Volume 62, Issue 5

Artificial intelligence (AI) and machine learning (ML) are becoming vital in laboratory medicine and the broader context of healthcare. In this review article, we summarized the development of ML models and how they contribute to clinical laboratory workflow and improve patient outcomes. The process of ML model development involves data collection, data cleansing, feature engineering, model development, and optimization. These models, once finalized, are subjected to thorough performance assessments and validations. Recently, due to the complexity inherent in model development, automated ML tools were also introduced to streamline the process, enabling non-experts to create models. Clinical Decision Support Systems (CDSS) use ML techniques on large datasets to aid healthcare professionals in test result interpretation. They are revolutionizing laboratory medicine, enabling labs to work more efficiently with less human supervision across pre-analytical, analytical, and post-analytical phases. Despite contributions of the ML tools at all analytical phases, their integration presents challenges like potential model uncertainties, black-box algorithms, and deskilling of professionals. Additionally, acquiring diverse datasets is hard, and models’ complexity can limit clinical use. In conclusion, ML-based CDSS in healthcare can greatly enhance clinical decision-making. However, successful adoption demands collaboration among professionals and stakeholders, utilizing hybrid intelligence, external validation, and performance assessments.

Thyroid-stimulating hormone (TSH) is an important clinical marker in the diagnosis and management of thyroid disease. TSH measurements are reported in milli-International Units per Litre (mIU/L), traceable to a World Health Organisation (WHO) reference material. There is a wide variety of commercial immunoassays for TSH measurements available, which have historically been poorly harmonised due to a lack of commutability of the WHO reference materials with patient samples. This led to the recent development of a serum-based reference panel for TSH, traceable to the WHO reference material, available via the International Federation for Clinical Chemistry and Laboratory Medicine (IFCC), aimed at harmonisation of TSH immunoassays. This report describes recent developments in the TSH reference system, including establishment of the 4th WHO International Standard for TSH, and aims to clarify the relationship between the available reference materials and their intended uses. This 4th WHO IS is widely available and defines the unit of TSH activity, therefore its continued existence is of paramount importance, however it continues to show a lack of commutability with patient in many TSH immunoassays. This makes the C-STFT TSH panel, albeit available in restricted numbers, a critical resource to ensure better TSH assay harmonisation.

The indirect immunofluorescence assay on HEp-2 cells (HEp-2 IFA) is still considered the reference method to detect anti-nuclear antibodies (ANA) because of its high sensitivity and represents a relevant tool for the diagnosis of autoimmune rheumatic diseases. During the last decade, the International Consensus on ANA Patterns (ICAP) initiative promoted harmonization and understanding of HEp-2 IFA staining pattern nomenclature, as well as promoting their use in patient care by providing interpretation for HEp-2 IFA test results. In conjunction with a nationwide survey on the evolution of autoantibody diagnostics in autoimmune rheumatic diseases, we focused on the adherence of the Italian laboratories to the ICAP nomenclature analyzing its lights and shadows. The recent ICAP-oriented report, largely used today among Italian laboratories, also represents a further step in harmonizing and improving communication with the clinicians, adding value to laboratory findings and helping with critical clinical decisions.

Background In the rapid evolving landscape of artificial intelligence (AI), scientific publishing is experiencing significant transformations. AI tools, while offering unparalleled efficiencies in paper drafting and peer review, also introduce notable ethical concerns. Content This study delineates AI’s dual role in scientific publishing: as a co-creator in the writing and review of scientific papers and as an ethical challenge. We first explore the potential of AI as an enhancer of efficiency, efficacy, and quality in creating scientific papers. A critical assessment follows, evaluating the risks vs. rewards for researchers, especially those early in their careers, emphasizing the need to maintain a balance between AI’s capabilities and fostering independent reasoning and creativity. Subsequently, we delve into the ethical dilemmas of AI’s involvement, particularly concerning originality, plagiarism, and preserving the genuine essence of scientific discourse. The evolving dynamics further highlight an overlooked aspect: the inadequate recognition of human reviewers in the academic community. With the increasing volume of scientific literature, tangible metrics and incentives for reviewers are proposed as essential to ensure a balanced academic environment. Summary AI’s incorporation in scientific publishing is promising yet comes with significant ethical and operational challenges. The role of human reviewers is accentuated, ensuring authenticity in an AI-influenced environment. Outlook As the scientific community treads the path of AI integration, a balanced symbiosis between AI’s efficiency and human discernment is pivotal. Emphasizing human expertise, while exploit artificial intelligence responsibly, will determine the trajectory of an ethically sound and efficient AI-augmented future in scientific publishing.

Objectives To deliver biological variation (BV) data for serum hepcidin, soluble transferrin receptor (sTfR), erythropoietin (EPO) and interleukin 6 (IL-6) in a population of well-characterized high-endurance athletes, and to evaluate the potential influence of exercise and health-related factors on the BV. Methods Thirty triathletes (15 females) were sampled monthly (11 months). All samples were analyzed in duplicate and BV estimates were delivered by Bayesian and ANOVA methods. A linear mixed model was applied to study the effect of factors related to exercise, health, and sampling intervals on the BV estimates. Results Within-subject BV estimates (CV I ) were for hepcidin 51.9 % (95 % credibility interval 46.9–58.1), sTfR 10.3 % (8.8–12) and EPO 27.3 % (24.8–30.3). The mean concentrations were significantly different between sex, but CV I estimates were similar and not influenced by exercise, health-related factors, or sampling intervals. The data were homogeneously distributed for EPO but not for hepcidin or sTfR. IL-6 results were mostly below the limit of detection. Factors related to exercise, health, and sampling intervals did not influence the BV estimates. Conclusions This study provides, for the first time, BV data for EPO, derived from a cohort of well-characterized endurance athletes and indicates that EPO is a good candidate for athlete follow-up. The application of the Bayesian method to deliver BV data illustrates that for hepcidin and sTfR, BV data are heterogeneously distributed and using a mean BV estimate may not be appropriate when using BV data for laboratory and clinical applications.

Objectives Monitoring quality control for a laboratory or network with multiple instruments measuring the same analyte is challenging. We present a retrospective assessment of a method to detect medically significant out-of-control error conditions across a group of instruments measuring the same analyte. The purpose of the model was to ensure that results from any of several instruments measuring the same analytes in a laboratory or a network of laboratories provide comparable results and reduce patient risk. Limited literature has described how to manage QC in these very common situations. Methods Single Levey–Jennings control charts were designed using peer group target mean and control limits for five common clinical chemistry analytes in a network of eight analyzers in two different geographical sites. The QC rules used were 1 3s /2 2s /R 4s , with the mean being a peer group mean derived from a large population of the same instrument and the same QC batch mean and a group CV. The peer group data used to set the target means and limits were from a quality assurance program supplied by the instrument supplier. Both statistical and clinical assessments of significance were used to evaluate QC failure. Instrument bias was continually monitored. Results It was demonstrated that the biases of each instrument were not statistically or clinically different compared to the peer group’s average over six months from February 2023 until July 2023. Over this period, the error rate determined by the QC model was consistent with statistical expectations for the 1 3s /2 2s /R 4s rule. There were no external quality assurance failures, and no detected error exceeded the TEa (medical impact). Thus, the combined statistical/clinical assessment reduced unnecessary recalibrations and the need to amend results. Conclusions This paper describes the successful implementation of a quality control model for monitoring a network of instruments, measuring the same analytes and using externally provided quality control targets. The model continually assesses individual instrument bias and imprecision while ensuring all instruments in the network meet clinical goals for quality. The focus of this approach is on detecting medically significant out-of-control error conditions.

Objectives To evaluate the performance of the Academia-Government Collaboration for Laboratory Medicine Standardization in Korea (KR-STDZN) based on data from KR-STDZN proficiency testing (KR-STDZN-PT) for creatinine over eight years (2015–2022). Methods We used KR-STDZN-PT data of creatinine tests from 2015 to 2022. Acceptance of the participating institutions’ test results was assessed by calculating the acceptance performance as absolute bias (absBias%), total coefficient of variance (tCV%), and total error (TE%) for each sample using six measurements from each institution and true values of each reference material. The test result was considered acceptable when absBias%, tCV%, and TE% were <5.10, <3.20, and <11.40 %, respectively. The proportion of acceptable institutions among all participating institutions in each round was defined as the acceptance rate. Improvements in absBias%, tCV%, and TE% were analyzed using creatinine concentration ranges in samples. Results The number of participating institutions increased from 2015 to 2017 but remained consistent since 2018. The acceptance rates for absBias% and TE% increased from 52.2 and 77.6 %, in 2015 and to 90.7 and 96.3 %, in 2022, respectively. The acceptance rate for tCV% remained in the 90 % range for eight years. When creatinine <3 mg/dL, mean absBias%, and mean TE% improved significantly in 2021–2022 compared to 2015–2016 (p<0.05). When creatinine >3 mg/dL, acceptance performance did not improve. Mean tCV% remained consistent annually regardless of creatinine concentration. No significant variations in test methods were observed. Conclusions The collaboration between academia and the government improved creatinine testing quality. Nevertheless, KR-STDZN must be expanded and refined.

Objectives Developing procedures based on equilibrium dialysis (ED) that allow measuring the free drug concentration in plasma improves therapeutic drug monitoring (TDM) in those cases where its measurement is justified. However, this procedure requires specific sample preparation and presents different pitfalls, which are not error-free. As with any result provided by a clinical laboratory, this one should be as accurate as possible to allow a correct clinical interpretation. The measurement uncertainty (MU) is a parameter that enables the accuracy of results to be known, and that is mandated by ISO 15189. Herein, this study suggests how the MU for the results of the free drug concentrations in serum could be estimated when an ED is used. Methods A combination of the top-down and bottom-up approaches was used to estimate the MU based on the ISO/TS 20914:2019 and JCGM 100:2008 guidelines, including the concentration of free phenytoin in serum, as an example. Different scenarios were incorporated considering or not a significant bias related to the primary drawbacks of ED: the non-specific binding, the volume shift effect and the Gibbs-Donnan effect. Results The expanded uncertainties estimated ranged between 13.0 and 30.9 %. The highest MU corresponded to the free drug concentrations in serum results when significant biases related to the volume shift and Gibbs-Donnan effects exist. Conclusions A detailed estimation of MU for free drug concentrations is presented using ED, considering different scenarios. This study could stimulate clinical laboratories to perform MU studies and its application in TDM.

Objectives Blood microsampling, particularly dried blood spots (DBSs), is an attractive minimally-invasive approach that is well suited for home sampling and predictive medicine associated with longitudinal follow-up of the elderly. However, in vitro diagnostic quantification of biomarkers from DBS poses a major challenge. Clinical mass spectrometry can reliably quantify blood proteins in various research projects. Our goal here was to use mass spectrometry of DBS in a real-world clinical setting and compared it to the standard immunoassay method. We also sought to correlate DBS mass spectrometry measurements with clinical indices. Methods A clinical trial of diagnostic equivalence was conducted to compare conventional venous samples quantified by immunoassay and DBSs quantified by mass spectrometry in an elderly population. We assayed three protein biomarkers of nutritional and inflammatory status: prealbumin (transthyretin), C-reactive protein, and transferrin. Results The analysis of DBSs showed satisfactory variability and low detection limits. Statistical analysis confirmed that the two methods give comparable results at clinical levels of accuracy. In conclusion, we demonstrated, in a real-life setting, that DBSs can be used to measure prealbumin, CRP and transferrin, which are commonly used markers of nutritional status and inflammation in the elderly. However, there was no correlation with patient frailty for these proteins. Conclusions Early detection and regular monitoring of nutritional and inflammatory problems using DBS appear to be clinically feasible. This could help resolve major public health challenges in the elderly for whom frailty leads to serious risks of health complications.

Objectives To compare for the first time the performance of “GFAP and UCH-L1” vs. S100B in a cohort of patients managed for mild traumatic brain injury (mTBI) according to actualized French guidelines. Methods A prospective study was recently carried at the Emergency Department of Clermont-Ferrand University Hospital in France. Patients with mTBI presenting a medium risk of complications were enrolled. Blood S100B and “GFAP and UCHL-1” were sampled and measured according to French guidelines. S100B was measured in patients with samples within 3 h of trauma (Cobas ® , Roche Diagnostics), while GFAP and UCHL-1 were measured in all patients (samples <3 h and 3–12 h) using another automated assay (i-STAT ® Alinity, Abbott). Results For sampling <3 h, serum S100B correctly identifies intracranial lesions with a specificity of 25.7 % (95 % CI; 19.5–32.6 %), a sensitivity of 100 % (95 % CI; 66.4–100 %), and a negative predictive value of 100 % (95 % CI; 92.5–100 %). For sampling <12 h, plasma “GFAP and UCH-L1” levels correctly identify intracranial lesions with a specificity of 31.7 % (95 % CI; 25.7–38.2 %), a sensitivity of 100 % (95 % CI; 73.5–100 %), and a negative predictive value of 100 % (95 % CI; 95–100 %). Comparison of specificities (25.7 vs. 31.7 %) did not reveal a statistically significant difference (p=0.16). Conclusions We highlight the usefulness of measuring plasma “GFAP and UCH-L1” levels to target mTBI patients (sampling within 12 h post-injury) and optimize the reduction of CT scans.

Objectives A mass spectrometry (LC‒MS/MS)-based interlaboratory comparison study was performed for nine steroid analytes with five participating laboratories. The sample set contained 40 pooled samples of human serum generated from preanalyzed leftovers. To obtain a well-balanced distribution across reference intervals of each steroid, the leftovers first underwent a targeted mixing step. Methods All participants measured a sample set once using their own multianalyte protocols and calibrators. Four participants used in-house developed measurement platforms, including IVD-CE certified calibrators, which were used by three participants; the 5th lab used the whole LC‒MS kit from an IVD manufacturer. All labs reported results for 17-hydroxyprogesterone, androstenedione, cortisol, and testosterone, and four labs reported results for 11-deoxycortisol, corticosterone, cortisone, dehydroepiandrosterone sulfate (DHEAS), and progesterone. Results Good or acceptable overall comparability was found in Bland‒Altman and Passing‒Bablok analyses. Mean bias against the overall mean remained less than ±10 % except for DHEAS, androstenedione, and progesterone at one site and for cortisol and corticosterone at two sites (max. −18.9 % for androstenedione). The main analytical problems unraveled by this study included a bias not previously identified in proficiency testing, operator errors, non-supported matrix types and higher inaccuracy and imprecision at lower ends of measuring intervals. Conclusions This study shows that intermethod comparison is essential for monitoring the validity of an assay and should serve as an example of how external quality assessment could work in addition to organized proficiency testing schemes.

Objectives Interference from isomeric steroids is a potential cause of disparity between mass spectrometry-based 17-hydroxyprogesterone (17OHP) results. We aimed to assess the proficiency of mass spectrometry laboratories to report 17OHP in the presence of known isomeric steroids. Methods A series of five samples were prepared using a previously demonstrated commutable approach. These samples included a control (spiked to 15.0 nmol/L 17OHP) and four challenge samples further enriched with equimolar concentrations of 17OHP isomers (11α-hydroxyprogesterone, 11β-hydroxyprogesterone, 16α-hydroxyprogesterone or 21-hydroxyprogesterone). These samples were distributed to 38 participating laboratories that reported serum 17OHP results using mass spectrometry in two external quality assurance programs. The result for each challenge sample was compared to the control sample submitted by each participant. Results Twenty-six laboratories (68 % of distribution) across three continents returned results. Twenty-five laboratories used liquid chromatography-tandem mass spectrometry (LC-MS/MS), and one used gas chromatography-tandem mass spectrometry to measure 17OHP. The all-method median of the control sample was 14.3 nmol/L, ranging from 12.4 to 17.6 nmol/L. One laboratory had results that approached the lower limit of tolerance (minus 17.7 % of the control sample), suggesting the isomeric steroid caused an irregular result. Conclusions Most participating laboratories demonstrated their ability to reliably measure 17OHP in the presence of the four clinically relevant isomeric steroids. The performance of the 12 (32 %) laboratories that did not engage in this activity remains unclear. We recommend that all laboratories offering LC-MS/MS analysis of 17OHP in serum, plasma, or dried bloodspots determine that the isomeric steroids are appropriately separated.

Objectives Primary aldosteronism is the most common cause of endocrine hypertension and is associated with significant cardiovascular morbidities. The diagnostic workup depends on determinations of plasma aldosterone and renin which are highly variable and associated with false-positive and false-negative results. Quantification of aldosterone in 24 h urine may provide more reliable results, but the methodology is not well established. We aimed to establish an assay for urinary aldosterone and related steroids with suitability for clinical routine implementation. Methods Here, we report on the development and validation of a quantitative LC-MS/MS method for six urinary steroids: aldosterone, cortisol, 18-hydroxycorticosterone, 18-hydroxycortisol, 18-oxocortisol, tetrahydroaldosterone. After enzymatic deconjugation, total steroids were extracted using SepPak tC18 plates and quantified in positive electrospray ionization mode on a QTRAP 6500+ mass spectrometer. Results Excellent linearity was demonstrated with R 2 >0.998 for all analytes. Extraction recoveries were 89.8–98.4 % and intra- and inter-day coefficients of variations were <6.4 and <9.0 %, establishing superb precision. Patients with primary aldosteronism (n=10) had higher mean 24 h excretions of aldosterone-related metabolites than normotensive volunteers (n=20): 3.91 (95 % CI 2.27–5.55) vs. 1.92 (1.16–2.68) µmol/mol for aldosterone/creatinine, 2.57 (1.49–3.66) vs. 0.79 (0.48–1.10) µmol/mol for 18-hydroxycorticosterone/creatinine, 37.4 (13.59–61.2) vs. 11.61 (10.24–12.98) µmol/mol for 18-hydroxycortisol/creatinine, 1.56 (0.34–2.78) vs. 0.13 (0.09–0.17) µmol/mol for 18-oxocortisol/creatinine, and 21.5 (13.4–29.6) vs. 7.21 (4.88–9.54) µmol/mol for tetrahydroaldosterone/creatinine. Conclusions The reported assay is robust and suitable for routine clinical use. First results in patient samples, though promising, require clinical validation in a larger sample set.

Objectives Free light chain (FLC) assays and the ratio of κ/λ are recommended for diagnosis, prognosis and monitoring of plasma cell dyscrasias (PCD). Limited data exists on FLC clinical specificity in patients diagnosed with other conditions. Methods We assessed the κ, λ, and κ/λ FLC ratio using the FreeLite assay and the Sebia FLC ELISA assay in 176 patients with clinical presentations of fatigue, anemia, polyclonal hypergammaglobulinemia, joint disorders, kidney disease and non PCD-cancers with no monoclonal protein observed on serum protein electrophoresis or MASS-FIX immunoglobulin isotyping. Manufacturer defined reference intervals (RI) and glomerular filtration rate (GFR) specific RI (renal RI) were utilized. Results For the κ/λ ratio, 68.7 % (121/176) of specimens on the FreeLite and 87.5 % (154/176) of specimens on the Sebia assay were within RI. For κ, 68.2 % (120/176) and 72.2 % (127/176) of results were outside RI for FreeLite and Sebia respectively. For λ, 37.5 % (66/176) and 84.1 % (148/176) of FreeLite and Sebia results were outside RI. With FreeLite and Sebia, patients with kidney disease (n=25) had the highest κ/λ ratios. 44 patients (25.0 %) had GFR <60 mL/min/BSA. When renal RI were applied, 13.6 % had a FLCr outside the renal RI with FreeLite, and 4.5 % with Sebia. Conclusions In a cohort of patients with signs and symptoms suggestive of PCDs, but ultimately diagnosed with other conditions, Sebia FLC had improved clinical specificity relative to FreeLite, if one was using an abnormal κ/λ ratio as a surrogate for monoclonality.

Objectives Severe deficiency of growth hormone (GHD) of the newborn is a rare but potentially life-threatening disease. GH measured during the first week of life, using dried blood spots (DBS), may offer several advantages. Aim of the study was to estimate the reference values for GH in newborns by a new analytical method using DBS. Methods Using a new developed analytical method, GH was estimated from DBS of 1,036 healthy newborns attending the Neonatology Unit of Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico of Milan in the period July–October 2021. Reference values for GH deficiency were estimated by the Harrell–Davis bootstrap method, with 90 %CI calculated by the bias-corrected and accelerated bootstrap method. Results All GH measurements required 33 analytical sessions (8 months) with a CV% for calibration curve slopes equal to 6.9 %. Intermediate precision evaluated by measurement of low (3 μg/L) and high (10 μg/L) quality controls was, respectively, 14 and 6.5 %. GH reference values, estimated at percentiles 1.0st, 2.5th and 5.0th, and their 90 %CI, were, respectively, 4.5 μg/L (90 %CI 3.8–5.1), 5.9 μg/L (90 %CI 5.4–6.4) and 7.0 μg/L (90 %CI 6.7–7.3). GH levels were not associated with sex, standard deviation scores, birth weight, gestational age, type of delivery or mother’s variables (age, smoking habit, gestational diabetes). Conclusions Validation data suggest that this method can be used to measured GH in newborns using DBS. The reference values estimated in this study are in accordance with previous published works using ELISA and may help confirming the clinical suspicion of neonatal GHD.

Objectives The aim of the present study was to establish the population- and laboratory-specific reference intervals (RIs) for the Slovenian adult population for 24 trace elements (TEs) in blood, plasma and erythrocytes and to evaluate the impact of gender, age, seafood consumption, smoking habits and amalgam fillings on TEs levels. Methods TEs (Mn, Co, Cu, Zn, Se and Mo, Li, Be, V, Cr, Ni, Ga, As, Rb, Sr, Ag, Cd, Sn, Cs, Au, Hg, Tl, Pb and U) were determined in 192 a priori selected blood donors (107 women and 85 men, aged 18–65 years), using inductively coupled plasma mass spectrometry (ICP-MS) with the Octopole Reaction System. Participants filled out a questionnaire, and RIs were established according to the Clinical and Laboratory Standards Institute (CLSI) guidelines for TEs. Results Uniform RIs for non-essential and gender-specific for essential TEs in blood, plasma and erythrocytes were established. In our population, higher blood and plasma Cu, and erythrocyte Mn levels in women were found. In men, blood Zn, plasma Zn, Mn and Se, and erythrocyte Cu levels were higher. Zn levels were higher in 30–39 years age group. Pb and Sr increased with age. Smoking positively affected Cd, Pb, Cs and Rb; seafood consumption increased As, Hg and Zn; and amalgam increased Hg, Ag and Cu levels. Conclusions Essential TEs were inside recommended levels, and the non-essential ones were far below critical levels. Established RIs will provide an important foundation for clinical diagnostics, safety erythrocyte transfusions assessment, toxicology and epidemiological studies.

Objectives White blood cell (WBC)-related flags are essential for detecting abnormal cells including blasts in automated hematology analyzers (AHAs). Cell population data (CPD) may characterize each WBC population, and customized CPD rules can be also useful for detecting blasts. We evaluated the performance of WBC-related flags, customized CPD rules, and their combination for detecting blasts on the Beckman Coulter DxH 900 AHA (DxH 900, Beckman Coulter, Miami, Florida, USA). Methods In a total of 239 samples from patients with hematologic diseases, complete blood count on DxH 900 and manual slide review (MSR) were conducted. The sensitivity, specificity, and efficiency of the five WBC-related flags, nine customized CPD rules, and their combination were evaluated for detecting blasts, in comparison with MSR. Results Blasts were detected by MSR in 40 out of 239 (16.7 %) samples. The combination of flags and CPD rules showed the highest sensitivity compared with each of flags and CPD rules for detecting blasts (97.5 vs. 72.5 % vs. 92.5 %). Compared with any flag, the combination of flags and CPD rules significantly reduced false-negative samples from 11 to one for detecting blasts (27.5 vs. 2.5 %, p=0.002). Conclusions This is the first study that evaluated the performance of both flags and CPD rules on DxH 900. The customized CPD rules as well as the combination of flags and CPD rules outperformed WBC-related flags for detecting blasts on DxH 900. The customized CPD rules can play a complementary role for improving the capability of blast detection on DxH 900.

Objectives In this study, we investigated the role of several circulating and drainage fluid biomarkers for detecting postoperative complications (PCs) and anastomotic leakage (AL) in patients undergoing colorectal surgery. Methods All consecutive patients undergoing colorectal surgery between June 2018 and April 2020 were prospectively considered. On postoperative days (POD) 1, 3, and 5, we measured lactate dehydrogenase (LDH) in drainage fluid, C-reactive protein (CRP) in serum and drainage fluid, and neutrophil to lymphocyte ratio (NLR). Results We enrolled 187 patients. POD1 patients with AL had higher serum CRP levels, while on POD3 and on POD5 higher NLR and serum CRP. LDH and CRP in drainage fluid were also significantly higher at both time points. The area under the curves (AUCs) of serum and drainage fluid CRP were 0.752 (0.629–0.875) and 0.752 (0.565–0.939), respectively. The best cut-off for serum and drainage fluid CRP was 185.23 and 76 mg/dL, respectively. The AUC of NLR on POD3 was 0.762 (0.662–0.882) with a sensitivity and specificity of 84 and 63 %, respectively, at a cut-off of 6,6. Finally, drainage fluid LDH showed the best diagnostic performance for AL, with an AUC, sensitivity, and specificity of 0.921 (0.849–0.993), 82 %, and 90 % at a cut-off of 2,186 U/L. Trends in serum parameters between patients with or without PCs or AL were also evaluated. Interestingly, we found that NLR decreased faster in patients without PCs than in patients with PCs and patients with AL. Conclusions Drainage fluid LDH and NLR could be promising biomarkers of PCs and AL.

Objectives To evaluate the analytical characteristics of a novel high-sensitivity cardiac troponin T (hs-cTnT) test on the automatic light-initiated chemiluminescent assay (LiCA ® ) system, and validated its diagnostic performance for non-ST-segment elevation myocardial infarction (NSTEMI). Methods Studies included an extensive analytical evaluation and established the 99th percentile upper reference limit (URL) from apparently healthy individuals, followed by a diagnostic performance validation for NSTEMI. Results Sex-specific 99th percentile URLs were 16.0 ng/L (1.7 % CV: coefficient of variation) for men (21–92 years) and 13.4 ng/L (2.0 % CV) for women (23–87 years) in serum, and 30.6 ng/L (0.9 % CV) for men (18–87 years) and 20.2 ng/L (1.4 % CV) for women (18–88 years) in heparin plasma. Detection rates in healthy individuals ranged from 98.9 to 100 %. An excellent agreement was identified between LiCA ® and Elecsys ® assays with a correlation coefficient of 0.993 and mean bias of −0.7 % (−1.8–0.4 %) across the full measuring range, while the correlation coefficient and overall bias were 0.967 and −1.1 % (−2.5–0.3 %) for the lower levels of cTnT (10–100 ng/L), respectively. At the specific medical decision levels (14.0 and 52.0 ng/L), assay difference was estimated to be <5.0 %. No significant difference was found between these two assays in terms of area under curve (AUC), sensitivity and specificity, negative predictive value (NPV) and positive predictive value (PPV) for the diagnosis of NSTEMI. Conclusions LiCA ® hs-cTnT is a reliable 3rd-generation (level 4) high-sensitivity assay for detecting cardiac troponin T. The assay is acceptable for practical use in the diagnosis of NSTEMI.

Objectives To explore the metabolic fingerprints of diabetic retinopathy (DR) in individuals with type 2 diabetes using a newly-developed laser desorption/ionization mass spectrometry (LDI-MS) platform assisted by ferric particles. Methods Metabolic fingerprinting was performed using a ferric particle-assisted LDI-MS platform. A nested population-based case-control study was performed on 216 DR cases and 216 control individuals with type 2 diabetes. Results DR cases and control individuals with type 2 diabetes were comparable for a list of clinical factors. The newly-developed LDI-MS platform allowed us to draw the blueprint of plasma metabolic fingerprints from participants with and without DR. The neural network afforded diagnostic performance with an average area under curve value of 0.928 for discovery cohort and 0.905 for validation cohort (95 % confidence interval: 0.902–0.954 and 0.845–0.965, respectively). Tandem MS and Fourier transform ion cyclotron resonance MS with ultrahigh resolution identified seven specific metabolites that were significantly associated with DR in fully adjusted models. Of these metabolites, dihydrobiopterin, phosphoserine, N-arachidonoylglycine, and 3-methylhistamine levels in plasma were first reported to show the associations. Conclusions This work advances the design of metabolic analysis for DR and holds the potential to promise as an efficient tool for clinical management of DR.

Objectives Sepsis is a life-threatening condition implicating an inadequate activation of the immune system. Platelets act as modulators and contributors to immune processes. Indeed, altered platelet turnover, thrombotic events, and changes in thrombopoietin levels in systemic inflammation have been reported, but thrombopoietin-levels in sepsis and septic-shock have not yet been systematically evaluated. We therefore performed a meta-analysis of thrombopoietin (TPO)-levels in patients with sepsis. Methods Two independent reviewers screened records and full-text articles for inclusion. Scientific databases were searched for studies examining thrombopoietin levels in adult sepsis and septic-shock patients until August 1st 2022. Results Of 95 items screened, six studies met the inclusion criteria, including 598 subjects. Both sepsis and severe sepsis were associated with increased levels of thrombopoietin (sepsis vs. control: standardized mean difference 3.06, 95 % CI 1.35–4.77; Z=3.50, p=0.0005) (sepsis vs. severe sepsis: standardized mean difference −1.67, 95 % CI −2.46 to −0.88; Z=4.14, p<0.0001). TPO-levels did not show significant differences between severe sepsis and septic shock patients but differed between sepsis and inflammation-associated non-septic controls. Overall, high heterogeneity and low sample size could be noted. Conclusions Concluding, increased levels of thrombopoietin appear to be present both in sepsis and severe sepsis with high heterogeneity but thrombopoietin does not allow to differentiate between severe sepsis and septic-shock. TPO may potentially serve to differentiate sepsis from non-septic trauma and/or tissue damage related (systemic) inflammation. Usage of different assays and high heterogeneity demand standardization of methods and further large multicenter trials.

Objectives Thermostability is one of the pre-requisites for the reliability of analytes in clinical practice and biomedical research. Although presepsin represents a promising new biomarker for the early diagnosis of sepsis in newborns, data on its stability under different storage conditions are lacking. We aimed to investigate presepsin thermostability in blood, urine and saliva samples after thawing at 4 predetermined monitoring time-points in a cohort of preterm and term infants. Methods We conducted an observational study, where each case served as its own control, in 24 preterm and term infants. Blood, urine and saliva samples were stored at −80 °C for 18 months, and presepsin measured in different biological fluids at thawing (T0), 24 (T1), 48 (T2) and at 72 (T3) hours after thawing. Results No significant differences (p>0.05, for all) in presepsin levels were observed at T0–T3 in the different biological fluids. Furthermore, no differences at T0–T3 were observed in presepsin levels between blood and saliva fluids, whilst urine levels were significantly higher (p<0.05, for all) than blood and saliva at T0–T3. Conclusions Results on presepsin pre-analytical thermo-stability in different biological fluids after long-term refrigeration support the reliability of this biomarker in the diagnosis and monitoring of perinatal sepsis.