Clinical Decision-Making Suffers from Inequivalent Measurement Results and Inadequate Reference Intervals.

BACKGROUND: Appropriate clinical decision-making relies on the interpretation of equivalent measurement results in the context of valid clinical decision limits. Besides guideline-based decision limits, reference intervals (RIs) are commonly used to discriminate between abnormal results and results from "healthy" individuals. This study evaluated the suitability of RIs in light of the analytical bias for laboratories in the Netherlands using one standardized, one harmonized, and one unharmonized measurand (creatinine, hemoglobin, and ferritin, respectively). METHODS: Three types of data were collected: (a) external quality assessment (EQA) performance data from the Dutch Foundation for Quality Assurance in Laboratory Medicine (SKML); (b) the RIs reported by laboratories for a 55-year-old female; and (c) harmonized RIs established by using unique routine patient results using RefineR. Routinely used RIs (b) were compared to the harmonized RIs (c) and evaluated in combination with the analytical bias at the lower and upper reference limits. RESULTS: Laboratories reported a variety of routinely used RIs that were inconsistent with the analytical bias, with differences between measurement procedures. The use of assays that perform within allowable bias limits does not automatically guarantee that the appropriate RI is used, allowing potential for structural misinterpretation of important diagnoses in patients. CONCLUSIONS: The use of RIs that are inconsistent with the analytical bias causes unnecessary between-laboratory differences in clinical decision-making. Adopting harmonized RIs facilitates similar interpretation of results across facilities. Harmonized RIs can be adopted immediately if the observed bias is acceptable or eliminated, or after standardization/harmonization of measurands without complete metrological traceability.

Modelling the impact of bias in fecal immunochemical testing on long-term outcomes of colorectal cancer screening.

BACKGROUND: As the impact of unmanaged bias (i.e. systematic source of inaccuracy) in fecal immunochemical test (FIT) analytical performance on long-term colorectal cancer (CRC) outcomes is unknown, we assessed the impact bias in FIT performance in an ongoing FIT-based CRC screening program. METHODS: This study consisted of two parts: cross-sectional observational data analysis to estimate change in short-term outcomes and microsimulation modelling to estimate change in long-term outcomes assuming different levels of bias by assuming 15 % lower up to 15 % higher Hemoglobin detected in the stool compared to observed. Two scenarios were considered: bias occurring 1) one-time only, due to the occasional bias associated with the FIT kits used in 2020 and 2) consistently due to a constant bias associated with the FIT kits used from 2020 onwards. RESULTS: With a hypothetical bias of -15 % to +15 %, we observed a positivity rate ranging from 6.7 % to 7.8 %, and a detection rate for CRC between 0.65 % and 0.68 %. Single biases in FIT performance resulted in less than 0.1 % change in long-term CRC screening outcomes, while consistent biases resulted in a much larger change (up to 1.4 % in CRC cases and CRC-related deaths and up to 2.07 % in total costs). Detecting lower Hemoglobin concentrations resulted in a relatively larger change on long-term CRC outcomes in comparison to positive bias. CONCLUSIONS: Because of the substantial impact of consistent FIT bias, it is important to set evidence-based acceptance criteria of bias on long-term CRC screening outcomes and in particular, the introduction of an asymmetrical or upward shifted tolerance interval for FIT bias.

Quality control in the Netherlands; todays practices and starting points for guidance and future research.

OBJECTIVES: Adequate analytical quality of reported results is primarily ensured by performing internal quality control (iQC). Currently, several different iQC practices are in use. As a prelude to the revision of a Dutch guidance document on analytical QC, a questionnaire was sent out to gain insights in the applied practices and the need for guidance. METHODS: A questionnaire, containing 20 multiple-choice questions with possibilities for explanation and comment on iQC practices and aspects was distributed to all clinical chemistry laboratories within the Netherlands. Results were reported descriptively. RESULTS: Responses were received from 27 clinical laboratories (response 43 %). In 30 % the iQC was based on the analytical characteristics only, while 30 % used a 6-Sigma method, 19 % risk-based beyond 6-Sigma and 22 % used an alternative approach. 89 % of laboratories used a virtual analyzer model for iQC setup within one or more laboratory sites. Practices for determining standard deviation (SD) values included determining SD for each new iQC material (35 %), using historical SD values for new materials (35 %), and incorporating clinical tolerances into the SD value (31 %). Furthermore, 44 % of laboratories used patient moving averages for one or more tests. Daily iQC management was based on either "traffic lights" indicating in or out of control status, and review of all QC charts, often using multiple software systems. CONCLUSIONS: A large heterogeneity of iQC practices in clinical laboratories was observed in the Netherlands. Several starting points for further research and/or guidance were identified, particularly in relation to the determination of SD values, the virtual analyzer model and methods to ensure analyzer equivalence.

When bias becomes part of imprecision: how to use analytical performance specifications to determine acceptability of lot-lot variation and other sources of possibly unacceptable bias.

ISO 15189 requires laboratories to estimate the uncertainty of their quantitative measurements and to maintain them within relevant performance specifications. Furthermore, it refers to ISO TS 20914 for instructions on how to estimate the uncertainty and what to take into consideration when communicating uncertainty of measurement with requesting clinicians. These instructions include the responsibility of laboratories to verify that bias is not larger than medically significant. If estimated to be larger than acceptable, such bias first needs to be eliminated or (temporarily) corrected for. In the latter case, the uncertainty of such correction becomes part of the estimation of the total measurement uncertainty. If small enough to be acceptable, bias becomes part of the long term within laboratory random variation. Sources of possible bias are (not limited to) changes in reagent or calibrator lot variation or calibration itself. In this paper we clarify how the rationale and mathematics from an EFLM WG ISO/A position paper on allowable between reagent lot variation can be applied to calculate whether bias can be accepted to become part of long-term imprecision. The central point of this rationale is to prevent the risk that requesting clinicians confuse changes in bias with changes in the steady state of their patients.

To rule-in, or not to falsely rule-out, that is the question: evaluation of hs-cTnT EQA performance in light of the ESC-2020 guideline.

OBJECTIVES: To accurately evaluate non-ST-elevated acute cardiac syndrome (NSTE-ACS), the quality of high-sensitive cardiac troponin (hs-cTn) assays is of vital importance. The 2020 revision of the NSTE-ACS guideline includes clinical decision-limits (CDL's) to both rule-in and rule-out NSTE-ACS for most commercially available platforms, providing both 0/1 h and 0/2 h delta limits. Our study evaluated whether laboratories are able to meet the analytical performance specifications for imprecision (APS) for hs-cTnT. METHODS: Results from external quality assurance (EQA) in commutable samples were used to evaluate the current and historic performance of analyzers. The performance of analyzers that either passed or failed to comply with 0/1 h-APS were used on a real-world dataset of first hs-cTnT-values to simulate 10.000 samples of t=0, t=1 and t=2 h values with multiple delta's for all relevant CDL's. We compared the simulated values to the input values to obtain the percentage of aberrant results simulated. RESULTS: The majority of analyzers complies with APS for rule-in in 2022 (0/1 h: 90.4 % and 0/2 h: 100 %), compliance for the 0/1 h rule-out is still far from optimal (0/1 h: 30.7 %, 0/2 h: 75.4 %), with improving compliance over the past years (rule-in p=<0.0001, rule-out p=0.011, χ2). Whilst 0/1 h-APS-passing analyzers have a minute risk to falsely rule-out patients whom should be ruled-in (0.0001 %), failing performance increases this risk to 2.1 % upon using 0/1 h CDL's. Here, adopting 0/2 h CDL's is favorable (0.01 %). CONCLUSIONS: Laboratories that fail to meet hs-cTnT 0/1 h-APS should improve their performance to the required and achievable level. Until performance is reached clinics should adopt the 0/2 h CDL's.

APS calculator: a data-driven tool for setting outcome-based analytical performance specifications for measurement uncertainty using specific clinical requirements and population data.

OBJECTIVES: According to ISO 15189:2022, analytical performance specifications (APS) should relate to intended clinical use and impact on patient care. Therefore, we aimed to develop a web application for laboratory professionals to calculate APS based on a simulation of the impact of measurement uncertainty (MU) on the outcome using the chosen decision limits, agreement thresholds, and data of the population of interest. METHODS: We developed the "APS Calculator" allowing users to upload and select data of concern, specify decision limits and agreement thresholds, and conduct simulations to determine APS for MU. The simulation involved categorizing original measurand concentrations, generating measured (simulated) results by introducing different degrees of MU, and recategorizing measured concentrations based on clinical decision limits and acceptable clinical misclassification rates. The agreements between original and simulated result categories were assessed, and values that met or exceeded user-specified agreement thresholds that set goals for the between-category agreement were considered acceptable. The application generates contour plots of agreement rates and corresponding MU values. We tested the application using National Health and Nutrition Examination Survey data, with decision limits from relevant guidelines. RESULTS: We determined APS for MU of six measurands (blood total hemoglobin, plasma fasting glucose, serum total and high-density lipoprotein cholesterol, triglycerides, and total folate) to demonstrate the potential of the application to generate APS. CONCLUSIONS: The developed data-driven web application offers a flexible tool for laboratory professionals to calculate APS for MU using their chosen decision limits and agreement thresholds, and the data of the population of interest.

Albumin determined by bromocresol green leads to erroneous results in routine evaluation of patients with chronic kidney disease.

OBJECTIVES: Measurement of plasma albumin is pivotal for clinical decision-making in patients with chronic kidney disease (CKD). Routinely used methods as bromocresol green (BCG) and bromocresol purple (BCP) can suffer from aselectivity, but the impact of aselectivity on the accuracy of plasma albumin results of CKD-patients is still unknown. Therefore, we evaluated the performance of BCG-, BCP- and JCTLM-endorsed immunological methods in patients with various stages of CKD. METHODS: We evaluated the performance of commonly used albumin methods in patients with CKD stages G1 through G5, the latter divided in two groups based on whether they received hemodialysis treatment. In total, 163 patient plasma samples were measured at 14 laboratories, on six different BCG and BCP-platforms, and four different immunological platforms. The results were compared with an ERM-DA-470k-corrected nephelometric assay. The implications on outcome is evaluated by the proportion of patient results <38 g/L for the diagnosis of protein energy wasting. RESULTS: Albumin results determined with BCP- and immunological methods showed the best agreement with the target value (92.7 and 86.2 %, respectively vs. 66.7 % for BCG, namely due to overestimation). The relative agreement of each method with the target value was platform-dependent, with larger variability in agreement between platforms noted for BCG and immunological methods (3.2-4.6 and 2.6-5.3 %) as opposed to BCP (0.7-1.5 %). The stage of CKD had similar effects on the variability in agreement for the three method-groups (0.6-1.8 % vs. 0.7-1.5 % vs. 0.4-1.6 %). The differences between methods cause discrepancies in clinical decision-making, as structurally fewer patients were diagnosed with protein energy wasting upon using BCG-based albumin results. CONCLUSIONS: Our study shows that BCP is fit for the intended use to measure plasma albumin levels in CKD patients from all stages, including patients on hemodialysis. In contrast, most BCG-based platforms falsely overestimate the plasma albumin concentration.

An approach for determining allowable between reagent lot variation.

Clinicians trust medical laboratories to provide reliable results on which they rely for clinical decisions. Laboratories fulfil their responsibility for accurate and consistent results by utilizing an arsenal of approaches, ranging from validation and verification experiments to daily quality control procedures. All these procedures verify, on different moments, that the results of a certain examination procedure have analytical performance characteristics (APC) that meet analytical performance specifications (APS) set for a particular intended use. The APC can in part be determined by estimating the measurement uncertainty component under conditions of within-laboratory precision (uRw), which comprises all components influencing the measurement uncertainty of random sources. To maintain the adequacy of their measurement procedures, laboratories need to distinguish aspects that are manageable vs. those that are not. One of the aspects that may influence uRw is the momentary significant bias caused by shifts in reagent and/or calibrator lots, which, when accepted or unnoticed, become a factor of the APC. In this paper, we postulate a model for allocating a part of allowable uRw to between-reagent lot variation, based on the need for long-term consistency of the measurement variability for that specific measurand. The allocation manages the ratio between short-term and long-term variation and indicates laboratories when to reject or correct certain variations due to reagent lots.

Serum albumin measurement in nephrology: room for improvement.

Serum albumin is a widely used biomarker in clinical nephrology. Serum albumin cut-off values are used to define disease, to predict outcome and to guide patient care. The available commercial assays to measure serum albumin rely on different analytical principles, all with their own (analytical) specifications. This article provides an overview of the different clinical applications of serum albumin measurements in nephrology, the (dis)advantages of the available assays and the estimates of the effects of the measurement uncertainty between different assays in clinical decision making. This article concludes that harmonization of serum albumin assay results is needed.

Improving the laboratory result release process in the light of ISO 15189:2012 standard.

The ISO 15189:2012 standard section 5.9.1 requires laboratories to review results before release, considering quality control, previous results, and clinical information, if any, and to issue documented procedures about it. While laboratory result reporting is generally regarded as part of the post-analytical phase, the result release process requires a general view of the total examination process. Reviewing test results may follow with troubleshooting and test repetition, including reanalyzing an individual sample or resampling. A systematic understanding of the result release may help laboratory professionals carry out appropriate test repetition and ensure the plausibility of laboratory results. In this paper, we addressed the crucial steps in the result release process, including evaluation of sample quality, critical result notification, result reporting, and recommendations for the management of the result release, considering quality control alerts, instrument flags, warning messages, and interference indexes. Error detection tools and plausibility checks mentioned in the present paper can support the daily practice of results release.

Impact of mental resilience and perceived immune functioning on the severity of alcohol hangover.

OBJECTIVE: Recent research comparing hangover sensitive drinkers with hangover resistant drinkers has revealed that experiencing alcohol hangovers is associated with significantly poorer self-reported immune functioning (p < 0.0001). No significant difference between the groups was found on mental resilience. The objective of the current survey was to examine the association between hangover severity, perceived immune status, and mental resilience. N = 341 Dutch students, all hangover sensitive drinkers, completed an online survey. The Brief Resilience Scale was completed, and perceived immune functioning and overall hangover severity for their latest past month hangover were assessed. RESULTS: Students consumed a mean (SD) of 12.3 (5.9) alcoholic drinks the evening before their latest hangover. A significant positive association was found between mental resilience and perceived immune functioning (r = 0.372, p = 0.000). No significant associations of hangover severity were found with mental resilience (r = - 0.010, p = 0.858), or perceived immune functioning (r = - 0.025, p = 0.645). Previous research revealed that hangover resistant and hangover sensitive drinkers report having significantly different levels of immune functioning, and that the immune system is involved in the development of alcohol hangover. These findings suggest that levels of mental resilience and perceived immune functioning are not related to the severity of hangovers in hangover sensitive drinkers.

Susceptibility to Alcohol Hangovers: The Association with Self-Reported Immune Status.

Increasing evidence points at a role for the immune system in the genesis of the alcohol hangover. This study investigated the association between self-reported immune function and experiencing hangovers. Dutch students aged 18 to 30 years old were invited to complete an online survey. Eighteen items on immune-related complaints were completed to assess self-reported immune function. Alcohol consumption in the past month (with respect to usual consumption and the occasion of heaviest drinking) was also recorded. Subjects with an estimated blood alcohol concentration (eBAC) of 0.18% or higher on their heaviest drinking occasion in the prior month were included in the analyses. Self-reported immune function was compared between drinkers with a hangover and those who claimed to be hangover resistant. In total, of 481 subjects (79.2% women) with a mean (SD) age of 21.1 (1.9) years old were included in the analysis. Of these, 83.3% (n = 400) reported having hangovers and 16.8% (n = 81) claimed to be hangover resistant. Drinkers with hangovers had significantly higher self-reported overall immune function scores when compared to hangover-resistant drinkers (mean ± SD = 10.5 ± 3.6 versus 13.1 ± 4.9, p = 0.0001), indicating a poorer immune status. In conclusion, experiencing alcohol hangovers is associated with significantly poorer self-reported immune function.

Differences in the Temporal Typology of Alcohol Hangover.

BACKGROUND: At a group level, hangover severity during the day has been described to follow an inverted U-shaped curve, with gradually increasing severity scores that, after reaching a peak, gradually decrease toward zero. The aim of this study was to examine if and how individual drinkers' hangover severity scores vary during the day. METHODS: Data from a survey (Penning et al., ) in which 727 drinkers reported on their latest alcohol hangover were reanalyzed. The temporal pattern of each individual's hangover was first categorized as belonging to 1 of 6 types based on predefined temporal characteristics. RESULTS: Three dominant hangover patterns emerged as comprising more than 95% of the sample: (i) a continuous decline hangover (Severity Type 1 hangover, 54.5%), (ii) a steady state hangover (Severity Type 2 hangover, 19.1%), and (iii) an inverted U-shaped curve hangover (Severity Type 3 hangover, 21.8%). Of these 3 patterns, Severity Type 2 hangovers are associated with significantly less alcohol consumption and with having the lowest severity scores of individual hangover symptoms. Severity Type 1 hangovers are associated with having the highest severity of individual hangover symptoms. In line with significantly lower levels of alcohol consumption, Severity Type 2 hangovers were significantly more often observed in women when compared to men. Severity Type 1 hangovers were significantly more common in men than in women. Severity Type 3 hangovers, characterized by the increased presence of gastrointestinal complaints, were equally commonly experienced in men and women. CONCLUSIONS: This study revealed that the temporal pattern of hangover severity can follow marked interindividual variability. Three common temporal patterns were identified, which are uniquely related to the amount of alcohol consumed and the presence and severity of different individual hangover symptoms. Better understanding of individual differences in hangover typology may help to delineate mechanisms underlying alcohol hangover.

Susceptibility to Alcohol Hangovers: Not Just a Matter of Being Resilient.

INTRODUCTION: Although most drinkers have experienced a hangover the day following heavy alcohol consumption, a minority claims to be hangover resistant despite consuming the same large quantities of alcohol as those reporting alcohol hangover. The aim of the current study was to examine if susceptibility to experiencing hangovers is related to a drinker's interpretation of wellbeing and psychological assets to bounce back. METHODS: A survey was conducted among 2295 Dutch students assessing their past month alcohol consumption patterns, and measuring mental resilience and wellbeing. Estimated peak blood alcohol concentration (e-pBAC) for their heaviest drinking occasion in the past month was computed for each participant. Data from participants who reported a past month hangover, i.e. hangover sensitive drinkers, were compared with hangover resistant drinkers. The analyses were conducted for (a) all participants reaching an e-pBAC ≥ 0.11% (N = 986, of which 24.6% claimed to be hangover resistant) and (b) participants reaching an e-pBAC ≥ 0.18% (N = 480, of which 16.7% claimed to be hangover resistant). RESULTS: For both e-pBAC cut-off values, no significant differences between hangover sensitive and hangover resistant drinkers were found for mental resilience and wellbeing. CONCLUSION: The current findings suggest that having a hangover is not simply an expression of poor psychological coping with the next-day consequences of heavy alcohol consumption.

Total sleep time, alcohol consumption, and the duration and severity of alcohol hangover.

INTRODUCTION: An evening of alcohol consumption often occurs at the expense of sleep time. The aim of this study was to determine the relationship between total sleep time and the duration and severity of the alcohol hangover. METHODS: A survey was conducted among Dutch University students to collect data on their latest alcohol hangover. Data on alcohol consumption, total sleep time, hangover severity, and duration were collected. Alcohol consumption and hangover severity and duration were compared for participants who (a) slept <5 hours, (b) slept between 5 and 7 hours, or (c) slept >7 hours. RESULTS: Data from N=578 students (40.1% men and 59.9% women) were included in the statistical analyses. Significant correlations were found between total sleep time and alcohol consumption (r=0.117, p=0.005), hangover severity (r= -0.178, p=0.0001) and hangover duration (r=0.168, p=0.0001). In contrast, total alcohol consumption did not correlate significantly with overall hangover severity or duration. Those who slept longer than 7 hours consumed significantly more alcohol (p=0.016) and reported extended hangover duration (p=0.004). However, they also reported significantly less severe hangovers (p=0.001) than students who slept <7 hours. CONCLUSION: Reduced total sleep time is associated with more severe alcohol hangovers.

The impact of alcohol hangover symptoms on cognitive and physical functioning, and mood.

Hangover research often records the presence and severity of symptoms experienced the day after heavy alcohol consumption. However, usually no information is gathered on the impact of experiencing these symptoms on mood, cognition, and physical activities. An online survey was held among Dutch students, aged 18-30 years, who recently had a hangover. Overall hangover severity (i.e., a single 1-item rating) and the severity of 22 individual symptoms were rated on an 11-point scale ranging from 0 (absent) to 10 (extreme). In addition, for each symptom, participants were asked to rate their respective negative impact on (a) cognitive functioning, (b) physical functioning, and (c) mood, on a 6-point Likert scale ranging from 0 (no impact) to 5 (extreme). N = 1837 subjects completed the survey. The mean (SD) overall (1-item) hangover severity score was 6.1 (1.9). Sleepiness, being tired, thirst, and concentration problems were the most frequently reported hangover symptoms. These symptoms also reached the highest severity scores (ranging from 6.3 to 7.0). The 4 symptoms with the biggest combined impact on mood, and cognitive and physical functioning were being tired, sleepiness, headache, and concentration problems. In conclusion, whereas severity and impact scores usually correspond well, some frequently reported symptoms with moderate to high severity scores had little impact on mood, and cognitive and physical functioning (i.e., reduced appetite, regret, and thirst).

Mental resilience, perceived immune functioning, and health.

BACKGROUND: Mental resilience can be seen as a trait that enables an individual to recover from stress and to face the next stressor with optimism. People with resilient traits are considered to have a better mental and physical health. However, there are limited data available assessing the relationship between resilient individuals and their perspective of their health and immune status. Therefore, this study was conducted to examine the relationship between mental resilience, perceived health, and perceived immune status. METHODS: A total of 779 participants recruited at Utrecht University completed a questionnaire consisting of demographic characteristics, the brief resilience scale for the assessment of mental resilience, the immune function questionnaire (IFQ), and questions regarding their perceived health and immune status. RESULTS: When correcting for gender, age, height, weight, smoker status, amount of cigarettes smoked per week, alcohol consumption status, amount of drinks consumed per week, drug use, and frequency of past year drug use, mental resilience was significantly correlated with perceived health (r=0.233, p=0.0001), perceived immune functioning (r=0.124, p=0.002), and IFQ score (r=-0.185, p=0.0001). CONCLUSION: A significant, albeit modest, relationship was found between mental resilience and perceived immune functioning and health.