Annals of Clinical Biochemistry: International Journal of Laboratory Medicine

Point of care (POC) tests may improve accessibility and reduce costs of blood tests including in prostate cancer. The Man Van project was a pilot designed to address health inequalities that affect prostate cancer with novel community-based targeting of high-risk groups on a mobile clinical unit.

The i-CHROMA-II™ POC machine is a quantitative assay for the measurement of total prostate specific antigen (PSA) from capillary blood using fluorescence immunoassay technology. Laboratory based Serum PSA testing was compared with capillary blood POC testing using the i-CHROMA-II™ to determine its accuracy and impact on clinical decision making on the Man Van.

28 men participated. The median age was 53 years (range 45–74). One POC test result was invalid. Nine POCT samples gave a result of <0.5 μg/L and were not included in the analysis. Of the remaining results (N = 18) the median PSA was 1.97 μg/L (range 0.54-31.22 μg/L). Using Lin’s Concordance Correlation Coefficient of Absolute Agreement gave a value of 0.392 (N = 17). A Bland-Altman plot showed a mean difference of 0.377 μg/L.

We report the first testing of PSA using the i-Chroma-II™ machine, and the first real-world mobile testing using any POC PSA test. Our study did not show correlation between the laboratory and i-Chroma-II™, although it did replicate the positive bias seen in previous studies. Further testing and refinement of POC tests may help to achieve the goal to developing reliable POC PSA tests.

Measurement of N-terminal pro-B-type natriuretic peptide (NT-proBNP) and left ventricular ejection fraction (LVEF) are used in diagnosing heart failure (HF). The main aim was to explore the correlation between NT-proBNP and LVEF.

Patient data for 14,962 patients were extracted from medical records and national registries and compiled in the Swedish DEMONSTRATE database. HF phenotype was categorized according to LVEF level: HF with reduced EF (≤40%, HFrEF); HF with mildly reduced EF (41–49%, HFmrEF); HF with preserved EF (≥50%, HFpEF). Spearman’s rank was employed for correlation analysis and ROC curves for discrimination and classification.

NT-proBNP correlated negatively with LVEF level (r = −0.40) and positively with age (r = 0.49), creatinine (r = 0.35), and cystatin C (r = 0.53). Individuals with an HF diagnosis were more likely to have higher NT-proBNP levels compared to those without. The association between NT-proBNP and LVEF remained statistically significant (P < .0001) also after adjusting for age and kidney function estimates (r = −0.20). NT-proBNP discriminated well between HFrEF (AUC = 0.80) and HFpEF (AUC = 0.78). In discriminating the presence of an HF diagnosis, NT-proBNP (AUC = 0.81) outperformed LVEF (AUC = 0.75). However, on an individual level the correlation between LVEF and NT-proBNP was modest.

NT-proBNP levels increase when LVEF deteriorates but with large inter-individual differences. Further research is needed, but these findings show potential in optimizing the use of LVEF with the aid of sequential analysis of NT-proBNP as a complementary diagnostic and prognostic tool to enhance assessment of cardiac function.

Phosphatidylethanol (PEth) is formed in erythrocyte membranes after alcohol consumption. When abstaining, the PEth level falls with a rate proportional to its concentration, and a short apparent PEth half-life supports abstinence. We here derive algorithms for calculating unbiased half-lives and confidence intervals (CIs).

PEth was measured using Acquity UPC2-MS/MS systems in clinical blood samples from out-patients. We identified 6989 individuals having taken two or more PEth samples within 28 days. One measurement pair was randomly selected from everyone. We derived methods for and calculated PEth half-lives and corresponding 95% CIs for exact, rounded, and truncated data, on closed form, Monte Carlo methods and No-U-turn sampling.

The peak of the PEth half-life was at 8.62 days. Peak PEth half-life was 8.72 days for men and 8.47 days for women (P = 0.028) and on age: 8.55 days for age 18–39 years, 8.56 for age 40–59 years and 8.87 for 60+ years (P = 0.026). PEth concentration did not significantly affect half-life. CIs on a closed form performed excellently on exact data, with misclassification of abstinence for 16 out of 6989 observations (0.23%). When rounding or truncating data, misclassification occurred using Monte Carlo methods in 104 (1.5%) and 127 (1.8%) of the observations and using closed form algorithms in 855 (12.2%) and 777 (11.1%).

Unbiased PEth half-lives and CIs can be calculated and put into use in laboratory information systems. Rounding or truncating data used for PEth half-life calculation widened CIs with misinterpretations of alcohol abstinence.

This study aimed to identify laboratory parameters that could optimize the PLASMIC score, thereby improving its diagnostic accuracy for thrombotic thrombocytopenic purpura (TTP).

We performed a retrospective analysis of 136 patients with suspected TTP who had available ADAMTS-13 activity measurements. Patients were stratified into two groups based on ADAMTS-13 activity: a TTP group (n = 49) and a non-TTP group (n = 87). Routine laboratory parameters—including hemoglobin (HGB), red blood cell distribution width-standard deviation (RDW-SD), mean corpuscular volume (MCV), platelet count (PLT), alanine aminotransferase (ALT), aspartate aminotransferase (AST), direct bilirubin (DBIL), indirect bilirubin (IBIL), lactate dehydrogenase (LDH), creatinine (CR), urea (UREA), international normalized ratio (INR), and D-dimer—were compared between groups. Statistically significant parameters were selected as candidate variables to refine the PLASMIC score. The diagnostic performance of the modified model was evaluated using receiver operating characteristic (ROC) curve analysis.

Six parameters—HGB, PLT, ALT, RDW-SD, IBIL, and LDH—demonstrated significant differences between TTP and non-TTP patients. Multivariate logistic regression identified RDW-SD, PLT, and LDH as independent predictors of TTP. Based on these findings, we revised the PLASMIC score by substituting MCV with RDW-SD. The modified model exhibited a higher area under the curve (AUC) (0.907 vs 0.817) while maintaining sensitivity (95.9%) and improving specificity (70.1% vs 65.9%) compared to the original.

The modified PLASMIC score model may improve diagnostic accuracy for TTP in similar patient populations, but requires external validation in diverse cohorts to confirm its broader utility.

Acidification of urine samples has long been used as a method of preservation to enhance analyte stability. However, there are inherent safety risks to staff and patients when acid preservatives are used. The Association of Laboratory Medicine National Audit Committee sought to assess urine acidification practices in NHS laboratories.

An 11 question survey was sent to all Association of Laboratory Medicine members for completion between 24th January 2023 and 24th February 2023 and data analysis performed using Microsoft Excel. For a variety of analytes, laboratories were asked to detail the type of recommended and accepted collection containers, whether 24 h and/or spot urine samples were accepted, if preservative was added to samples on receipt if not collected with preservative and the storage conditions for unpreserved samples.

69 laboratories responded. Safety information was provided to users by the majority of laboratories and 88% of laboratories would pH test samples prior to sending them to a referral laboratory if acidification was a prerequisite. Variation was noted in quoted time of sample stability when refrigerated. Laboratories provided answers about specific tests – sodium, potassium, osmolality, calcium, magnesium, phosphate, creatinine, Bence Jones protein, total protein, urate, citrate, oxalate, cysteine, catecholamines, metanephrines, 5-HIAA, VMA/HMMA, copper, amino acids, organics acids and glycosaminoglycans.

There is significant variation in the use of acid as a preservative for urine samples throughout NHS laboratories as well as historical requirements for urine acidification for certain analytes which evidence has indicated is no longer a requirement.

Laboratory test results are crucial for clinical decisions, but errors at any stage can compromise patient safety. Despite technological advances and quality systems, laboratory processes remain vulnerable, necessitating structured risk assessment. Limited research exists on integrating Failure Mode and Effects Analysis (FMEA) with Sigma metrics. This study addresses these gaps through a comprehensive risk assessment in a NABL-accredited tertiary care hospital laboratory.

A retrospective observational study was conducted over 2.5 years. FMEA was used to identify errors across all phases of the total testing process. Quarterly error rates were calculated, converted to defects per million (DPM), and expressed as Sigma metrics. Risk Priority Numbers (RPN = severity × detectability × frequency) were scored quarterly to prioritize failures. The effect of corrective actions was evaluated by comparing pre- and post-intervention Sigma values.

Across 10 quarters (five pre- and five post-intervention), 23 error types were identified. The highest RPNs (>20) were observed for haemolyzed samples, clotted samples, and non-intimation of critical values. Haemolyzed samples declined from 0.97% to 0.49% (ARR 0.48%; RR 0.51; 95% CI 0.47–0.55; P < .0001). Clotted samples reduced from 0.24% to 0.06% (ARR 0.18%; RR 0.24; 95% CI 0.20–0.29; P < .0001). Non-intimation of critical values decreased from 2.63% to 2.18% (RR 0.83; 95% CI 0.70–0.99; P = .065).

Integrating FMEA with Sigma metrics provides a robust framework for identifying, prioritizing, and reducing laboratory errors. Continuous monitoring and corrective action are essential to sustain improvements in laboratory quality and patient safety.