Cardiotoxicity (CTox) is a major side effect of cancer therapies, but uniform diagnostic criteria to guide clinical and research practices are lacking.
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).
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.
Celiac disease (CeD) is an autoimmune condition triggered by gluten in genetically predisposed individuals, affecting all ages. Intestinal permeability (IP) is crucial in the pathogenesis of CeD and ...it is primarily governed by tight junctions (TJs) that uphold the intestinal barrier's integrity. The protein zonulin plays a critical role in modulating the permeability of TJs having emerged as a potential non-invasive biomarker to study IP. The importance of this study lies in providing evidence for the usefulness of a non-invasive tool in the study of IP both at baseline and in the follow-up of paediatric patients with CeD. In this single-centre prospective observational study, we explored the correlation between faecal zonulin levels and others faecal and serum biomarkers for monitoring IP in CeD within the paediatric population. We also aimed to establish reference values for faecal zonulin in the paediatric population. We found that faecal zonulin and calprotectin values are higher at the onset of CeD compared with the control population. Specifically, the zonulin levels were 347.5 ng/mL as opposed to 177.7 ng/mL in the control population (
= 0.001), while calprotectin levels were 29.8 μg/g stool compared to 13.9 μg/g stool (
= 0.029). As the duration without gluten consumption increased, a significant reduction in faecal zonulin levels was observed in patients with CeD (348.5 ng/mL vs. 157.1 ng/mL;
= 0.002), along with a decrease in the prevalence of patients with vitamin D insufficiency (88.9% vs. 77.8%). We conclude that faecal zonulin concentrations were higher in the patients with active CeD compared with healthy individuals or those following a gluten-free diet (GFD). The significant decrease in their values over the duration of the GFD suggests the potential use of zonulin as an additional tool in monitoring adherence to a GFD.
* Context.--Point-of-care testing allows rapid analysis and short turnaround times. To the best of our knowledge, the present study assesses, for the first time, clinical, operative, and economic ...outcomes of point-of-care blood gas analysis in a nephrology department. Objective.--To evaluate the impact after implementing blood gas analysis in the nephrology department, considering clinical (differences in blood gas analysis results, critical results), operative (turnaround time, elapsed time between consecutive blood gas analysis, preanalytical errors), and economic (total cost per process) outcomes. Design.--A total amount of 3195 venous blood gas analyses from 688 patients of the nephrology department before and after point-of-care blood gas analyzer installation were included. Blood gas analysis results obtained by ABL90 FLEX PLUS were acquired from the laboratory information system. Statistical analyses were performed using SAS 9.3 software. Results.--During the point-of-care testing period, there was an increase in blood glucose levels and a decrease in pCO2, lactate, and sodium as well as fewer critical values (especially glucose and lactate). The turnaround time and the mean elapsed time were shorter. By the beginning of this period, the number of preanalytical errors increased; however, no statistically significant differences were found during year-long monitoring. Although there was an increase in the total number of blood gas analysis requests, the total cost per process decreased. Conclusions.--The implementation of a point-of-care blood gas analysis in a nephrology department has a positive impact on clinical, operative, and economic terms of patient care.
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.
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.
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.
Aims
To examine the association of alcohol consumption patterns with growth differentiation factor 15 (GDF‐15) in older drinkers, separately among individuals with cardiovascular disease ...(CVD)/diabetes and those without them, as GDF‐15 is a strong biomarker of chronic disease burden.
Design
Cross‐sectional study.
Setting
Population‐based study in Madrid (Spain).
Participants
A total of 2051 life‐time drinkers aged 65+ years included in the Seniors‐ENRICA‐2 study in 2015–17. Participants’ mean age was 71.4 years and 55.4% were men.
Measurements
According to their average life‐time alcohol intake, participants were classified as occasional (≤ 1.43 g/day), low‐risk (men: > 1.43–20 g/day; women: > 1.43–10 g/day), moderate‐risk (men: > 20–40 g/day; women: > 10–20 g/day) and high‐risk drinkers (men: > 40 g/day; women: > 20 g/day; or binge drinkers). We also ascertained wine preference (> 80% of alcohol derived from wine), drinking with meals and adherence to a Mediterranean drinking pattern (MDP) defined as low‐risk drinking, wine preference and one of the following: drinking only with meals; higher adherence to the Mediterranean diet; or any of these.
Findings
In participants without CVD/diabetes, GDF‐15 increased by 0.27% 95% confidence interval (CI) = 0.06%, 0.48% per 1 g/day increment in alcohol among high‐risk drinkers, but there was no clear evidence of association in those with lower intakes or in the overall group, or across categories of alcohol consumption status. Conversely, among those with CVD/diabetes, GDF‐15 rose by 0.19% (95% CI = 0.05%, 0.33%) per 1 g/day increment in the overall group and GDF‐15 was 26.89% (95% CI = 12.93%, 42.58%) higher in high‐risk versus low‐risk drinkers. Drinking with meals did not appear to be related to GDF‐15, but among those without CVD/diabetes, wine preference and adherence to the MDP were associated with lower GDF‐15, especially when combined with high adherence to the Mediterranean diet.
Conclusions
Among older life‐time drinkers in Madrid, Spain, high‐risk drinking was positively associated with growth differentiation factor 15 (a biomarker of chronic disease burden). There was inconclusive evidence of a beneficial association for low‐risk consumption.
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).
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).
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.
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.
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