Biological Variation Data in Triathletes for Metabolism and Growth-Related Biomarkers Included in the Athlete Biological Passport.

BACKGROUND: When using biological variation (BV) data, BV estimates need to be robust and representative. High-endurance athletes represent a population under special physiological conditions, which could influence BV estimates. Our study aimed to estimate BV in athletes for metabolism and growth-related biomarkers involved in the Athlete Biological Passport (ABP), by 2 different statistical models. METHODS: Thirty triathletes were sampled monthly for 11 months. The samples were analyzed for human growth hormone (hGH), insulin-like growth factor-1 (IGF-1), insulin-like growth factor binding protein 3 (IGFBP-3), insulin, and N-terminal propeptide of type III procollagen (P-III-NP) by immunoassay. Bayesian and ANOVA methods were applied to estimate within-subject (CVI) and between-subject BV. RESULTS: CVI estimates ranged from 7.8% for IGFBP-3 to 27.0% for insulin, when derived by the Bayesian method. The 2 models gave similar results, except for P-III-NP. Data were heterogeneously distributed for P-III-NP for the overall population and in females for IGF-1 and IGFBP-3. BV components were not estimated for hGH due to lack of steady state. The index of individuality was below 0.6 for all measurands, except for insulin. CONCLUSIONS: In an athlete population, to apply a common CVI for insulin would be appropriate, but for IGF-1 and IGFBP-3 gender-specific estimates should be applied. P-III-NP data were heterogeneously distributed and using a mean CVI may not be representative for the population. The high degree of individuality for IGF-1, IGFBP-3, and P-III-NP makes them good candidates to be interpreted through reference change values and the ABP.

The influence of undetected hemolysis on POCT potassium results in the emergency department.

OBJECTIVES: This study aimed to evaluate discrepancies in potassium measurements between point-of-care testing (POCT) and central laboratory (CL) methods, focusing on the impact of hemolysis on these measurements and its impact in the clinical practice in the emergency department (ED). METHODS: A retrospective analysis was conducted using data from three European university hospitals: Technische Universitat Munchen (Germany), Hospital Universitario La Paz (Spain), and Erasmus University Medical Center (The Netherlands). The study compared POCT potassium measurements in EDs with CL measurements. Data normalization was performed in categories for potassium levels (kalemia) and hemolysis. The severity of discrepancies between POCT and CL potassium measurements was assessed using the reference change value (RCV). RESULTS: The study identified significant discrepancies in potassium between POCT and CL methods. In comparing POCT normo- and mild hypokalemia against CL results, differences of -4.20 % and +4.88 % were noted respectively. The largest variance in the CL was a +4.14 % difference in the mild hyperkalemia category. Additionally, the RCV was calculated to quantify the severity of discrepancies between paired potassium measurements from POCT and CL methods. The overall hemolysis characteristics, as defined by the hemolysis gradient, showed considerable variation between the testing sites, significantly affecting the reliability of potassium measurements in POCT. CONCLUSIONS: The study highlighted the challenges in achieving consistent potassium measurement results between POCT and CL methods, particularly in the presence of hemolysis. It emphasised the need for integrated hemolysis detection systems in future blood gas analysis devices to minimise discrepancies and ensure accurate POCT results.

Long-Term Within- and Between-Subject Biological Variation Data of Hematological Parameters in Recreational Endurance Athletes.

BACKGROUND: Hematological parameters have many applications in athletes, from monitoring health to uncovering blood doping. This study aimed to deliver biological variation (BV) estimates for 9 hematological parameters by a Biological Variation Data Critical Appraisal Checklist (BIVAC) design in a population of recreational endurance athletes and to assess the effect of self-reported exercise and health-related variables on BV. METHODS: Samples were drawn from 30 triathletes monthly for 11 months and measured in duplicate for hematological measurands on an Advia 2120 analyzer (Siemens Healthineers). After outlier and homogeneity analysis, within-subject (CVI) and between-subject (CVG) BV estimates were delivered (CV-ANOVA and log-ANOVA, respectively) and a linear mixed model was applied to analyze the effect of exercise and other related variables on the BV estimates. RESULTS: CVI estimates ranged from 1.3% (95%CI, 1.2-1.4) for mean corpuscular volume to 23.8% (95%CI, 21.6-26.3) for reticulocytes. Sex differences were observed for platelets and OFF-score. The CVI estimates were higher than those reported for the general population based on meta-analysis of eligible studies in the European Biological Variation Database, but 95%CI overlapped, except for reticulocytes, 23.9% (95%CI, 21.6-26.5) and 9.7% (95%CI, 6.4-11.0), respectively. Factors related to exercise and athletes' state of health did not appear to influence the BV estimates. CONCLUSIONS: This is the first BIVAC-compliant study delivering BV estimates that can be applied to athlete populations performing high-level aerobic exercise. CVI estimates of most parameters were similar to the general population and were not influenced by exercise or athletes' state of health.

Failure Mode and Effects Analysis (FMEA) at the preanalytical phase for POCT blood gas analysis: proposal for a shared proactive risk analysis model.

OBJECTIVES: Proposal of a risk analysis model to diminish negative impact on patient care by preanalytical errors in blood gas analysis (BGA). METHODS: Here we designed a Failure Mode and Effects Analysis (FMEA) risk assessment template for BGA, based on literature references and expertise of an international team of laboratory and clinical health care professionals. RESULTS: The FMEA identifies pre-analytical process steps, errors that may occur whilst performing BGA (potential failure mode), possible consequences (potential failure effect) and preventive/corrective actions (current controls). Probability of failure occurrence (OCC), severity of failure (SEV) and probability of failure detection (DET) are scored per potential failure mode. OCC and DET depend on test setting and patient population e.g., they differ in primary community health centres as compared to secondary community hospitals and third line university or specialized hospitals. OCC and DET also differ between stand-alone and networked instruments, manual and automated patient identification, and whether results are automatically transmitted to the patient's electronic health record. The risk priority number (RPN = SEV × OCC × DET) can be applied to determine the sequence in which risks are addressed. RPN can be recalculated after implementing changes to decrease OCC and/or increase DET. Key performance indicators are also proposed to evaluate changes. CONCLUSIONS: This FMEA model will help health care professionals manage and minimize the risk of preanalytical errors in BGA.

Screening Protocol and Prevalence of Venous Thromboembolic Disease in Hospitalized Patients With COVID-19.

BACKGROUND: SARS-CoV-2 disease (COVID-19) induces endothelial damage and sustained hypoxia and facilitates immobilization as factors of hypercoagulability. OBJECTIVES: The objective of our study was to assess the prevalence of venous thromboembolic disease (VTD) in COVID-19 patients and the usefulness of VTD screening based on age-adjusted D-dimer and point-of-care ultrasound (POCUS). PATIENTS/METHODS: We conducted a single cohort, prospective observational study in 102 consecutive hospitalized patients. RESULTS: A total of 102 POCUS and 39 pulmonary computed tomography angiography (PCTA) were performed diagnosing 27 VTD (26.5%): 17 deep vein thrombosis (DVT) (16.6% positive POCUS) and 18 pulmonary embolism (PE) (46.2% positive PCTA). COVID-19 patients with VTD were older (P < .030), had higher D-dimer (P < .001), higher International Society on Thrombosis and Hemostasis score (P < .001), and higher mortality (P = .025). However, there were no differences in inflammatory laboratory parameters neither in the cytokine storm syndrome (CSS) development. The ROC curve for D-dimer showed an AUC of 0.91. We have evidenced that patients with D-dimer between 2000 and 6000 ng/mL could benefit from a screening strategy with POCUS given the high sensitivity and specificity of the test. Furthermore, patients with D-dimer ≥6000 ng/mL should undergo POCUS and PCTA to rule out DVT and PE, respectively. CONCLUSIONS: In our cohort, 26.5% of the patients presented VTD. Screening strategy based on age-adjusted D-dimer and POCUS proved high sensitivity and specificity. Future trials focused on screening strategies are necessary to early detect the presence of DVT and PE and determine thromboprophylaxis strategies in patients with COVID-19.

ANN-Based Discernment of Septic and Inflammatory Synovial Fluid: A Novel Method Using Viscosity Data from a QCR Sensor.

The synovial fluid (SF) analysis involves a series of chemical and physical studies that allow opportune diagnosing of septic, inflammatory, non-inflammatory, and other pathologies in joints. Among the variety of analyses to be performed on the synovial fluid, the study of viscosity can help distinguish between these conditions, since this property is affected in pathological cases. The problem with viscosity measurement is that it usually requires a large sample volume, or the necessary instrumentation is bulky and expensive. This study compares the viscosity of normal synovial fluid samples with samples with infectious and inflammatory pathologies and classifies them using an ANN (Artificial Neural Network). For this purpose, a low-cost, portable QCR-based sensor (10 MHz) was used to measure the viscous responses of the samples by obtaining three parameters: Δf, ΔΓ (parameters associated with the viscoelastic properties of the fluid), and viscosity calculation. These values were used to train the algorithm. Different versions of the ANN were compared, along with other models, such as SVM and random forest. Thirty-three samples of SF were analyzed. Our study suggests that the viscosity characterized by our sensor can help distinguish infectious synovial fluid, and that implementation of ANN improves the accuracy of synovial fluid classification.

Optimised molecular genetic diagnostics of Fanconi anaemia by whole exome sequencing and functional studies.

PURPOSE: Patients with Fanconi anaemia (FA), a rare DNA repair genetic disease, exhibit chromosome fragility, bone marrow failure, malformations and cancer susceptibility. FA molecular diagnosis is challenging since FA is caused by point mutations and large deletions in 22 genes following three heritability patterns. To optimise FA patients' characterisation, we developed a simplified but effective methodology based on whole exome sequencing (WES) and functional studies. METHODS: 68 patients with FA were analysed by commercial WES services. Copy number variations were evaluated by sequencing data analysis with RStudio. To test FANCA missense variants, wt FANCA cDNA was cloned and variants were introduced by site-directed mutagenesis. Vectors were then tested for their ability to complement DNA repair defects of a FANCA-KO human cell line generated by TALEN technologies. RESULTS: We identified 93.3% of mutated alleles including large deletions. We determined the pathogenicity of three FANCA missense variants and demonstrated that two FANCA variants reported in mutations databases as 'affecting functions' are SNPs. Deep analysis of sequencing data revealed patients' true mutations, highlighting the importance of functional analysis. In one patient, no pathogenic variant could be identified in any of the 22 known FA genes, and in seven patients, only one deleterious variant could be identified (three patients each with FANCA and FANCD2 and one patient with FANCE mutations) CONCLUSION: WES and proper bioinformatics analysis are sufficient to effectively characterise patients with FA regardless of the rarity of their complementation group, type of mutations, mosaic condition and DNA source.

Classification, prevalence, and outcomes of anticancer therapy-induced cardiotoxicity: the CARDIOTOX registry.

AIM: Cardiotoxicity (CTox) is a major side effect of cancer therapies, but uniform diagnostic criteria to guide clinical and research practices are lacking. METHODS AND RESULTS: We prospectively studied 865 patients, aged 54.7 ± 13.9; 16.3% men, scheduled for anticancer therapy related with moderate/high CTox risk. Four groups of progressive myocardial damage/dysfunction were considered according to current guidelines: normal, normal biomarkers (high-sensitivity troponin T and N-terminal natriuretic pro-peptide), and left ventricular (LV) function; mild, abnormal biomarkers, and/or LV dysfunction (LVD) maintaining an LV ejection fraction (LVEF) ≥50%; moderate, LVD with LVEF 40-49%; and severe, LVD with LVEF ≤40% or symptomatic heart failure. Cardiotoxicity was defined as new or worsening of myocardial damage/ventricular function from baseline during follow-up. Patients were followed for a median of 24 months. Cardiotoxicity was identified in 37.5% patients during follow-up [95% confidence interval (CI) 34.22-40.8%], 31.6% with mild, 2.8% moderate, and 3.1% with severe myocardial damage/dysfunction. The mortality rate in the severe CTox group was 22.9 deaths per 100 patients-year vs. 2.3 deaths per 100 patients-year in the rest of groups, hazard ratio of 10.2 (95% CI 5.5-19.2) (P < 0.001). CONCLUSIONS: The majority of patients present objective data of myocardial injury/dysfunction during or after cancer therapy. Nevertheless, severe CTox, with a strong prognostic relationship, was comparatively rare. This should be reflected in protocols for clinical and research practices.

Multi-site performance evaluation and Sigma metrics of 20 assays on the Atellica chemistry and immunoassay analyzers.

Background The Atellica Solution comprises chemistry (CH) and immunoassay (IM) analyzers. Recently, six early adopter clinical laboratories across Europe evaluated the analytical performance of 20 CH and IM assays. To measure analytical performance quality, Sigma metrics were calculated for individual-site and pooled-site results. Methods Precision, detection capability, linearity, and method comparison studies were performed according to Clinical Laboratory Standards Institute protocols. Global Sigma metrics across sites were calculated from pooled data at the medical decision level using total allowable error (TEa) goals from CLIA for CH assays, and TEa goals from RiliBÄK for IM assays; and, the equation: Sigma metrics=%TEa-%bias/%CV. A pooled %CV was calculated by combining the imprecision obtained from individual sites. Bias calculations were performed against the ADVIA Chemistry system or ADVIA Centaur system using Deming regression analysis (Passing-Bablok regression for electrolytes) on the pooled-site data. The 103 individual-site Sigma metric calculations used individual-site imprecision and pooled-bias. Results The limits of blank and detection results agreed with the manufacturer's claims. Most assays were linear across the assay range tested. Pooled Sigma metrics were good or better (>4 Sigma) for 18 of 20 assays; and, acceptable for urea nitrogen (3.1) and sodium (3.9), the latter values attributable to higher imprecision at one of five sites. Conclusions Sigma metrics for data generated across multiple real-world sites evaluating the Atellica Solution demonstrated good or better performance of greater than 4 Sigma for 18 of 20 assays tested. Overall, results verified the manufacturer's claims that methods were fit for use in clinical laboratories.

Examination of Cause-of-Death Data Quality Among New York City Deaths Due to Cancer, Pneumonia, or Diabetes From 2010 to 2014.

The cause-of-death (COD) statement on the standard US death certificate is a valuable tool for public health practice, but its utility is impaired by reporting inaccuracies. To assess the quality of CODs reported in New York City, we developed and applied a quality measure to 3 leading CODs: cancer, pneumonia, and diabetes. The COD quality measure characterized 5 common issues with COD completion: nonspecific conditions as the underlying COD (UCOD); UCOD discrepancies; the presence of only 1 informative cause on the entire certificate; competing causes listed together on 1 line; and clinically improbable sequences. COD statements with more than 1 quality issue were defined as statements of "limited" quality. Of 82,116 deaths with cancer, diabetes, or pneumonia assigned as the UCOD in New York City from 2010 to 2014, 66.8% of pneumonia certificates were classified as "limited" quality as compared with 45.6% of cancer certificates and 32.3% of diabetes certificates. Forty percent of cancer certificates listed only 1 informative condition on the death certificate. Almost half of pneumonia certificates (45.9%) contained only enough information to assign International Classification of Diseases, Tenth Revision, code J18.9 ("unspecified pneumonia") as the UCOD, whereas most diabetes certificates contained UCOD discrepancies (25.2%). These limitations affect the quality of mortality data but may be reduced through quality improvement efforts.

N-linked glycosylation of protease-activated receptor-1 at extracellular loop 2 regulates G-protein signaling bias.

Protease-activated receptor-1 (PAR1) is a G-protein-coupled receptor (GPCR) for the coagulant protease thrombin. Similar to other GPCRs, PAR1 is promiscuous and couples to multiple heterotrimeric G-protein subtypes in the same cell and promotes diverse cellular responses. The molecular mechanism by which activation of a given GPCR with the same ligand permits coupling to multiple G-protein subtypes is unclear. Here, we report that N-linked glycosylation of PAR1 at extracellular loop 2 (ECL2) controls G12/13 versus Gq coupling specificity in response to thrombin stimulation. A PAR1 mutant deficient in glycosylation at ECL2 was more effective at stimulating Gq-mediated phosphoinositide signaling compared with glycosylated wildtype receptor. In contrast, wildtype PAR1 displayed a greater efficacy at G12/13-dependent RhoA activation compared with mutant receptor lacking glycosylation at ECL2. Endogenous PAR1 rendered deficient in glycosylation using tunicamycin, a glycoprotein synthesis inhibitor, also exhibited increased PI signaling and diminished RhoA activation opposite to native receptor. Remarkably, PAR1 wildtype and glycosylation-deficient mutant were equally effective at coupling to Gi and ß-arrestin-1. Consistent with preferential G12/13 coupling, thrombin-stimulated PAR1 wildtype strongly induced RhoA-mediated stress fiber formation compared with mutant receptor. In striking contrast, glycosylation-deficient PAR1 was more effective at increasing cellular proliferation, associated with Gq signaling, than wildtype receptor. These studies suggest that N-linked glycosylation at ECL2 contributes to the stabilization of an active PAR1 state that preferentially couples to G12/13 versus Gq and defines a previously unidentified function for N-linked glycosylation of GPCRs in regulating G-protein signaling bias.

Characterization of thrombin-bound dabigatran effects on protease-activated receptor-1 expression and signaling in vitro.

Thrombin, the key effector protease of the coagulation cascade, drives fibrin deposition and activates human platelets through protease-activated receptor-1 (PAR1). These processes are critical to the progression of thrombotic diseases. Thrombin is the main target of anticoagulant therapy, and major efforts have led to the discovery of new oral direct inhibitors of thrombin. Dabigatran is the first oral anticoagulant licensed for the prevention of thromboembolisms associated with orthopedic surgery and stroke prevention in atrial fibrillation. Dabigatran is a direct thrombin inhibitor that effectively blocks thrombin's catalytic activity but does not preclude thrombin's exosites and binding to fibrinogen. Thus, we hypothesized that catalytically inactive thrombin retains the capacity to bind to PAR1 through exosite-I and may modulate its function independent of receptor cleavage and activation. Here, we report that dabigatran at clinically relevant concentrations is an effective and acute inhibitor of thrombin-induced PAR1 cleavage, activation, internalization, and ß-arrestin recruitment in vitro. Interestingly, prolonged exposure to catalytic inactive thrombin incubated with dabigatran at 20-fold higher therapeutic concentration resulted in increased PAR1 cell-surface expression, which correlated with higher detectable levels of ubiquitinated receptor. These findings are consistent with ubiquitin function as a negative regulator of PAR1 constitutive internalization. Increased PAR1 expression also enhanced agonist-induced phosphoinositide hydrolysis and endothelial barrier permeability. Thus, catalytically inactive thrombin appears to modulate PAR1 function in vitro by stabilizing receptor cell-surface expression; but given the high clearance rate of thrombin, the high concentration of dabigatran required to achieve this effect the in vivo physiologic relevance is unknown.

Perioperative management of obstructive sleep apnea: a survey of Puerto Rico anesthesia providers.

BACKGROUND: Obstructive sleep apnea (OSA) prevalence has been increasing in the past years adding significant morbidity. Perioperative management is controversial and few studies have addressed this matter. The American Society of Anesthesiology (ASA) and the American Academy of Sleep Medicine (AASM) have developed clinical practice guidelines for the perioperative management of patients with OSA. Existing evidence suggest an increase in early postoperative complications in patients with OSA. Nevertheless, data about perioperative management of OSA is limited. To our knowledge, only two studies that address this matter, none in Puerto Rico. METHODS: A questionnaire was given to participants at the annual meeting of anesthesiology in Puerto Rico. The document was then anonymously deposited into sealed box. RESULTS: The response rate was 80 %. The awareness about written postoperative policy in patients with diagnosed (23 %) and suspected (11 %) OSA was low. If a written policy were available, 46 % of patients would have gone to ICU. The most important factor for final disposition was the degree of OSA, which was decided by surgery and anesthesia (69 %). In the last year, at least one complication related to OSA was observed in 20 % of respondents. The most common preoperative screening tool was the ASA guidelines. Seventy-two percent of respondents suggested a lack of institutional policies as the main reason for disparity. CONCLUSION: There is a significant heterogeneity in the current clinical practice. The main barriers identified to achieve current recommendations were lack of institutional policies, awareness of current guideline, formal training in management of OSA, and access to a sleep specialist.

Effect of cause-of-death training on agreement between hospital discharge diagnoses and cause of death reported, inpatient hospital deaths, New York City, 2008-2010.

INTRODUCTION: Accurate cause-of-death reporting is required for mortality data to validly inform public health programming and evaluation. Research demonstrates overreporting of heart disease on New York City death certificates. We describe changes in reported causes of death following a New York City health department training conducted in 2009 to improve accuracy of cause-of-death reporting at 8 hospitals. The objective of our study was to assess the degree to which death certificates citing heart disease as cause of death agreed with hospital discharge data and the degree to which training improved accuracy of reporting. METHODS: We analyzed 74,373 death certificates for 2008 through 2010 that were linked with hospital discharge records for New York City inpatient deaths and calculated the proportion of discordant deaths, that is, death certificates reporting an underlying cause of heart disease with no corresponding discharge record diagnosis. We also summarized top principal diagnoses among discordant reports and calculated the proportion of inpatient deaths reporting sepsis, a condition underreported in New York City, to assess whether documentation practices changed in response to clarifications made during the intervention. RESULTS: Citywide discordance between death certificates and discharge data decreased from 14.9% in 2008 to 9.6% in 2010 (P < .001), driven by a decrease in discordance at intervention hospitals (20.2% in 2008 to 8.9% in 2010; P < .001). At intervention hospitals, reporting of sepsis increased from 3.7% of inpatient deaths in 2008 to 20.6% in 2010 (P < .001). CONCLUSION: Overreporting of heart disease as cause of death declined at intervention hospitals, driving a citywide decline, and sepsis reporting practices changed in accordance with health department training. Researchers should consider the effect of overreporting and data-quality changes when analyzing New York City heart disease mortality trends. Other vital records jurisdictions should employ similar interventions to improve cause-of-death reporting and use linked discharge data to monitor data quality.

The network simulation method: a useful tool for locating the kinetic-thermodynamic switching point in complex kinetic schemes.

The kinetic-thermodynamic switching point of a multistep process, whose reaction mechanism has been elucidated by DFT calculations, can be calculated by means of an efficient model based on the Network Simulation Method (NSM). This method can solve, fast and effectively, a difficult system of differential equations derived from a complex kinetic scheme by establishing a formal equivalence between the chemical system and an electrical network. The NSM employs very short simulation times to determine the dependence of the switching time on the temperature, a fundamental topic to take control over the product composition which has not been treated exhaustively so far, and that could be applied for synthetic purposes avoiding laborious and costly experimental trials.

Understanding perinatal death: a systematic analysis of New York City fetal and neonatal death vital record data and implications for improvement, 2007-2011.

We aimed to compare demographic, medical, and cause-of-death information reported for third-trimester fetal and neonatal death vital records collected in New York City (NYC) before and after implementation of the revised fetal death certificate to identify: (1) the limitations of combining fetal and neonatal death records for the purpose of perinatal death prevention; and (2) improvement opportunities for fetal death vital records registration. Using Chi squared tests, we compared data completeness and cause-of-death information between third-trimester NYC fetal (n = 1,930) and neonatal deaths (n = 735) from 2007 to 2011. We also compared fetal death data before and after the 2011 implementation of the 2003 United States (US) Standard Report of Fetal Death and an electronic reporting system. Compared with neonatal deaths, fetal death data were generally less complete (P < 0.0001). Fetal death data much more frequently reported an ill-defined cause of death (67 vs. 5 %). Most ill-defined reported causes of fetal death (73 %) were attributed to stillbirth synonyms (e.g., "fetal demise"). Ill-defined causes of fetal death decreased from 68 to 61 % (P < 0.01) after 2011. Both data completeness and ill-defined causes of death varied widely by hospital. In NYC, fetal deaths lack demographic, medical, and cause-of-death information compared with neonatal deaths, with implications for research that uses combined perinatal mortality data sets. Electronic implementation of the US Standard Report of Fetal Death minimally improved cause-of-death information. Substantial variability by hospital suggests opportunities for improvement exist.

Test of an electronic program to query clinicians about nonspecific causes reported for pneumonia deaths, New York City, 2012.

We tested an electronic cause-of-death query system at a hospital in New York City to evaluate clinicians' reporting of cause of death. We used the system to query clinicians about all deaths assigned International Classification of Disease code J189 (pneumonia, unspecified) as the underlying cause of death. Of 29 death certificates that generated queries, 28 were updated with additional information, which led to revisions in the underlying cause of 27 deaths. The electronic system for querying reported cause of death was feasible and enabled quicker than usual responses; however, follow-up with clinicians to ensure timely, accurate, and complete responses was labor-intensive. Educating clinicians and enforcing reporting standards would reduce the time and effort required to ensure accurate and timely cause-of-death reporting.

Growth differentiation factor 15 and malnutrition in older adults.

OBJECTIVES: Growth differentiation factor 15 (GDF-15) levels increase due to systemic inflammation and chronic disease burden. Since these biological processes are pathogenic factors of malnutrition, we examined the prospective association between GDF-15 serum levels and subsequent malnutrition in older adults. METHODS: We used data from 723 women and 735 men aged ≥65 years [mean age (SD): 71.3 (4.18) years] participating in the Seniors-ENRICA-2 cohort, who were followed-up for 2.2 years. Malnutrition was assessed with the Mini Nutritional Assessment-Short form (MNA-SF), where a 12-14 score indicates normal nutritional status, an 8-11 score indicates at risk of malnutrition, and a 0-7 score malnutrition. Associations of GDF-15 and malnutrition were analyzed, separately in women and men, using linear and logistic regression and adjusted for the main potential confounders. RESULTS: The mean (SD) MNA-SF score at baseline was 13.2 (1.34) for women and 13.5 (1.13) for men. Incident malnutrition (combined endpoint "at risk of malnutrition or malnutrition") over 2.2 years was identified in 55 (9.7%) of women and 38 (5.4%) of men. In women, GDF-15 was linearly associated with a decrease in the MNA-SF score; mean differences (95% confidence interval) in the MNA-SF score were -0.07 (-0.13; -0.01) points per 25% increase in GDF-15, and -0.49 (-0.83; -0.16) for the highest versus lowest quartile of GDF-15. Also in women, GDF-15 was linearly associated with a higher malnutrition incidence, with odds ratio (95% confidence interval) of 1.24 (1.06; 1.46) per 25% increment in GDF-15 and of 3.05 (1.21; 7.65) for the highest versus lowest quartile of GDF-15. Results were similar after excluding subjects with cardiovascular disease and diabetes. No association of GDF-15 with changes in MNA score or malnutrition incidence was found in men. CONCLUSION: Higher serum GDF-15 concentrations are associated with worsening nutritional status in older women. Further studies should elucidate the reasons for the sex differences in this association and explore the therapeutic potential of modifying GDF-15 to prevent malnutrition.

Serum biomarkers for liver fibrosis assessment.

Liver fibrosis is the result of chronic liver injury of different etiologies produced by an imbalance between the synthesis and degeneration of the extracellular matrix and dysregulation of physiological mechanisms. Liver has a high regenerative capacity in the early stage of chronic diseases so a prompt liver fibrosis detection is important. Consequently, an easy and economic tool that could identify patients with liver fibrosis at the initial stages is needed. To achieve this, many non-invasive serum direct, such as hyaluronic acid or metalloproteases, and indirect biomarkers have been proposed to evaluate liver fibrosis. Also, there have been developed formulas that combine these biomarkers, some of them also introduce clinical and/or demographic parameters, like FIB-4, non-alcoholic fatty liver disease fibrosis score (NFS), enhance liver fibrosis (ELF) or Hepamet fibrosis score (HFS). In this manuscript we critically reviewed different serum biomarkers and formulas for their utility in the diagnosis and progression of liver fibrosis.

Use of point-of-care glucometers during an oral glucose tolerance test in children for prediabetes and diabetes diagnosis: a comparison study.

Objectives: Despite clinical guidelines do not recommend the use of point-of-care testing (POCT) glucometers for diagnostic purposes yet, the analytical performance is continuously improving. Thus, we evaluate the technical accuracy and clinical concordance of POCT glucometers during an oral glucose tolerance test (OGTT) in children for prediabetes and diabetes diagnosis in a comparison study. Methods: Pediatric patients with an OGTT indication who attended the Diabetes Unit between December 2020 and September 2021 were recruited for this prospective observational study. During the functional test, glycaemia was immediately measured in venous blood using two glucometers (unconnected and connected) and sent to the central laboratory. Results: The study included 98 patients. There was a high correlation between the glucometers and the central laboratory (Pearson correlation coefficient=0.912 and 0.950, for unconnected and connected glucometer, respectively). The median OGTT turnaround time (TAT) was significantly decreased (connected glucometer: 2.02 h [interquartile range, 2.00-2.07], central laboratory: 11.63 h [6.09-25.80]), with similar overall cost. The diagnostic concordance between connected glucometer and the central laboratory was 71.1 % (95 % confidence interval (CI) 61.5-79.2). The clinical decision would have been the same in the 92.8 % of the cases, but treatment would have not been indicated in 4 patients (4.1 %). Conclusions: POCT glucometers have demonstrated a high correlation and an acceptable diagnostic concordance with the central laboratory during an OGTT, as well the connected device offers a significant decrease in TAT, without increasing costs. However, as severe clinical impact could happen, POCT glucometers may not be used for diagnosis yet.