Plasma lipids paediatric reference intervals: Indirect estimation using a large 14-year database.

OBJECTIVES: Establishing direct reference intervals (RIs) for paediatric patients is a very challenging endeavour. Indirect RIs can address this problem, using existing clinical laboratory databases from real-world data research. Compared to the traditional direct method, the indirect approach is highly practical, widely applicable, and low-cost. Considering the relevance of dyslipidemia in the paediatric age, to provide better laboratory services to the local paediatric population, we established population-specific lipid RIs via data mining. METHODS: Our laboratory information system was searched for cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL) and high-density lipoprotein (HDL) of patients aged less than 18 years, performed from January 2009 until December 2022. RIs were estimated using RefineR algorithm. RESULTS: Values from 215,594 patients were initially collected. After refining data on the basis of specific exclusion criteria that left 17,933 patients, we determined the RIs for each analyte, including corresponding 95% confidence interval (95% CI). Age and sex partitions were required for proper stratification of the heterogenous subpopulations. Age-related variations in TC and TG values were observed mainly in children until 5 years. RIs were defined for children less than 3 years and for those of 3-18 years. In our population, the obtained RIs were comparable with those of the literature, but the upper TG limit in subjects under the age of 3 (2.03 mmol/L with 95% CI: 1.45-2.86) was lower than that previously reported. CONCLUSIONS: Our RIs, necessary for paediatric lipid monitoring, are tailored to the serviced patient population as should be done whenever possible.

Risk of SARS-CoV-2 Reinfection in Children Within the 12 Months Following Mild COVID-19: Insights From a Survey Study.

Understanding the correlation between immune response and protection from COVID-19 will play a pivotal role in predicting the effectiveness of vaccines in children. We studied SARS-CoV-2 reinfection risk in children 12 months post-mild COVID-19. Children under 5 years old exhibited lower reinfection risk than older infected or vaccinated siblings during 12 months postimmunization.

Clinical and Analytical Performance of ELISA Salivary Serologic Assay to Detect SARS-CoV-2 IgG in Children and Adults.

Saliva is a promising matrix with several purposes. Our aim is to verify if salivary anti-SARS-CoV-2 antibody determination is suitable for monitoring immune responses. One hundred eighty-seven subjects were enrolled at University-Hospital Padova: 105 females (56.1%) and 82 males (43.9%), 95 (50.8%) children and 92 (49.2%) adults. Subjects self-collected saliva using Salivette; nineteen subjects collected three different samples within the day. A serum sample was obtained for all individuals. The N/S anti-SARS-CoV-2 salivary IgG (sal-IgG) and serum anti-SARS-CoV-2 S-RBD IgG (ser-IgG) were used for determining anti-SARS-CoV-2 antibodies. The mean (min-max) age was 9.0 (1-18) for children and 42.5 (20-61) for adults. Of 187 samples, 63 were negative for sal-IgG (33.7%), while 7 were negative for ser-IgG (3.7%). Spearman's correlation was 0.56 (p < 0.001). Sal-IgG and ser-IgG levels were correlated with age but not with gender, comorbidities, prolonged therapy, previous SARS-CoV-2 infection, or time from last COVID-19 infection/vaccination. The repeatability ranged from 23.8% (7.4 kAU/L) to 4.0% (3.77 kAU/L). The linearity of the assay was missed in 4/6 samples. No significant intrasubject differences were observed in sal-IgG across samples collected at different time points. Sal-IgG has good agreement with ser-IgG. Noninvasive saliva collection represents an alternative method for antibody measurement, especially in children.

Machine learning-based nonlinear regression-adjusted real-time quality control modeling: a multi-center study.

OBJECTIVES: Patient-based real-time quality control (PBRTQC), a laboratory tool for monitoring the performance of the testing process, has gained increasing attention in recent years. It has been questioned for its generalizability among analytes, instruments, laboratories, and hospitals in real-world settings. Our purpose was to build a machine learning, nonlinear regression-adjusted, patient-based real-time quality control (mNL-PBRTQC) with wide application. METHODS: Using computer simulation, artificial biases were added to patient population data of 10 measurands. An mNL-PBRTQC was created using eight hospital laboratory databases as a training set and validated by three other hospitals' independent patient datasets. Three different Patient-based models were compared on these datasets, the IFCC PBRTQC model, linear regression-adjusted real-time quality control (L-RARTQC), and the mNL-PBRTQC model. RESULTS: Our study showed that in the three independent test data sets, mNL-PBRTQC outperformed the IFCC PBRTQC and L-RARTQC for all measurands and all biases. Using platelets as an example, it was found that for 20 % bias, both positive and negative, the uncertainty of error detection for mNL-PBRTQC was smallest at the median and maximum values. CONCLUSIONS: mNL-PBRTQC is a robust machine learning framework, allowing accurate error detection, especially for analytes that demonstrate instability and for detecting small biases.

Analytical and clinical evaluations of SNIBE Maglumi chemiluminescent immunoassay for the detection of SARS-CoV-2 antigen in salivary samples.

OBJECTIVES: In this study, we describe the analytical and clinical performances of the SNIBE Maglumi SARS-CoV-2 antigen fully-automated chemiluminescent immunoassay (MAG-CLIA) on salivary samples. METHODS: Limit of detection (LOD), linearity and precision were tested for values close to or below the declared LOD. Clinical performance of MAG-CLIA was evaluated on leftover salivary samples from the healthcare workers (HCW) surveillance program, at the University-Hospital of Padova. Salivary samples were analyzed by Lumipulse G SARS-CoV-2 Ag, and in case where the values exceeded 0.41 ng/L, further testing was conducted using TaqPathTM COVID-19 RT-PCR (Applied Biosystems, Thermo Fisher Scientific). RESULTS: The estimated MAG-CLIA LOD was 3 ng/L, with repeatability of 7.5 %. Good linearity was demonstrated by diluting two samples at 52.7 ng/L and 211.4 ng/L. Of the 228 HCW samples, 59/228 (25.9 %) were positive, 169/228 (74.1 %) were negative. MAG-CLIA SARS-CoV-2 sAg median level (and interquartile range [IQR]) was 5.03 ng/L (<0.001-35.8 ng/L) for positive and <0.001 ng/L (<0.001 ng/L) for negative samples. MAG-CLIA AUC was 0.795 (95 % CI: 0.720-0.871). Using the best cut-off, 3.5 ng/L, sensitivity and specificity were 57.1 % (95 % CI: 42.2-71.2 %) and 97.0 % (95 % CI: 93.2-99.0 %), respectively. The agreement with the molecular assay was 88.1 % (Cohen's kappa 0.606 [SE=0.066, p<0.001]). CONCLUSIONS: The analytical performances of MAG-CLIA are satisfactory, also when values below LOD were tested. In saliva samples, although specificity was elevated, clinical performance was not comparable with that on nasopharyngeal swabs (NPS).

Stronger and durable SARS-CoV-2 immune response to mRNA vaccines in 5-11 years old children with prior COVID-19.

BACKGROUND AND OBJECTIVES: mRNA vaccines elicit a durable humoral response to SARS-CoV-2 in adults, whereas evidence in children is scarce. This study aimed to assess the early and long-term immune response to the mRNA vaccine in children with or without previous SARS-CoV-2 infection. METHODS: In a multicentre prospective observational study, we profiled the immune response to the Pfizer BioNTech (BNT162b2) vaccine in 5-11-year-old children attending the University Pediatric Hospital of Padua and Bambino-Gesù Hospital in Rome (Italy) from December-2021 to February-2023. Blood samples were collected pre-, 1-, and 6-months after vaccination. Neutralizing antibodies (NAbs) and anti-spike-receptor-binding-domain (anti-S-RBD) IgG titers were analyzed through Plaque Reduction Neutralization Test (PRNT) and chemiluminescent immune-enzymatic assay (CLIA), respectively. Immune cell phenotypes were analyzed by flow cytometry. RESULTS: Sixty children (26 [43 %] female, median age = 8 years [IQR = 7-10.7]) were enrolled in the study, including 46 children with a laboratory-confirmed previous COVID-19 (SARS-CoV-2-recovered) and 14 SARS-CoV-2-naïve participants defined as the absence of antigen-specific antibodies before vaccination. SARS-CoV-2-recovered participants recorded higher anti-S-RBD IgG and Wild-type and Omicron BA.2 NAbs titers than SARS-CoV-2-naïve participants at both 1- and 6-months after vaccination. Antibody titers correlated with T (Tregs) and B (Bregs) regulatory cell frequencies in SARS-CoV-2-recovered children. Both SARS-CoV-2-recovered and SARS-CoV-2-naïve participants decreased antibody titers by approximately 100 to 250 % from 1 to 6 months. While children with immunocompromising underlying conditions developed immune responses comparable to those of healthy children, solid organ transplant recipients exhibited lower levels of NAbs and anti-S-RBD IgG titers, as well as reduced frequencies of Tregs and Bregs. CONCLUSIONS: mRNA vaccination triggered a higher production of specific anti-SARS-CoV-2 antibodies along with increased levels of regulatory cells in children with previous SARS-CoV-2 infection up to the following 6 months. These findings provide insights into boosting pre-existing immunity.

Machine learning algorithms in sepsis.

Sepsis remains a significant global health challenge due to its high mortality and morbidity, compounded by the difficulty of early detection given its variable clinical manifestations. The integration of machine learning (ML) into laboratory medicine for timely sepsis identification and outcome forecasting is an emerging field of interest. This comprehensive review assesses the current body of research on ML applications for sepsis within the realm of laboratory diagnostics, detailing both their strengths and shortcomings. An extensive literature search was performed by two independent investigators across PubMed and Scopus databases, employing the keywords "Sepsis," "Machine Learning," and "Laboratory" without publication date limitations, culminating in January 2023. Each selected study was meticulously evaluated for various aspects, including its design, intent (diagnostic or prognostic), clinical environment, demographics, sepsis criteria, data gathering period, and the scope and nature of features, in addition to the ML methodologies and their validation procedures. Out of 135 articles reviewed, 39 fulfilled the criteria for inclusion. Among these, the majority (30 studies) were focused on devising ML algorithms for diagnosis, fewer (8 studies) on prognosis, and one study addressed both aspects. The dissemination of these studies across an array of journals reflects the interdisciplinary engagement in the development of ML algorithms for sepsis. This analysis highlights the promising role of ML in the early diagnosis of sepsis while drawing attention to the need for uniformity in validating models and defining features, crucial steps for ensuring the reliability and practicality of ML in clinical setting.

Evaluation of a new molecular test for the detection of SARS-CoV-2 nucleic acid in salivary samples.

Background: Molecular testing is considered the gold standard for the detection of SARS-CoV-2. This study aimed to compare the performance of the P742H SARS-CoV-2 Nucleic Acid Multiplex Detection Kit in salivary samples, with respect to the 732HF Novel Coronavirus (2019-nCoV) Nucleic Acid Detection Kit and the TaqPath COVID-19 CEIVD RT-PCR Kit, used at University-Hospital of Padova, Italy. Methods: One hundred twenty-four salivary samples selfcollected by healthcare workers (HCW) during the screening program at University-Hospital of Padova, Italy, from Oct to Nov 2022, were included in the study. RNA extraction was performed by Viral DNA and RNA Extraction Kit (Technogenetics, Lodi, Italy) and amplification by P742H and 732HF (Technogenetics, Lodi, Italy). RNA was extracted using MagNa Pure 96 DNA and Viral NA Small Volume Kit (Roche, Switzerland) for TaqPath analysis (Thermo Fisher Scientific, USA).

Rising adoption of artificial intelligence in scientific publishing: evaluating the role, risks, and ethical implications in paper drafting and review process.

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.

The Safety of a High-Flow Nasal Cannula in Neuromuscular Disease Patients with Acute Respiratory Failure: A Retrospective Case-Series Study.

(1) Background: Although Non-Invasive Ventilation (NIV) is effective in preventing mortality and endotracheal intubation in patients with Acute Respiratory Failure (ARF) linked to a neuromuscular disorder, its efficacy can be affected by patient intolerance. A High-Flow Nasal Cannula (HFNC) appears to have a significant advantage over NIV as far as patient tolerance is concerned. The aim of the study was to investigate HFNC's safety profile in a group of consecutive Neuromuscular Disease (NMD) patients intolerant to NIV who were admitted to an Intermediate Respiratory Care Unit (IRCU) for ARF. (2) Methods: The clinical course of nine NMD patients intolerant to NIV and switched to HFNC was reported. HFNC was provided during daytime hours and NIV during the night-time to the NIV-intolerant patients. HFNC was utilized 24 h a day in those patients who were intolerant of even nocturnal NIV. (3) Results: HFNC was simple to use and it was well tolerated by all of the patients. Three out of nine patients experienced treatment failure, consisting of the need for ETI and/or death during their IRCU stay. The remaining 6 had a favorable outcome. Treatment failure was linked to the utilization of HFNC 24 h a day. (4) Conclusion: HFNC during the daytime hours, together with nocturnal NIV, seems to be a safe therapeutic approach for NMD patients with ARF. A round-the-clock use of HFNC tends to be linked to a high likelihood of failure.

Plasma Bile Acid Profiling and Modulation of Secreted Mucin 5AC in Cholangiocarcinoma.

Studies investigating the potential role of circulating bile acids (BAs) as diagnostic biomarkers for cholangiocarcinoma (CCA) are sparse and existing data do not adjust for confounding variables. Furthermore, the mechanism by which BAs affect the expression of the oncogenic mucin 5AC (MUC5AC) has never been investigated. We performed a case-control study to characterise the profile of circulating BAs in patients with CCA (n = 68) and benign biliary disease (BBD, n = 48) with a validated liquid chromatography-tandem mass spectrometry technique. Odd ratios (OR) for CCA associations were calculated with multivariable logistic regression models based on a directed acyclic graph structure learning algorithm. The most promising BAs were then tested in an in vitro study to investigate their interplay in modulating MUC5AC expression. The total concentration of BAs was markedly higher in patients with CCA compared with BBD controls and accompanied by a shift in BAs profile toward a higher proportion of primary conjugated BAs (OR = 1.50, CI: 1.14 to 1.96, p = 0.003), especially taurochenodeoxycholic acid (TCDCA, OR = 42.29, CI: 3.54 to 504.63, p = 0.003) after multiple adjustments. Western blot analysis of secreted MUC5AC in human primary cholangiocytes treated with primary conjugated BAs or with TCDCA alone allowed us to identify a novel 230 kDa isoform, possibly representing a post-translationally modified MUC5AC specie.

Clinical features of COVID-19 in Italian outpatient children and adolescents during Parental, Delta, and Omicron waves: a prospective, observational, cohort study.

Introduction: COVID-19 features changed with the Omicron variant of SARS-CoV-2 in adults. This study aims to describe COVID-19 symptoms in children and adolescents during the Parental, Delta, and Omicron eras. Methods: A single-centre, prospective observational study was conducted on individuals aged 0-20 years attending the University Hospital of Padua (Italy) from April 2020 to December 2022. COVID-19 cases were defined by positive SARS-CoV-2 molecular detection and/or serology; patient/family symptoms and virological positivity were considered to determine the infection onset. Variables were summarized and compared using appropriate tests of descriptive statistics. Results: A total of 509 cases [46% female, median age eight years (IQR: 4-12)] were studied. Three-hundred-eighty-seven (76%), 52 (10%), and 70 (14%) subjects experienced COVID-19 during the Parental, Delta, and Omicron waves, respectively. All subjects developed an asymptomatic/mild COVID-19. Overall, the most frequent symptoms were fever (47%) and rhinitis (21%), which showed a significant increasing incidence from the Parental to Omicron waves (p < 0.001). Conversely, diarrhea was most common during the pre-Omicron eras (p = 0.03). Stratifying symptoms according to the age group, fever, rhinitis, and skin rashes were observed more frequently among infants/toddlers; conversely, fatigue was more common in children older than five years. The duration of symptoms was similar across different SARS-CoV-2 variants of concern (VOCs); conversely, the number of symptoms varied according to the age group (p < 0.0001). Discussion: This study showed differences in COVID-19 clinical presentation among infants, children, and adolescents and confirmed Omicron infection is more likely to be associated with upper respiratory symptoms. However, further population-based studies are needed to support these findings. In addition, active surveillance will play a crucial role in assessing the disease severity of future VOCs.

Inflammation, Autoinflammation and Autoimmunity in Inflammatory Bowel Diseases.

In this review, the role of innate and adaptive immunity in the pathogenesis of inflammatory bowel diseases (IBD) is reported. In IBD, an altered innate immunity is often found, with increased Th17 and decreased Treg cells infiltrating the intestinal mucosa. An associated increase in inflammatory cytokines, such as IL-1 and TNF-α, and a decrease in anti-inflammatory cytokines, such as IL-10, concur in favoring the persistent inflammation of the gut mucosa. Autoinflammation is highlighted with insights in the role of inflammasomes, which activation by exogenous or endogenous triggers might be favored by mutations of NOD and NLRP proteins. Autoimmunity mechanisms also take place in IBD pathogenesis and in this context of a persistent immune stimulation by bacterial antigens and antigens derived from intestinal cells degradation, the adaptive immune response takes place and results in antibodies and autoantibodies production, a frequent finding in these diseases. Inflammation, autoinflammation and autoimmunity concur in altering the mucus layer and enhancing intestinal permeability, which sustains the vicious cycle of further mucosal inflammation.

Autoinflammatory Diseases and COVID-19 Vaccination: Analysis of SARS-CoV-2 Anti-S-RBD IgG Levels in a Cohort of Patients Receiving IL-1 Inhibitors.

The purpose of the study was to evaluate the antibody response after COVID-19 vaccination in patients affected by systemic autoinflammatory diseases (SAID) undertaking IL-1 inhibitors (IL-1i) compared to healthy vaccinated controls (HC). The course of COVID-19 in vaccinated patients on IL-1i was also assessed. The serological response was evaluated in SAID patients using the CLIA MAGLUMI TM 2000 Plus test after the first vaccination cycle and the booster dose. Fifty-four fully vaccinated healthcare workers were enrolled as HCs. GraphPad Prism 8 software was used for statistical analysis. All patients developed an adequate antibody response. No differences were observed between the antibody titers of patients on IL-1i and those not on IL-1i, either after the first vaccination cycle or the booster dose (p = 0.99), and to HC (p = 0.99). With increasing age, a decrease in antibody production was assessed after the second vaccine in SAID (r = 0.67, p = 0.0003). In general, 11.6% of SAID patients had COVID-19 after receiving vaccination. None of them developed severe disease or experienced flares of their autoinflammatory disease. In conclusion, patients receiving IL-1i develop an antibody response comparable to HC. No side effects after vaccination were observed; IL-1i was continued before and after injections to avoid flare-ups.

Tixagevimab/Cilgavimab as pre-exposure prophylaxis against SARS-CoV-2 in patients with hematological malignancies.

The approved combination of Tixagevimab/Cilgavimab has been shown to decrease the rate of symptomatic SARS-CoV-2 infection in patients at increased risk of inadequate response to vaccination. However, Tixagevimab/Cilgavimab was tested in a few studies that included patients with hematological malignancies, even if this population has shown an increased risk of unfavorable outcomes following infection (with high rates of hospitalization, intensive care unit admission, and mortality) and poor significant immunization following vaccines. We performed a real-life prospective cohort study to evaluate the rate of SARS-CoV-2 infection following pre-exposure prophylaxis with Tixagevimab/Cilgavimab in anti-spike seronegative patients compared to a cohort of seropositive patients who were observed or received a fourth vaccine dose. We recruited 103 patients with a mean age of 67 years: 35 (34%) received Tixagevimab/Cilgavimab and were followed from March 17, 2022, until November 15, 2022. After a median follow-up of 4.24 months, the 3-month cumulative incidence of infection was 20% versus 12% in the Tixagevimab/Cilgavimab and observation/vaccine groups respectively (HR 1.57; 95% CI: 0.65-3.56; p = 0.34). In this study, we report our experience with Tixagevimab/Cilgavimab and a tailored approach to SARS-CoV-2 infection prevention in patients with hematological malignancies during the SARS-CoV-2 omicron surge.

Artificial intelligence and laboratory data in rheumatic diseases.

Artificial intelligence (AI)-based medical technologies are rapidly evolving into actionable solutions for clinical practice. Machine learning (ML) algorithms can process increasing amounts of laboratory data such as gene expression immunophenotyping data and biomarkers. In recent years, the analysis of ML has become particularly useful for the study of complex chronic diseases, such as rheumatic diseases, heterogenous conditions with multiple triggers. Numerous studies have used ML to classify patients and improve diagnosis, to stratify the risk and determine disease subtypes, as well as to discover biomarkers and gene signatures. This review aims to provide examples of ML models for specific rheumatic diseases using laboratory data and some insights into relevant strengths and limitations. A better understanding and future application of these analytical strategies could facilitate the development of precision medicine for rheumatic patients.

Analytical evaluation of a GAD65 antibodies chemiluminescence immunoassay for CSF in neurological syndromes.

OBJECTIVES: Antibodies against glutamic acid decarboxylase isoform 65 (GAD-Ab) have been found in different severe neurological conditions associated with altered synthesis of γ-aminobutyric acid (GABA). Serum GAD-Ab can be found in up to 90 % of patients with type 1 diabetes mellitus (T1DM), mostly at relatively low concentrations, while high concentrations of GAD-ab are thought to be more frequently associate to a neurological condition, with levels 100-folds higher than those found in T1DM. Although CSF testing is recommended when suspecting a GAD-associated neurological syndrome, no commercial immunoassay is validated for this use and no cut-off is internationally recognized to support the diagnosis. METHODS: In this study we validated CSF testing of GAD-Ab on an automated chemiluminescence (CLIA) immunoassay that had previously shown good agreement with ELISA on serum. RESULTS: We tested 43 CSF from patients with typical GAD-associated neurological disorders and patients with other neurological conditions, identifying a clinical cut-off of 18 kIU/L that discriminated GAD-disease with an area under the curve (AUC) of 0.921. CLIA showed good analytical performances on repeatability and recovery tests in CSF and confirmed an excellent agreement with ELISA. CONCLUSIONS: GAD-Ab associated neurological disorders are rare but CSF testing for GAD-Ab is a common request for neurologists when suspecting an insidious autoimmune central nervous system disease. CLIA platforms are expected to be increasingly adopted in clinical laboratories due to their flexibility and reliability, therefore studies on decisional levels should be implemented for improving the interpretation and utilization of laboratory data.

Potentials and pitfalls of ChatGPT and natural-language artificial intelligence models for the understanding of laboratory medicine test results. An assessment by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Artificial Intelligence (WG-AI).

OBJECTIVES: ChatGPT, a tool based on natural language processing (NLP), is on everyone's mind, and several potential applications in healthcare have been already proposed. However, since the ability of this tool to interpret laboratory test results has not yet been tested, the EFLM Working group on Artificial Intelligence (WG-AI) has set itself the task of closing this gap with a systematic approach. METHODS: WG-AI members generated 10 simulated laboratory reports of common parameters, which were then passed to ChatGPT for interpretation, according to reference intervals (RI) and units, using an optimized prompt. The results were subsequently evaluated independently by all WG-AI members with respect to relevance, correctness, helpfulness and safety. RESULTS: ChatGPT recognized all laboratory tests, it could detect if they deviated from the RI and gave a test-by-test as well as an overall interpretation. The interpretations were rather superficial, not always correct, and, only in some cases, judged coherently. The magnitude of the deviation from the RI seldom plays a role in the interpretation of laboratory tests, and artificial intelligence (AI) did not make any meaningful suggestion regarding follow-up diagnostics or further procedures in general. CONCLUSIONS: ChatGPT in its current form, being not specifically trained on medical data or laboratory data in particular, may only be considered a tool capable of interpreting a laboratory report on a test-by-test basis at best, but not on the interpretation of an overall diagnostic picture. Future generations of similar AIs with medical ground truth training data might surely revolutionize current processes in healthcare, despite this implementation is not ready yet.

Seasonal variation and disease distribution of cytophagocytic mononuclear cells in synovial fluid: A medical record study.

Cytophagocytic mononuclear (CPM) cells, previously known as Reiter's cells, are macrophages containing apoptotic polymorphonuclear leucocytes. Although they can be found in synovial fluid (SF) from different arthropathies, their role remains unclear. This study was performed to determine the frequency and disease distribution of CPM cells in SF in a large cohort of patients with rheumatic diseases over a 12-year period. We also investigated the seasonal variation in their incidence. This record review study included the reports pertaining to SF analyses performed between January 2010 and December 2021. Data were retrieved from the charts of inpatients and outpatients at Rheumatology and Emergency Departments of Padova. The total number of SF samples containing CPM cells was 189: 69% was from patients with seronegative spondyloarthritis (SpA), thus indicating a strong association between CPM cells and SpA. SF samples containing CPM cells were predominantly inflammatory. Our analyses demonstrated a 6-month cyclical fluctuation in concentrations of CPM cells, with an increase in spring and autumn. The presence of CPM cells in SF might offer diagnostic insight into the definition of SpA. Further studies are warranted to ascertain the link between CPM cells and the apoptotic process, shedding light on the mechanisms leading to their formation.

SARS-CoV-2 specific T-cell humoral response assessment after COVID-19 vaccination using a rapid direct real-time PCR amplification.

OBJECTIVES: The SARS-CoV-2 immune response is mediated by both humoral and cellular immunity. In this study, SARS-CoV-2 specific cellular immunity was tested by a novel direct real-time PCR (dRT-PCR) assay, targeting mRNA of CXCL10, and compared with respect to an ELISA measuring interferon gamma (IFN-γ) release. METHODS: Whole blood (Li-He) and serum samples were collected from 92 healthcare workers (HCW), with three doses of homologous (Pfizer/BioNTech, n=74) or heterologous (Pfizer/BioNTech and Vaxzevria or Moderna, n=18) vaccinations. Li-He samples were incubated with SCV2 PANEL-1-T-ACTIVATION (Hyris srl, Lodi, Italy), or CoV-2 IGRA TUBE ELISA (Euroimmune, Lubeck, Germany). CXCL10 mRNA expression was analyzed by bCube/bApp (Hyris), while IFN-γ was evaluated by quant-T-Cell SARS-CoV-2 ELISA (Euroimmune). Anti-SARS-CoV-2 S-RBD IgG levels were measured in sera using a CLIA assay (Snibe, Shenzen, China). RESULTS: Imprecision of dRT-PCR assay was found to be satisfactory, and the two methods for measuring T cell immunity to SARS-CoV-2 peptides agreed in 82/87 (94.2%) of results. At qualitative dRT-PCR analyses, 81 subjects (93.2%) resulted as reactive to SARS-CoV-2 peptides, 3 (3.4%) were borderline and 3 were negative (3.4%). At univariate and multivariate analyses of quantitative dRT-PCR mRNA of CXCL10 and IFN-γ release results showed no difference between HCW with previous infection, homologous/heterologous vaccination, or demographical features. Anti-SARS-CoV-2 S-RBD IgG was associated with the previous infection and the time between the last vaccination or positivity. CONCLUSIONS: Direct RT-PCR appeared accurate for determining the presence or absence of immunoreactivity of SARS-CoV-2 specific T cells, especially when rapid analyses are required, such as for organ transplantation.