously demonstrated to be important for general practitioners (GPs) in the decision to implement a POCT in practice., Methods: Scopus and Medline were searched to identify studies that evaluated a POCT in primary care. We identified abstracts and full-texts consisting of applied studies (eg trials, simulations, observational studies) and qualitative studies (eg interviews, surveys). Data were extracted from the included studies, such as the type of study, the extent to which manufacturers were involved in the study, and the biomarker/assay measured by the test(s). Studies were evaluated to summarise the extent to which they reported on, amongst others, clinical utility, user-friendliness, turnaround-time and technical performance (aspects previously identified as important)., Results: The initial search resulted in 1398 publications, of which 125 met the inclusion criteria. From these studies, 83 POCTs across several disease areas (including cardiovascular disease, venous thromboembolism and respiratory-tract-infections) were identified. There was an inconsistency between what is reported in the studies and what GPs consider important. GPs perceive clinical utility as the most important aspect, yet this was rarely included explicitly in test evaluations in the literature, with only 8% of evaluations incorporating it in their analysis/discussion., Conclusions: This review showed that, despite the growing market and development of new POCTs, studies evaluating such tests fail to report on aspects that GPs find important. To ensure that an evaluation of a POCT is useful to primary care clinicians, future evaluations should not only focus on the technical performance aspects of a test, but also report on the aspects relating to the clinical utility and risks., (© 2019 The Authors. International Journal of Clinical Practice published by John Wiley & Sons Ltd.)

An influenza epidemic can greatly increase the workload in primary care and the emergency department (ED) and can even disrupt the healthcare system. It is difficult to diagnose influenza by history taking and physical examination. A fast diagnosis usinginfluenza point-of-care tests (POCTs) could reduce unnecessary antibiotic prescriptions, diagnostic tests, consultations and hospital admissions. Moreover, length of stay on EDs and length of admission could be shortened. The analytical accuracy of antigen detection tests for influenza is relatively low compared to the well performing RT-PCR assays (sensitivity and specificity approximately 95%). Only 1 randomized controlled trial has shown the effect of a (combined) RT-PCR assay for influenza detection on clinically relevant outcome measures. Observational research suggests that introduction of RT-PCR assays for influenza detection reduces length of stay on the ED and decreased time from sample reception to result. For practical reasons, we should embrace the introduction of RT-PCR assays for influenza detection on EDs. Before POCTs can be implemented in primary care (family medicine) the analytical accuracy and time to receive results should be improved and effects of its clinical impact should be proven.

Background Knowledge of possible drug-laboratory test interactions (DLTIs) is important for the interpretation of laboratory test results. Test results may be affected by physiological or analytical drug effects. Failure to recognize these interactions may lead to misinterpretation of test results, a delayed or erroneous diagnosis or unnecessary extra tests or therapy, which may harm patients. Content Thousands of interactions have been reported in the literature, but are often fragmentarily described and some papers even reported contradictory findings. How can healthcare professionals become aware of all these possible interactions in their individual patients? DLTI decision support applications could be a good solution. In a literature search, only four relevant studies have been found on DLTI decision support applications in clinical practice. These studies show a potential benefit of automated DLTI messages to physicians for the interpretation of laboratory test results. All physicians reported that part of the DLTI messages were useful. In one study, 74% of physicians even sometimes refrained from further additional examination. Summary and outlook Unrecognized DLTIs potentially cause diagnostic errors in a large number of patients. Therefore, efforts to avoid these errors, for example with a DLTI decision support application, could tremendously improve patient outcome.

Background: Venipuncture for the purpose of blood analysis is often performed at remote locations, and samples may be centrifuged locally to preserve the integrity of analytes. At the central laboratory, these tubes may be centrifuged again in the routine process. However, limited research shows that >1 centrifugation cycle of gel separator tubes causes significant changes in analytes, in particular troponin I and potassium. These preanalytical test changes are undesirable and may lead to errors in diagnosis and treatment of patients., Methods: Ten volunteers donated blood in 10 lithium heparin gel tubes. Per volunteer, 5 tubes were centrifuged with Becton Dickinson centrifugation settings and 5 tubes with our local centrifugation settings. For each centrifugation setting, 1 tube was centrifuged directly after venipuncture; the second tube, directly after venipuncture and again after 4 h; the third tube, directly after venipuncture and again after 8 h; the fourth tube, 4 h after venipuncture; the last tube, 8 h after venipuncture. Thirty routine chemistry analyses were performed in plasma directly after the last centrifugation cycle. All tubes were kept at room temperature. Analytes were considered unstable when the mean percentage deviation exceeded the total allowable error., Results: Except for calcium, which slightly exceeded the predefined total allowable error limit, all the investigated analytes remained stable up to 8 h after a second centrifugation cycle with both centrifugation settings., Conclusion: This study shows that recentrifugation up to 8 h after blood collection does not cause relevant deviations in test results and may be applied safely., (© 2018 American Association for Clinical Chemistry.)

Background: The increasing number of available point-of-care (POC) tests challenges clinicians regarding decisions on which tests to use, how to efficiently use them, and how to interpret the results. Although POC tests may offer benefits in terms of low turn-around-time, improved patient's satisfaction, and health outcomes, only few are actually used in clinical practice. Therefore, this study aims to identify which criteria are, in general, important in the decision to implement a POC test, and to determine their weight. Two POC tests available for use in Dutch general practices (i.e. the C-reactive protein (CRP) test and the glycated haemoglobin (HbA 1c ) test) serve as case studies. The information obtained from this study can be used to guide POC test development and their introduction in clinical practice., Methods: Relevant criteria were identified based on a literature review and semi-structured interviews with twelve experts in the field. Subsequently, the criteria were clustered in four groups (i.e. user, organization, clinical value, and socio-political context) and the relative importance of each criterion was determined by calculating geometric means as implemented in the Analytic Hierarchy Process. Of these twelve experts, ten participated in a facilitated group session, in which their priorities regarding both POC tests (compared to central laboratory testing) were elicited., Results: Of 20 criteria in four clusters, the test's clinical utility, its technical performance, and risks (associated with the treatment decision based on the test result) were considered most important for using a POC test, with relative weights of 22.2, 12.6 and 8.5%, respectively. Overall, the experts preferred the POC CRP test over its laboratory equivalent, whereas they did not prefer the POC HbA 1c test. This difference was mainly explained by their strong preference for the POC CRP test with regard to the subcriterion 'clinical utility'., Conclusions: The list of identified criteria, and the insights in their relative impact on successful implementation of POC tests, may facilitate implementation and use of existing POC tests in clinical practice. In addition, having experts score new POC tests on these criteria, provides developers with specific recommendations on how to increase the probability of successful implementation and use.

Background: Modern health care focuses on shared decision making (SDM) because of its positive effects on patient satisfaction, therapy compliance, and outcomes. Patients' knowledge about their illness and available treatment options, gained through medical education, is one of the key drivers for SDM. Current patient education relies heavily on medical consultation and is known to be ineffective., Objective: This study aimed to determine whether providing patients with information in a subdivided, categorized, and interactive manner via an educational app for smartphone or tablet might increase the knowledge of their illness., Methods: A surgeon-blinded randomized controlled trial was conducted with 213 patients who were referred to 1 of the 6 Dutch hospitals by their general practitioner owing to knee complaints that were indicative of knee osteoarthritis. An interactive app that, in addition to standard care, actively sends informative and pertinent content to patients about their illness on a daily basis by means of push notifications in the week before their consultation. The primary outcome was the level of perceived and actual knowledge that patients had about their knee complaints and the relevant treatment options after the intervention., Results: In total, 122 patients were enrolled in the control group and 91 in the intervention group. After the intervention, the level of actual knowledge (measured on a 0-36 scale) was 52% higher in the app group (26.4 vs 17.4, P<.001). Moreover, within the app group, the level of perceived knowledge (measured on a 0-25 scale) increased by 22% during the week within the app group (from 13.5 to 16.5, P<.001), compared with no gain in the control group., Conclusions: Actively offering patients information in a subdivided (per day), categorized (per theme), and interactive (video and quiz questions) manner significantly increases the level of perceived knowledge and demonstrates a higher level of actual knowledge, compared with standard care educational practices., Trial Registration: International Standard Randomized Controlled Trial Number ISRCTN98629372; http://www.isrctn.com/ISRCTN98629372 (Archived by WebCite at http://www.webcitation.org/73F5trZbb)., (©Thomas Timmers, Loes Janssen, Yvette Pronk, Babette C van der Zwaard, Sander Koëter, Dirk van Oostveen, Stefan de Boer, Keetie Kremers, Sebastiaan Rutten, Dirk Das, Rutger CI van Geenen, Koen LM Koenraadt, Rob Kusters, Walter van der Weegen. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 21.12.2018.)

Intake of drugs may influence the interpretation of laboratory test results. Knowledge and correct interpretation of possible drug-laboratory test interactions (DLTIs) is important for physicians, pharmacists and laboratory specialists. Laboratory results may be affected by analytical or physiological effects of medication. Failure to take into account the possible unintended influence of drug use on a laboratory test result may lead to incorrect diagnosis, incorrect treatment and unnecessary follow-up. The aim of this review is to give an overview of the literature investigating the clinical impact and use of DLTI decision support systems on laboratory test interpretation. Particular interactions were reported in a large number of articles, but they were fragmentarily described and some papers even reported contradictory findings. To provide an overview of information that clinicians and laboratory staff need to interpret test results, DLTI databases have been made by several groups. In a literature search, only four relevant studies have been found on DLTI decision support applications for laboratory test interpretation in clinical practice. These studies show a potential benefit of automated DLTI messages to physicians for the correct interpretation of laboratory test results. Physicians reported 30-100% usefulness of DLTI messages. In one study 74% of physicians sometimes even refrained from further additional examination. The benefit of decision support increases when a refined set of clinical rules is determined in cooperation with health care professionals. The prevalence of DLTIs is high in a broad range of combinations of laboratory tests and drugs and these frequently remain unrecognized.

Background: Procalcitonin (PCT) testing can help in safely reducing antibiotic treatment duration in intensive care patients with sepsis. However, the cost-effectiveness of such PCT guidance is not yet known., Methods: A trial-based analysis was performed to estimate the cost-effectiveness of PCT guidance compared with standard of care (without PCT guidance). Patient-level data were used from the SAPS trial in which 1546 patients were randomised. This trial was performed in the Netherlands, which is a country with, on average, low antibiotic use and a short duration of hospital stay. As quality of life among sepsis survivors was not measured during the SAPS, this was derived from a Dutch follow-up study. Outcome measures were (1) incremental direct hospital cost and (2) incremental cost per quality-adjusted life year (QALY) gained from a healthcare perspective over a one-year time horizon. Uncertainty in outcomes was assessed with bootstrapping., Results: Mean in-hospital costs were €46,081/patient in the PCT group compared with €46,146/patient with standard of care (i.e. - €65 (95% CI - €6314 to €6107); - 0.1%). The duration of the first course of antibiotic treatment was lower in the PCT group with 6.9 vs. 8.2 days (i.e. - 1.2 days (95% CI - 1.9 to - 0.4), - 14.8%). This was accompanied by lower in-hospital mortality of 21.8% vs. 29.8% (absolute decrease 7.9% (95% CI - 13.9% to - 1.8%), relative decrease 26.6%), resulting in an increase in mean QALYs/patient from 0.47 to 0.52 (i.e. + 0.05 (95% CI 0.00 to 0.10); + 10.1%). However, owing to high costs among sepsis survivors, healthcare costs over a one-year time horizon were €73,665/patient in the PCT group compared with €70,961/patient with standard of care (i.e. + €2704 (95% CI - €4495 to €10,005), + 3.8%), resulting in an incremental cost-effectiveness ratio of €57,402/QALY gained. Within this time frame, the probability of PCT guidance being cost-effective was 64% at a willingness-to-pay threshold of €80,000/QALY., Conclusions: Although the impact of PCT guidance on total healthcare-related costs during the initial hospitalisation episode is likely negligible, the lower in-hospital mortality may lead to a non-significant increase in costs over a one-year time horizon. However, since uncertainty remains, it is recommended to investigate the long-term cost-effectiveness of PCT guidance, from a societal perspective, in different countries and settings.

Background Establishing the underlying cause of anaemia in general practice is a diagnostic challenge. Currently, general practitioners individually determine which laboratory tests to request (routine work-up) in order to diagnose the underlying cause. However, an extensive work-up (consisting of 14 tests) increases the proportion of patients correctly diagnosed. This study investigates the cost-effectiveness of this extensive work-up. Methods A decision-analytic model was developed, incorporating all societal costs from the moment a patient presents to a general practitioner with symptoms suggestive of anaemia (aged ≥ 50 years), until the patient was (correctly) diagnosed and treated in primary care, or referred to (and diagnosed in) secondary care. Model inputs were derived from an online survey among general practitioners, expert estimates and published data. The primary outcome measure was expressed as incremental cost per additional patient diagnosed with the correct underlying cause of anaemia in either work-up. Results The probability of general practitioners diagnosing the correct underlying cause increased from 49.6% (95% CI: 44.8% to 54.5%) in the routine work-up to 56.0% (95% CI: 51.2% to 60.8%) in the extensive work-up (i.e. +6.4% [95% CI: -0.6% to 13.1%]). Costs are expected to increase slightly from €842/patient (95% CI: €704 to €994) to €845/patient (95% CI: €711 to €994), i.e. +€3/patient (95% CI: €-35 to €40) in the extensive work-up, indicating incremental costs of €43 per additional patient correctly diagnosed. Conclusions The extensive laboratory work-up is more effective for diagnosing the underlying cause of anaemia by general practitioners, at a minimal increase in costs. As accompanying benefits in terms of quality of life and reduced productivity losses could not be captured in this analysis, the extensive work-up is likely cost-effective.

Objectives: General frameworks for conducting and reporting health economic evaluations are available but not specific enough to cover the intricacies of the evaluation of diagnostic tests and biomarkers. Such evaluations are typically complex and model-based because tests primarily affect health outcomes indirectly and real-world data on health outcomes are often lacking. Moreover, not all aspects relevant to the evaluation of a diagnostic test may be known and explicitly considered for inclusion in the evaluation, leading to a loss of transparency and replicability. To address this challenge, this study aims to develop a comprehensive reporting checklist., Methods: This study consisted of 3 main steps: 1) the development of an initial checklist based on a scoping review, 2) review and critical appraisal of the initial checklist by 4 independent experts, and 3) development of a final checklist. Each item from the checklist is illustrated using an example from previous research., Results: The scoping review followed by critical review by the 4 experts resulted in a checklist containing 44 items, which ideally should be considered for inclusion in a model-based health economic evaluation. The extent to which these items were included or discussed in the studies identified in the scoping review varied substantially, with 14 items not being mentioned in ≥47 (75%) of the included studies., Conclusions: The reporting checklist developed in this study may contribute to improved transparency and completeness of model-based health economic evaluations of diagnostic tests and biomarkers. Use of this checklist is therefore encouraged to enhance the interpretation, comparability, and-indirectly-the validity of the results of such evaluations.