Abstract
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.
Abstract Background It is unknown whether growth differentiation factor 15 (GDF-15) is associated with chronic musculoskeletal pain (CMP) and whether or not its association with incident ...cardiovascular disease (CVD) changes according to CMP status. Methods 1,957 randomly-selected adults aged ≥65 years without prior CVD were followed up between 2015-2023. CMP was classified according to its intensity, frequency, and interference with daily activities. The association between GDF-15 levels and CMP was assessed using linear models with progressive inclusion of potential confounders, whereas the association between GDF-15 and CVD risk was evaluated with Cox-proportional hazard models with similar adjustment and interaction terms between GDF-15 and CMP. The incremental predictive performance of GDF-15 over standard predictors was evaluated using discrimination and risk reclassification metrics. Results GDF-15 concentrations were 6.90% (95%CI:2.56;11.25) higher in individuals with CMP, and up to 8.89% (4.07;15.71) and 15.79% (8.43;23.16) higher in those with ≥3 CMP locations and interfering pain. These increased levels were influenced by a higher prevalence of cardiometabolic risk factors, functional impairments, depressive symptoms, and greater levels of inflammation in individuals with CMP. In fully-adjusted models, a two-fold increase in GDF-15 was associated with a with a 1.49 increased risk (95%CI: 1.08; 2.05) of a CVD event in individuals with CMP, but not among those without CMP 1.02 (0.77; 1.35); p-interaction 0.041. Adding GDF-15 to models including the Framingham Risk Score improved predictive performance among individuals with CMP. Conclusions We provide evidence that GDF-15 could serve as a biomarker to assess CMP, as well as to predict CVD incidence in individuals with CMP.
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.
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.
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.
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.
Hyponatraemia is the most common body fluid disorders but often goes unnoticed. Our laboratory incorporated a standardised procedure to help clinicians detect moderate/severe hyponatraemia. The study ...aims were to evaluate the outcomes on patient care and clinicians' satisfaction.
The study, observational and retrospective, included 1839 cases, adult and paediatric patients, with sodium concentration <130 mmol/L. The procedure consisted of interpretative comments in the emergency and core laboratories report and the point-of-care testing blood gas network report. We evaluated hyponatraemia length in two equal periods: before and after the implementation. We conducted a survey addressed to the staff of the clinical settings involved to know their satisfaction.
The median hyponatraemia length decreased significantly from 4.95 hours (2.08-16.57) in the first period to 2.17 hours (1.06-5.39) in the second period. The lack of hyponatraemia patients follow-up was significantly less after the procedure implementation. The survey was answered by 92 (60 senior specialists and 32 residents) out of 110 clinicians surveyed. Ninety of them (98%) answered positively.
We have demonstrated the reduction in the time for diagnosing and management by physicians, the higher uniformity in the time required to solve hyponatraemia episodes following our laboratory procedure and the clinicians' satisfaction.
Proposal of a risk analysis model to diminish negative impact on patient care by preanalytical errors in blood gas analysis (BGA).
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.
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.
This FMEA model will help health care professionals manage and minimize the risk of preanalytical errors in BGA.
Cardiovascular diseases (CVD) continue to be the main cause of death in our country. Adequate control of lipid metabolism disorders is a key challenge in cardiovascular prevention that is far from ...being achieved in real clinical practice. There is a great heterogeneity in the reports of lipid metabolism from Spanish clinical laboratories, which may contribute to its poor control. For this reason, a working group of the main scientific societies involved in the care of patients at vascular risk, has prepared this document with a consensus proposal on the determination of the basic lipid profile in cardiovascular prevention, recommendations for its realization and unification of criteria to incorporate the lipid control goals appropriate to the vascular risk of the patients in the laboratory reports.
Cardiovascular diseases (CVD) continue to be the main cause of death in our country. Adequate control of lipid metabolism disorders is a key challenge in cardiovascular prevention that is far from ...being achieved in real clinical practice. There is a great heterogeneity in the reports of lipid metabolism from Spanish clinical laboratories, which may contribute to its poor control. For this reason, a working group of the main scientific societies involved in the care of patients at vascular risk, has prepared this document with a consensus proposal on the determination of the basic lipid profile in cardiovascular prevention, recommendations for its realization and unification of criteria to incorporate the lipid control goals appropriate to the vascular risk of the patients in the laboratory reports.
Statins have been proposed as potentially useful agents for modulating the host response in COVID-19. However, solid evidence-based recommendations are still lacking. Our aim was to study the ...association between statin use and clinical outcomes in a large cohort of hospitalized patients with SARS-CoV-2 infection, as well as the specific consequences of chronic treatment withdrawal during hospital admission.
Retrospective observational study including 2191 hospitalized patients with confirmed SARS-CoV-2 infection.
Mean age was 68.0±17.8 years and 597 (27.3%) patients died during follow-up. A total of 827 patients (37.7% of the whole sample), received chronic treatment with statins. Even though they underwent more frequent admissions in critical care units, chronic treatment with statins was not independently associated with all-cause mortality HR 0.95 (0.72-1.25). During the whole hospital admission, 371 patients (16.9%) received at least one dose of statin. Although these patients had a significantly worse clinical profile, both treatment with statins during admission HR 1.03 (0.78-1.35) and withdrawal of chronic statin treatment HR 1.01 (0.78-1.30) showed a neutral effect in mortality. However, patients treated with statins presented more frequently hepatic cytolysis, rhabdomyolysis and thrombotic/hemorrhagic events.
In this large cohort of hospitalized COVID-19 patients, statins were not independently associated with all-cause mortality during follow-up. Clinically relevant statin-associated adverse effects should be carefully monitored during hospital admission.
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