Band 61, Heft 2

Objectives Unlike many dose-response curves used in clinical chemistry, the immunoassay curve used to quantitate measurands is often sigmoidal rather than linear. Consequently, a more complex curve fitting model is required. Various models are available, but they can introduce bias, and there can be little awareness of why this error can be introduced. Content These curve-fitting models include those based on the law of mass-action, empirical models such as splines or linearization models such as the log/logit function. All these models involve assumptions, which can introduce bias as the dose-response curve is ‘forced’ to fit or minimize the distance between the standard concentration points to the theoretical curve. The most common curve fitting model is the four or five parameter model, which uses four or five parameters to fit a sigmoidal curve to a set of standard points. Summary and outlook Measurement of cardiac troponin is an important element in establishing a diagnosis of acute myocardial infarction. We use troponin, a cardiac biomarker, to demonstrate the potential effect of the bias that the curve fit could introduce. Troponin is used for both rule-in and rule-out decisions at different concentrations and at either end of the dose-response curve. The curve fitting process can cause lot-to-lot reagent (and calibrator) variation in immunoassay. However, laboratory staff need to be aware of this potential source of error and why it occurs. Understanding how the error occurs leads to a greater awareness of the importance of validating new reagent/calibrator assessment using patient samples with concentrations at crucial decision points.

Due to the many technical limitations of molecular biology, the possibility to sustain enormous volumes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic testing relies strongly on the use of antigen rapid diagnostic tests (Ag-RDTs). Besides a limited analytical sensitivity, the manually intensive test procedures needed for performing these tests, very often performed by unskilled personnel or by the patients themselves, may contribute to considerably impair their diagnostic accuracy. We provide here an updated overview on the leading preanalytical drawbacks that may impair SARS-CoV-2 Ag-RDT accuracy, and which encompass lower diagnostic sensitivity in certain age groups, in asymptomatic subjects and those with a longer time from symptoms onset, in vaccine recipients, in individuals not appropriately trained to their usage, in those recently using oral or nasal virucidal agents, in oropharyngeal swabs and saliva, as well as in circumstances when instructions provided by the manufacturers are unclear, incomplete or scarcely readable and intelligible. Acknowledging these important preanalytical limitations will lead the way to a better, more clinically efficient and even safer use of this important technology, which represents an extremely valuable resource for management of the ongoing pandemic.

As testing for infectious diseases moves from manual, biological testing such as complement fixation to high throughput automated autoanalyzer, the methods for controlling these assays have also changed to reflect those used in clinical chemistry. However, there are many differences between infectious disease serology and clinical chemistry testing, and these differences have not been considered when applying traditional quality control methods to serology. Infectious disease serology, which is highly regulated, detects antibodies of varying classes and to multiple and different antigens that change according to the organisms’ genotype/serotype and stage of disease. Although the tests report a numerical value (usually signal to cut-off), they are not measuring an amount of antibodies, but the intensity of binding within the test system. All serology assays experience lot-to-lot variation, making the use of quality control methods used in clinical chemistry inappropriate. In many jurisdictions, the use of the manufacturer-provided kit controls is mandatory to validate the test run. Use of third-party controls, which are highly recommended by ISO 15189 and the World Health Organization, must be manufactured in a manner whereby they have minimal lot-to-lot variation and at a level where they detect exceptional variation. This paper outlines the differences between clinical chemistry and infectious disease serology and offers a range of recommendations when addressing the quality control of infectious disease serology.

Laboratories should estimate and validate [using analytical performance specifications (APS)] the measurement uncertainty (MU) of performed tests. It is therefore essential to appropriately define APS for MU, but also to provide a perspective on suitability of the practical application of these APS. In this study, 23 commonly ordered measurands were allocated to the models defined during the 2014 EFLM Strategic Conference to derive APS for MU. Then, we checked if the performance of commercial measuring systems used in our laboratory may achieve them. Most measurands (serum alkaline phosphatase, aspartate aminotransferase, creatine kinase, γ-glutamyltransferase, lactate dehydrogenase, pancreatic amylase, total proteins, immunoglobulin G, A, M, magnesium, urate, and prostate-specific antigen, plasma homocysteine, and blood red and white cells) were allocated to the biological variation (BV) model and desirable APS were defined accordingly (2.65%, 4.75%, 7.25%, 4.45%, 2.60%, 3.15%, 1.30%, 2.20%, 2.50%, 2.95%, 1.44%, 4.16%, 3.40%, 3.52%, 1.55%, and 5.65%, respectively). Desirable APS for serum total cholesterol (3.00%) and urine albumin (9.00%) were derived using outcome-based model. Lacking outcome-based information, serum albumin, high-density lipoprotein cholesterol, triglycerides, and blood platelets were temporarily reallocated to BV model, the corresponding desirable APS being 1.25%, 2.84%, 9.90%, and 4.85%, respectively. A mix between the two previous models was employed for serum digoxin, with a 6.00% desirable APS. In daily practice by using our laboratory systems, 16 tests fulfilled desirable and five minimum APS, while two (serum albumin and plasma homocysteine) exceeded goals, needing improvements.

The background to this debate is now well-known: an EU policy decision to tighten controls on the devices and diagnostics sector led to the adoption of a regulation in 2017 with a schedule for implementation over coming years – a timetable extended still further by last-minute legislation in early 2022, to provide the sector and regulators with more time to adapt to the changes. Discussions among experts organised in April by the European Alliance for Personalized Medicine (EAPM) exposed continuing challenges that cannot be fully resolved by the recent deferral of implementation deadlines. One salient problem is that there is little awareness of the In Vitro Diagnostic Regulation (IVDR) across Europe, and only limited awareness of the different structures of national systems involved in implementing IVDR, with consequent risks for patient and consumer access to in vitro diagnostics (IVDs). The tentative conclusion from these consultations is that despite a will across the sector to seek workable solutions, the obstacles remain formidable, and the potential solutions so far proposed remain more a matter of aspirations than of clear pathways.

Objectives Timely diagnosis of Alzheimer’s disease (AD) is critical for appropriate treatment/patient management. Cerebrospinal fluid (CSF) biomarker analysis is often used to aid diagnosis. We assessed analytical performance of second-generation (Gen II) Elecsys ® CSF immunoassays (Roche Diagnostics International Ltd), and adjusted existing cut-offs, to evaluate their potential utility in clinical routine. Methods Analytical performance was assessed using CSF samples measured with Elecsys CSF Gen II immunoassays on cobas e analyzers. Aβ42 Gen I/Gen II immunoassay method comparisons were performed (Passing-Bablok regression). Cut-off values were adjusted using estimated bias in biomarker levels between BioFINDER protocol aliquots/Gen I immunoassays and Gen II protocol aliquots/immunoassays. Distribution of Gen II immunoassay values was evaluated in AD, mild cognitive impairment (MCI), and cognitively normal cohorts; percentage observations outside the measuring range were derived. Results The Gen II immunoassays demonstrated good analytical performance, including repeatability, intermediate precision, lot-to-lot agreement (Pearson’s r: ≥0.999), and platform agreement (Pearson’s r: ≥0.995). Aβ42 Gen I/Gen II immunoassay measurements were strongly correlated (Pearson’s r: 0.985–0.999). Aβ42 Gen II immunoassay cut-offs were adjusted to 1,030 and 800 ng/L, and pTau181/Aβ42 ratio cut-offs to 0.023 and 0.029, for Gen II and I protocols, respectively. No observations were below the lower limit of the measuring range; above the upper limit, there were none from the AD cohort, and 2.6 and 6.8% from the MCI and cognitively normal cohorts, respectively. Conclusions Our findings suggest that the Gen II immunoassays have potential utility in clinical routine to aid diagnosis of AD.

Objectives This study aims to evaluate the interchangeability between the Siemens Healthineers’ “EVRO” new affinity chrome-mediated immunoassay (ACMIA/EVRO) and Thermo Fisher Scientific’s “EVER” Quantitative Microsphere System (QMS/EVER) with Chromsystems’ CE-IVD-certified “MassTox” liquid-chromatography/tandem-mass spectrometry (LC-MS/MS) assay for the therapeutic drug monitoring of everolimus. Methods A single lot of reagent, calibrators and controls were used for each assay. A total of 67 whole blood samples (n=67) from patients receiving solid organ transplant were analyzed (n=31 with kidney transplant and n=36 with liver transplant); Passing-Bablok regression and Bland-Altman difference plot were used to evaluate bias and individual agreement; LC-MS/MS analysis was used to measure the actual concentrations of calibrators and controls compared to the assigned value. Results ACMIA/EVRO did not show any systematic bias compared to LC-MS/MS (intercept=0.244 ng/mL, 95% CI: −0.254 to 0.651 ng/mL). Nevertheless, significant proportional bias (slope=1.511, 95% CI: 1.420 to 1.619) associated to a combined bias of 44.8% (95% CI: 41.2–48.3%) was observed. Conversely, QMS/EVER did not show any bias at both systematic (intercept=−0.151 ng/mL, 95% CI: −0.671 to 0.256 ng/mL) and proportional level (slope=0.971, 95% CI: 0.895 to 1.074) with a non-statistically significant combined bias of −3.6% (95% CI: −8.4–1.1%). Based on a concentration of calibrators and controls above the assigned value for both the analytical methods, in the ACMIA/EVRO a correction which was approximately one-third of the correction for the QMS/EVER was observed. Conclusions ACMIA/EVRO but not QMS/EVER shows a lack of interchangeability with the CE-IVD-certified LC-MS/MS assay. We hypothesize that, as the ACMIA/EVRO uses an anti-sirolimus antibody, the under-corrected assigned value in the assay calibrators was not sufficient to reproduce the everolimus metabolites cross-reactivity occurring in real samples.

Objectives This study aimed to establish time-resolved fluorescence immunoassays to quantitatively detect the autoantibodies targeting different epitopes of M-type phospholipase A2 receptor (PLA2R) and evaluate its clinical application in primary membranous nephropathy (PMN). Methods PLA2R and its reactive epitope-specific IgG/IgG4 time-resolved fluorescence immunoassays (TRFIAs) were established using europium-labeled anti-human IgG/IgG4 antibodies, recombinant proteins, and patient serum. The levels of IgG/IgG4 targeting PLA2R and its epitopes in PMN patient serum were detected, and the relationship between epitope spreading of PLA2R and the severity of patients with PMN was evaluated. Results The TRFIAs established in this study could quantitatively detect PLA2R and its epitope-specific IgG and IgG4. Sera from 59 patients with PMN were subjected to detection using anti-PLA2R IgG and anti-PLA2R IgG4. Among them, 46 and 54 patients were found positive for PLA2R antibodies, respectively. Moreover, the levels of PLA2R antibodies were strongly correlated with the severity of patients with PMN. Patients who were detected to have two or more epitopes had more serious renal injury. Conclusions PLA2R domain-specific IgG/IgG4 TRFIAs were established in this study, and detection with anti-PLA2R IgG4 could more sensitively screen the reactivity of patients to the PLA2R domain. Moreover, detection epitope spreading of PLA2R was confirmed which is related to the severity of patients with PMN.

Objectives Laboratory information systems typically contain hundreds or even thousands of reference limits stratified by sex and age. Since under these conditions a manual plausibility check is hardly feasible, we have developed a simple algorithm that facilitates this check. An open-source R tool is available as a Shiny application at github.com/SandraKla/Zlog_AdRI. Methods Based on the zlog standardization, we can possibly detect critical jumps at the transitions between age groups, regardless of the analytical method or the measuring unit. Its advantage compared to the standard z-value is that means and standard deviations are calculated from the reference limits rather than from the underlying data itself. The purpose of the tool is illustrated by the example of reference intervals of children and adolescents from the Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER). Results The Shiny application identifies the zlog values, lists them in a colored table format and plots them additionally with the specified reference intervals. The algorithm detected several strong and rapid changes in reference intervals from the neonatal period to puberty. Remarkable jumps with absolute zlog values of more than five were seen for 29 out of 192 reference limits (15.1%). This might be attenuated by introducing shorter time periods or mathematical functions of reference limits over age. Conclusions Age-partitioned reference intervals will remain the standard in laboratory routine for the foreseeable future, and as such, algorithmic approaches like our zlog approach in the presented Shiny application will remain valuable tools for testing their plausibility on a wide scale.

Objectives The aim of this study was to harmonize the criteria for the Bhattacharya indirect method Microsoft Excel Spreadsheet for reference intervals calculation to reduce between-user variability and use these criteria to calculate and evaluate reference intervals for eight analytes in two different years. Methods Anonymized laboratory test results from outpatients were extracted from January 1st 2018 to December 31st 2019. To assure data quality, we examined the monthly results from an external quality control program. Reference intervals were determined by the Bhattacharya method with the St Vincent’s hospital Spreadsheet firstly using original criteria and then using additional harmonized criteria defined in this study. Consensus reference intervals using the additional harmonized criteria were calculated as the mean of four users’ lower and upper reference interval results. To further test the operation criteria and robustness of the obtained reference intervals, an external user validated the Spreadsheet procedure. Results The extracted test results for all selected laboratory tests fulfilled the quality criteria and were included in the present study. Differences between users in calculated reference intervals were frequent when using the Spreadsheet. Therefore, additional criteria for the Spreadsheet were proposed and applied by independent users, such as: to set central bin as the mean of all the data, bin size as small as possible, at least three consecutive bins and a high proportion of bins within the curve. Conclusions The proposed criteria contributed to the harmonization of reference interval calculation between users of the Bhattacharya indirect method Spreadsheet.

Objectives Red blood cell parameters are frequently used biomarkers when assessing clinical status in newborns and in early childhood. Cell counts, amounts, and concentrations of these parameters change through gestation and after birth. Robust age-specific reference intervals are needed to optimize clinical decision making. Methods The Copenhagen Baby Heart Study (CBHS) and the COMPARE study are prospective cohort studies including red blood cell parameters from 7,938 umbilical cord blood samples and 295 parallel venous blood samples from newborns with follow-up at two and at 14–16 months after birth. Results For venous blood at birth, reference intervals for hemoglobin, erythrocytes, and hematocrit were 145–224 g/L, 4.1–6.4 × 10 12 /L, and 0.44–0.64, respectively. Hemoglobin, erythrocytes, and hematocrit were lower at birth in children delivered by prelabor cesarean section compared to vaginal delivery. Conversion algorithms based on term newborns were: venous hemoglobin=(umbilical cord hemoglobin˗86.4)/0.39; venous erythrocytes=(umbilical cord erythrocytes-2.20)/0.44; and venous hematocrit=(umbilical cord hematocrit-0.24)/0.45. Conclusions This study presents new reference intervals for red blood cell parameters in early childhood, describes the impact of delivery mode, and provide exact functions for converting umbilical cord to venous blood measurements for term newborns. These findings may improve clinical decision making within neonatology and infancy and enhance our clinical understanding of red blood cell parameters for health and diseases in early life.

Objectives Oxysterols, a family of oxidized cholesterol derivates, are of increasing interest due to their role in cancer development and progression. Some oxysterols are estrogen receptor modulators and thus of particular interest in breast cancer research. In human studies, two forms of circulating oxysterols are commonly evaluated: “free” (unesterified) and “total” (esterified and unesterified). However, associations between free and total oxysterols are not well established. We addressed this knowledge gap in a pilot study by evaluating correlations between the free and the total form of each of the circulating oxysterols (free vs. total), and pairwise associations within the panel of total oxysterols (total vs. total) and the panel of free oxysterols (free vs. free). Methods Concentrations of oxysterols and other non-cholesterol sterols were quantified in blood samples of 27 breast cancer patients from the MARIE breast cancer patient cohort using liquid chromatography mass spectrometry. We used Spearman rank correlations to assess associations. Overall, 12 oxysterols (including 27-hydroxycholesterol (HC), 25-HC, 24S-HC, 7a-HC, 5a6a-epoxycholesterol) and five sterols (including lanosterol and desmosterol) were analyzed. Results Strong correlations (r≥0.82) were observed for seven circulating free and total oxysterols/sterols. The free and total form of 27-HC (r=0.63), 25-HC (r=0.54), and two more oxysterols were weaker correlated. Correlation patterns in the panel of total oxysterols/sterols and the panel of free oxysterols/sterols were similar. Conclusions These findings demonstrate that concentrations of most free and total oxysterols/sterols are strongly correlated. We provide further insight into the interrelationships between oxysterols in breast cancer patients.

Objectives The stability of gene transcripts associated with the presence of circulating tumor cells (CTCs) has been predominantly studied in cultured cancer cell lines added to blood samples under artificial conditions. In the present study the effect of storage on CTC-related transcripts was assessed in blood samples taken from patients with non-small lung cancer (n=58). Methods The blood samples were split in two equal parts to compare the gene expression with and without storage for 24 h at ambient temperature without preservative added. After enrichment using the microfluidic Parsortix ® technology, the expression levels of selected genes were assessed using quantitative PCR following a gene-specific pre-amplification. The prognostic relevance of each gene in fresh and stored blood samples was evaluated using the R-package Survminer. Results Some genes were either not affected ( TWIST 1, CDH5 , CK19 ) or upregulated upon storage ( NANOG , MET , UCHL1 ) but still associated with poor prognosis. In contrast, ERBB3 , PTHLH , EpCAM , and TERT were no longer associated with the overall survival of the patients. Conclusions The study demonstrates the surprising stability of CTC-related transcripts, which makes overnight shipping of native blood samples possible. Careful verification is required when using model systems – such as normal blood spiked with tumor cells – or other CTC-related markers, as individual transcripts may respond differently to storage.

Objectives During 2020, the UK’s Department of Health and Social Care (DHSC) established the Moonshot programme to fund various diagnostic approaches for the detection of SARS-CoV-2, the pathogen behind the COVID-19 pandemic. Mass spectrometry was one of the technologies proposed to increase testing capacity. Methods Moonshot funded a multi-phase development programme, bringing together experts from academia, industry and the NHS to develop a state-of-the-art targeted protein assay utilising enrichment and liquid chromatography tandem mass spectrometry (LC-MS/MS) to capture and detect low levels of tryptic peptides derived from SARS-CoV-2 virus. The assay relies on detection of target peptides, ADETQALPQRK (ADE) and AYNVTQAFGR (AYN), derived from the nucleocapsid protein of SARS-CoV-2, measurement of which allowed the specific, sensitive, and robust detection of the virus from nasopharyngeal (NP) swabs. The diagnostic sensitivity and specificity of LC-MS/MS was compared with reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) via a prospective study. Results Analysis of NP swabs (n=361) with a median RT-qPCR quantification cycle (Cq) of 27 (range 16.7–39.1) demonstrated diagnostic sensitivity of 92.4% (87.4–95.5), specificity of 97.4% (94.0–98.9) and near total concordance with RT-qPCR (Cohen’s Kappa 0.90). Excluding Cq>32 samples, sensitivity was 97.9% (94.1–99.3), specificity 97.4% (94.0–98.9) and Cohen’s Kappa 0.95. Conclusions This unique collaboration between academia, industry and the NHS enabled development, translation, and validation of a SARS-CoV-2 method in NP swabs to be achieved in 5 months. This pilot provides a model and pipeline for future accelerated development and implementation of LC-MS/MS protein/peptide assays into the routine clinical laboratory.

Obejctives Serosurveys can be used to monitor COVID-19 seroprevalence and conduct surveillance. Dried blood spot (DBS), used increasingly as a valuable sample to assay severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) antibodies (Ab), has several advantages, particularly in infants, due to the limited amount of blood required and its utility in testing a large number of samples in a limited time-frame. We evaluated SARS-CoV-2 IgG Ab prevalence in newborn DBS in the Trentino region of Italy, during the time period January 2020 – December 2021. Methods Anti-SARS-CoV-2 IgG levels were determined in DBS by means of Anti-SARS-CoV-2 QuantiVac IgG ELISA assay (Euroimmun, Lubeck, Germany). Results Analyses included 2,400 DBS from newborns (54% M, 46% F), samples being collected 2–3 days after birth. The first DBS that tested positive for anti-SARS-CoV-2 IgG antibodies was found in March 2020 and, up to May 2020, only 4 positive results were detected overall. Starting from June 2020, the positivity thresholds increased according to the epidemiological waves of the COVID-19 pandemic in Italy, with a robust increment in the winters of 2020 and 2021. The percentage of positive DBS rose from 0 to 6% to 10–47%, in 2020 and 2021, respectively. Conclusions This study demonstrates DBS is a suitable tool for both epidemiological purposes and surveillance in the SARS-CoV-2 pandemic, particularly in newborns and pregnant women, saving blood waste and sparing patients any discomfort.

Objectives This proof of concept study was aimed to validate the hypothesis that the time of positivization of SARS-CoV-2 self-performed rapid diagnostic tests (RDTs) may reflect the actual viral load in the specimen. Methods A SARS-CoV-2 positive sample with high viral load was diluted and concomitantly assayed with molecular assay (Xpert Xpress SARS-CoV-2) and RDT (COVID-VIRO ALL IN RDT). The (mean cycle threshold; Ct) values and RDT positivization times of these dilutions were plotted and interpolated by calculating the best fit. The parameters of this equation were then used for converting the positivization times into RDT-estimated SARS-CoV-2 Ct values in routine patient samples. Results The best fit between measured and RDT-estimated Ct values could be achieved with a 2-degree polynomial curve. The RDT-estimated Ct values exhibited high correlation (r=0.996) and excellent Deming fit ( y =1.01 ×  x  − 0.18) with measured Ct values. In 30 consecutive patients with positive RDT test, the correlation between RDT positivization time and measured Ct value was r=0.522 (p=0.003). The correlation of RDT-estimated and measured Ct values slightly improved to 0.577 (Deming fit: y =0.44 ×  x  + 11.08), displaying a negligible bias (1.0; 95% CI, −0.2 to 2.2; p=0.105). Concordance of RDT-estimated and measured Ct values at the <20 cut-off was 80%, with 0.84 sensitivity and 0.73 specificity. Conclusions This proof of concept study demonstrates the potential feasibility of using RDTs for garnering information on viral load in patients with acute SARS-CoV-2 infection.

Objectives The rapid, accurate and safe detection of SARS-CoV-2 is the key to improving surveillance and infection containment. The aim of the present study was to ascertain whether, after heat/chemical inactivation, SARS-CoV-2 N antigen chemiluminescence (CLEIA) assay in saliva remains a valid alternative to molecular testing. Methods In 2022, 139 COVID-19 inpatients and 467 healthcare workers were enrolled. In 606 self-collected saliva samples (Salivette), SARS-CoV-2 was detected by molecular (TaqPath rRT-PCR) and chemiluminescent Ag assays (Lumipulse G). The effect of sample pre-treatment (extraction solution-ES or heating) on antigen recovery was verified. Results Salivary SARS-CoV-2 antigen assay was highly accurate (AUC=0.959, 95% CI: 0.943–0.974), with 90% sensitivity and 92% specificity. Of the 254 antigen positive samples, 29 were false positives. We demonstrated that heterophilic antibodies could be a cause of false positive results. A significant antigen concentration decrease was observed after ES treatment (p=0.0026), with misclassification of 43 samples. Heat had a minimal impact, after treatment the correct classification of cases was maintained. Conclusions CLEIA SARS-CoV-2 salivary antigen provides accurate, timely and high-throughput results that remain accurate also after heat inactivation, thus ensuring a safer work environment. This supports the use of salivary antigen detection by CLEIA in surveillance programs.

Objectives Anti-nucleocapsid (NC) antibodies are produced in response to SARS-CoV-2 infection. Therefore, they are well suited for the detection of a previous infection. Especially in the case of seroprevalence studies or during the evaluation of a novel in-vitro diagnostic test, samples have been stored at <−70 °C (short- and long-term) or 2–10 °C (short-term) before analysis. This study aimed to assess the impact of different storage conditions relevant to routine biobanking on anti-NC antibodies. Methods The preanalytical impact of short-term storage (84 [58–98] days) on <−70 °C and for 14 days at 2–10 °C was evaluated using samples from 111 donors of the MedUni Vienna Biobank. Long-term effects (443 [409–468] days) were assessed using 208 samples from Biobank Graz and 49 samples from Biobank Vienna. Anti-Nucleocapsid antibodies were measured employing electrochemiluminescence assays (Roche Anti-SARS-CoV-2). Results After short-term storage, the observed changes did not exceed the extent that could be explained by analytical variability. In contrast, results after long-term storage were approximately 20% higher and seemed to increase with storage duration. This effect was independent of the biobank from which the samples were obtained. Accordingly, the sensitivity increased from 92.6 to 95.3% (p=0.008). However, comparisons with data from Anti-Spike protein assays, where these deviations were not apparent, suggest that this deviation could also be explained by the analytical variability of the qualitative Anti-NC assay. Conclusions Results from anti-NC antibodies are stable during short-term storage at <−70 °C and 2–10 °C. After long-term storage, a slight increase in sensitivity could not be ruled out.

Objectives Many biomarkers have been studied to assist in the risk stratification and prognostication of patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Procalcitonin (PCT), a circulating precursor of the hormone calcitonin, has been studied with mixed results as a predictor of severe coronavirus disease 2019 (COVID-19) in the general population; however, to date, no studies have focused on the utility of PCT in predicting disease severity and death from COVID-19 in the cancer population. Methods We conducted a retrospective study of cancer patients hospitalized with COVID-19 at a comprehensive cancer center over a 10-month period who had PCT recorded on admission. We assessed associations between variables of clinical interest and the primary outcomes of progression of COVID-19 and death during or within 30 days of hospitalization using univariable and multivariable logistic regression. Results The study included 209 unique patients. In the univariate analysis, elevated PCT on admission was associated with higher odds of progression of COVID-19 or death (Odds ratio [OR] 1.40, 95% CI 1.08–1.93) and mortality alone (OR 1.53, 95% CI 1.17–2.11). In multivariate regression, PCT remained significantly associated with progression or death after holding chronic kidney disease (CKD) status constant (OR 1.40, 95% CI: 1.08, 1.93, p=0.003). Similarly, the association of PCT and death remained significant after adjusting for age (OR 1.54, 95% CI: 1.17–2.15). Conclusions In hospitalized COVID-19 patients with underlying cancer, initial PCT levels on admission may be associated with prognosis, involving higher odds of progression of COVID-19 and/or mortality.

Objectives We aimed to evaluate the impact of an uninterrupted workflow regarding blood cultures on turnaround time and antibiotic prescription. Methods Monomicrobial episodes of bacteremia were retrospectively evaluated before and after a continuous 24/7 workflow was implemented in our clinical microbiology laboratory (pre- and post-intervention periods; PREIP and POSTIP). Primary outcome was the time from specimen collection to the first change in antibiotic therapy. Secondary outcomes included the time from specimen collection to effective antibiotic therapy and to antibiotic susceptibility testing results (or turnaround time), as well as hospital length of stay and all-cause mortality at 30 days. Results A total of 548 episodes of bacteremia were included in the final analysis. There was no difference in PREIP and POSTIP regarding patient characteristics and causative bacteria. In POSTIP, the mean time to the first change in antibiotic therapy was reduced by 10.4 h (p<0.001). The time to effective antibiotic therapy and the turnaround time were respectively reduced by 4.8 h (p<0.001) and 5.1 h (p=0.006) in POSTIP. There was no difference in mean hospital length of stay or mortality between the two groups. Conclusions Around the clock processing of blood cultures allows for a reduction in turnaround time, which in turn reduces the delay until effective antibiotic therapy prescription.

Objectives To compare the artificial intelligence algorithms as powerful machine learning methods for evaluating patients with suspected sepsis using data from routinely available blood tests performed on arrival at the hospital. Results were compared with those obtained from the classical logistic regression method. Methods The study group consisted of consecutive patients with fever and suspected infection admitted to the Emergency Department. The complete blood counts (CBC) were acquired using the Mindray BC-6800 Plus analyser (Mindray Diagnostics, Shenzhen, China). Cell Population Data (CPD) were also recorded. The ML and artificial intelligence (AI) models were developed; their performance was evaluated using several indicators, such as the area under the receiver operating curve (AUC), calibration plots and decision curve analysis (DCA). Results Overall, all the tested approaches obtained an AUC>0.90. The logistic regression (LR) performed well compared to the ML/AI models. The naïve Bayes and the K-nearest neighbour (KNN) methods did not show good calibration properties. The multi-layer perceptron (MLP) model was the best in terms of discrimination, calibration and clinical usefulness. Conclusions The best performance in the early detection of sepsis was achieved using the ML and AI models. However, external validation studies are needed to strengthen model derivation and procedure updating.

Objectives Bloodstream infection (BSI) is one of the major causes of death in pediatric tumor patients. Blood samples are relatively easy to obtain and thus provide a ready source of infection-related biological markers for the prompt evaluation of infection risk. Methods A total of 259 pediatric tumor patients were included from May 2019 to March 2022. Patients were divided into BSI group (n=70) and control group (n=189). Clinical and biological data were collected using electronic medical records. Differences in biological markers between BSI group and control group and differences before and during infection in BSI group were analyzed. Results The infected group showed higher levels of procalcitonin (PCT) and hypersensitive C-reactive-protein (hsCRP), and lower prealbumin (PA) than the uninfected group. Area under the receiver-operating curve (ROC) curves (AUC) of PCT, hsCRP and NLR (absolute neutrophil count to the absolute lymphocyte count) were 0.756, 0.617 and 0.612. The AUC of other biomarkers was ≤0.6. In addition, PCT, hsCRP, NLR and fibrinogen (Fg) were significantly increased during infection, while PA and lymphocyte (LYM) were significantly decreased. Antibiotic resistant of Gram-positive bacteria to CHL, SXT, OXA and PEN was lower than that of Coagulase-negative Staphylococcus . Resistant of Gram-positive bacteria to CHL was lower, while to SXT was higher than that of Gram-negative bacteria. Conclusions This study explored the utility of biomarkers to assist in diagnosis and found that the PCT had the greatest predictive value for infection in pediatric tumor patients with BSI. Additionally, the PCT, hsCRP, NLR, PA, LYM and Fg were changed by BSI.