Clinical decision rules in primary care: necessary investments for sustainable healthcare.

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.

The societal impact of implementing an at-home blood sampling device for chronic care patients: patient preferences and cost impact.

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.

Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis.

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.

Added Diagnostic Value of Biomarkers in Patients with Suspected Sepsis: A Prospective Cohort Study in Out-Of-Hours Primary Care.

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.

New clinical prediction model for early recognition of sepsis in adult primary care patients: a prospective diagnostic cohort study of development and external validation.

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.

Awareness of drug laboratory test interactions is important for prevention of unnecessary additional diagnostics: An example.

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.

Automated prediction of low ferritin concentrations using a machine learning algorithm.

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.

Performance of C-Reactive Protein, Procalcitonin, TAT Complex, and Factor VIII in Addition to D-Dimer in the Exclusion of Venous Thromboembolism in Primary Care Patients.

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.).

Real-time monitoring of drug laboratory test interactions: a proof of concept.

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.

How to Realize the Benefits of Point-of-Care Testing at the General Practice: A Comparison of Four High-Income Countries.

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.

Clinical usefulness of drug-laboratory test interaction alerts: a multicentre survey.

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.

Performance of commercially-available cholesterol self-tests.

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 LDLcalc) 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.

Health Economic Evidence of Point-of-Care Testing: A Systematic Review.

OBJECTIVE: Point-of-care testing (POCT) has become an essential diagnostic technology for optimal patient care. Its implementation, however, still falls behind. This paper reviews the available evidence on the health economic impact of introducing POCT to assess if poor POCT uptake may be related to lacking evidence. STUDY DESIGN: The Scopus and PubMed databases were searched to identify publications describing a health economic evaluation of a point-of-care (POC) test. Data were extracted from the included publications, including general and methodological characteristics as well as the study results summarized in either cost, effects or an incremental cost-effectiveness ratio. Results were sorted into six groups according to the POC test's purpose (diagnosis, screening or monitoring) and care setting (primary care or secondary care). The reporting quality of the publications was determined using the CHEERS checklist. RESULTS: The initial search resulted in 396 publications, of which 44 met the inclusion criteria. Most of the evaluations were performed in a primary care setting (n = 31; 70.5%) compared with a secondary care setting (n = 13; 29.5%). About two thirds of the evaluations were on POC tests implemented with a diagnostic purpose (n = 28; 63.6%). More than 75% of evaluations concluded that POCT is recommended for implementation, although in some cases only under specific circumstances and conditions. Compliance with the CHEERS checklist items ranged from 20.8% to 100%, with an average reporting quality of 72.0%. CONCLUSION: There were very few evaluations in this review that advised against the implementation of POCT. However, the uptake of POCT in many countries remains low. Even though the evaluations included in this review did not always include the full long-term benefits of POCT, it is clear that health economic evidence across a few dimensions of value already indicate the benefits of POCT. This suggests that the lack of evidence on POCT is not the primary barrier to its implementation and that the low uptake of these tests in clinical practice is due to (a combination of) other barriers. In this context, aspects around organization of care, support of clinicians and quality management may be crucial in the widespread implementation of POCT.

Preventing overuse of laboratory diagnostics: a case study into diagnosing anaemia in Dutch general practice.

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.

Rapid identification of SARS-CoV-2-infected patients at the emergency department using routine testing.

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.

Analytical performance and user-friendliness of five novel point-of-care D-dimer assays.

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.

Recentrifugation of Lithium Heparin Gel Separator Tubes up to 8 h after Blood Collection Has No Relevant Influence on the Stability of 30 Routine Biochemical Analytes.

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.

[Influenza point-of-care test in the GP practice and Emergency Department; analytical accuracy and added value]. / Influenzasneltests voor de huisartsenpraktijk en SEH.

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.