Stability of Whole Blood Electrolyte Specimens at Room Temperature vs. Slushed Ice Conditions

A physio-chemical mathematical model of the effects of blood analysis delay on acid-base, metabolite and electrolyte status: evaluation in blood from critical care patients

OBJECTIVES

Measurements of acid-base status are performed quickly after blood sampling avoiding errors. This necessitates rapid sample transport which can be problematic. This study measures blood sampled in critically ill patients over 180 min and proposes a mathematical physio-chemical model to simulate changes.

METHODS

Eleven blood samples were taken from 30 critically ill patients and measured at baseline (2 samples) and 36, 54, 72, 90, 108, 126, 144, 162, and 180 min. A mathematical model was proposed including red blood cell metabolism, carbon dioxide diffusion, electrolyte distribution and water transport. This model was used to simulate values of plasma pH, pCO2, pO2, SO2, glucose, lactate, Na+ and Cl- during analysis delay. Simulated and measured values were compared using Bland-Altman and correlation analysis, and goodness of model fits evaluated with chi-squared.

RESULTS

The mathematical model provided a good fit to data in 29 of 30 patients with no significant differences (p>0.1) between simulated and measured plasma values. Differences were (bias±SD): pH 0.000 ± 0.012, pCO2 0.00 ± 0.24 kPa, lactate -0.10 ± 0.23 mmol/L, glucose 0.00 ± 0.34 mmol/L, Cl- -0.2 ± 1.21 mmol/L, Na+ 0.0 ± 1.0 mmol/L, pO2 0.0 ± 0.44 kPa, SO2 -0.6 ± 5.5 %, with these values close to manufacturers' measurement errors. All linear correlations had R2>0.86. Simulations of pH, PCO2, glucose and lactate could be performed from baseline values without patient specific parameters.

CONCLUSIONS

This paper illustrates that analysis delay can be accurately simulated with a mathematical model of physio-chemistry. While further evaluation is necessary, this may indicate a role for this model in clinical practice to simulate analysis delay.

Acid-base parameters in venous blood - agreement between values from safePICO syringes and lithium-heparin vacutainer tubes

Venous blood is considered an acceptable alternative to arterial blood for assessment of metabolic acid-base disorders. Also, venous sampling using lithium-heparin (Li-Hep) tubes is advantageous to arterial sampling using PICO syringes, the risk of complications being lower. Usage of partly filled tubes without firm knowledge about the clinical consequences is, however, a pre-analytic consideration. The study evaluated primary acid-base parameters (pH, standardized hydrogen carbonate (HCO3), standardized base excess (SBE), lactate) and co-determined parameters in venous blood stored at room temperature up to 60 min in Li-Hep tubes vs. venous blood in PICO syringes analyzed immediately. Also, 50% filled tubes stored up to 30 min were compared to filled tubes analyzed immediately. Significant differences were generally observed. Stability was parameter and time dependent (filled tubes: 30 min: pH, (preferably 15 min for optimal stability), SBE, potassium and lactate, 60 min: HCO3, hemoglobin, methemoglobin (MetHb), carbon monoxide hemoglobin (COHb), sodium, chloride, glucose and creatinine; 50% filled tubes: 15 min: lactate, 30 min: HCO3, hemoglobin, MetHb, COHb, potassium, sodium, chloride, glucose and creatinine). In conclusion, storage in filled Li-Hep tubes for 30 min generates comparable results to blood in PICO syringes for all parameters, except pCO2, pO2 and sO2. Storage in 50% filled Li-Hep tubes is not acceptable for pH, pCO2, pO2, sO2 and SBE, and lactate is only stable for 15 min.

The stability of 65 biochemistry analytes in plasma, serum, and whole blood

OBJECTIVES

The pre-analytical stability of various biochemical analytes requires careful consideration, as it can lead to the release of erroneous laboratory results. There is currently significant variability in the literature regarding the pre-analytical stability of various analytes. The aim of this study was to determine the pre-analytical stability of 65 analytes in whole blood, serum and plasma using a standardized approach.

METHODS

Blood samples were collected from 30 healthy volunteers (10 volunteers per analyte) into five vacutainers; either SST, Li-heparin, K2-EDTA, or Na-fluoride/K-oxalate. Several conditions were tested, including delayed centrifugation with storage of whole blood at room temperature (RT) for 8 h, delayed centrifugation with storage of whole blood at RT or 4 °C for 24 h, and immediate centrifugation with storage of plasma or serum at RT for 24 h. Percent deviation (% PD) from baseline was calculated for each analyte and compared to the maximum permissible instability (MPI) derived from intra- and inter-individual biological variation.

RESULTS

The majority of the analytes evaluated remained stable across all vacutainer types, temperatures, and timepoints tested. Glucose, potassium, and aspartate aminotransferase, among others, were significantly impacted by delayed centrifugation, having been found to be unstable in whole blood specimens stored at room temperature for 8 h.

CONCLUSIONS

The data presented provides insight into the pre-analytical variables that impact the stability of routine biochemical analytes. This study may help to reduce the frequency of erroneous laboratory results released due to exceeded stability and reduce unnecessary repeat phlebotomy for analytes that remain stable despite delayed processing.

Application of neural network and nomogram for the prediction of risk factors for bone mineral density abnormalities: A cross-sectional NHANES-based survey

Background

The risk of bone mineral density abnormalities is inconsistent between eastern and western regions owing to differences in ethnicity and dietary habits. A diet comprising carbohydrates and dietary fiber is not the common daily diet of the American population. Thus far, no studies have assessed the risk of bone mineral density abnormalities in the American population, and no predictive model has considered the intake of carbohydrates, dietary fiber, and coffee, as well as levels of various electrolytes for assessing bone mineral density abnormalities, especially in the elderly. This study conducted a neural network analysis and established a predictive nomogram considering an unusual diet to determine risk factors for bone mineral density abnormalities in the American population, mainly to provide a reference for the prevention and treatment of related bone mineral density abnormalities.

Methods

Overall, 9871 patients who had complete data were selected from the National Health and Nutrition Examination Survey database during 2017-2020 as the research object, and patients' general clinical characteristics were compared. Neural networks and nomograms were analyzed to screen for and quantify risk factors for bone mineral density abnormalities. Finally, the receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis (DCA), and community indifference curve (CIC) were constructed to comprehensively verify the accuracy, differential ability, and clinical practicability of the neural network and nomogram.

Results

The important risk factors for bone mineral density abnormalities were caffeine intake, carbohydrate consumption, body mass index (BMI), height, blood sodium, blood calcium, blood phosphorus, blood potassium, dietary fiber, vitamin D, participant age, weight, race, family history, and sex. The nomogram revealed that caffeine intake, carbohydrate consumption, blood potassium, and age were positively correlated with bone mineral density abnormalities, whereas BMI, height, blood phosphate, dietary fiber, and blood sodium were negatively correlated with bone mineral density abnormalities. Women were more prone to these abnormalities than men. The area under the ROC curve values of the neural network and nomogram were 85.8 % and 77.7 %, respectively. The Youden index was 58.04 % and 41.87 %, respectively. The detection sensitivity was 75.73 % and 65.06 %, respectively, and the specificity was 82.31 % and 76.81 %, respectively. Calibration curves of the neural network and nomogram showed better discrimination ability from the standard curve (P > 0.05). DCA and CIC analyses showed that the application of the neural network and nomogram to explore risk factors for bone mineral density abnormalities had certain clinical practicability, and the overall predictive effect of the model was good.

Conclusion

The outcomes of the neural network and nomogram analyses suggested that diet structure and electrolyte changes are important significant risk factors for bone mineral density abnormalities, especially with increasing carbohydrate and caffeine intake and decreasing dietary fiber intake. The established model can also provide a reference for future risk prediction.

The stability of blood gases and CO-oximetry under slushed ice and room temperature conditions

OBJECTIVES

Human blood gas stability data is limited to small sample sizes and questionable statistical techniques. We sought to determine the stability of blood gases under room temperature and slushed iced conditions in patients using survival analyses.

METHODS

Whole blood samples from ∼200 patients were stored in plastic syringes and kept at room temperature (22-24 °C) or in slushed ice (0.1-0.2 °C) before analysis. Arterial and venous pO2 (15-150 mmHg), pCO2 (16-72 mmHg), pH (6.73-7.52), and the CO-oximetry panel [total hemoglobin (5.4-19.3 g/dL), percentages of oxyhemoglobin (O2Hb%, 20-99%), carboxyhemoglobin (COHb, 0.1-5.4%) and methemoglobin (MetHb, 0.2-4.6%)], were measured over 5-time points. The Royal College of Pathologists of Australasia's (RCPA's) criteria determined analyte instability. Survival analyses identified storage times at which 5% of the samples for various analytes became unstable.

RESULTS

COHb and MetHb were stable up to 3 h in slushed ice and at room temperature; pCO2, pH was stable at room temperature for about 60 min and 3 h in slushed ice. Slushed ice shortened the storage time before pO2 became unstable (from 40 to 20 min), and the instability increased when baseline pO2 was ≥60 mmHg. The storage time for pO2, pCO2, pH, and CO-oximetry, when measured together, were limited by the pO2.

CONCLUSIONS

When assessing pO2 in plastic syringes, samples kept in slushed ice harm their stability. For simplicity's sake, the data support storage times for blood gas and CO-oximetry panels of up to 40 min at room temperature if following RCPA guidelines.

Impact of storage temperature and time before analysis on electrolytes (Na+, K+, Ca2+), lactate, glucose, blood gases (pH, pO2, pCO2), tHb, O2Hb, COHb and MetHb results

OBJECTIVES

The objective of our study is to evaluate the effect of storage temperature and time to analysis on arterial blood gas parameters in order to extend the CLSI recommendations.

METHODS

Stability of 12 parameters (pH, pCO₂, pO₂, Na+, K+, Ca2+, glucose, lactate, hemoglobin, oxyhemoglobin, carboxyhemoglobin, methemoglobin) measured by GEM PREMIER™ 5000 blood gas analyzer was studied at room temperature and at +4 °C (52 patients). The storage times were 30, 45, 60, 90 and 120 min. Stability was evaluated on the difference from baseline, the difference from the analyte-specific measurement uncertainty applied to the baseline value, and the impact of the variation on the clinical interpretation.

RESULTS

At room temperature, all parameters except the lactate remained stable for at least 60 min. A statistically significant difference was observed for pH at T45 and T60 and for pCO2 at T60 without modification of clinical interpretation. For lactate, clinical interpretation was modified from T45 and values were outside the range of acceptability defined by the measurement uncertainty. All parameters except pO2 remained stable for at least 120 min at +4 °C.

CONCLUSIONS

A one-hour transport at room temperature is compatible with the performance of all the analyses studied except lactate. If the delay exceeds 30 min, the sample should be placed at +4 °C for lactate measurement. If the samples are stored in ice, it is important to note that the pO2 cannot be interpreted.

Preanalytic Methodological Considerations and Sample Quality Control of Circulating miRNAs

As miRNAs emerge as potential circulating biomarkers for the diagnosis or prognosis of a wide variety of diseases, the quantification of miRNA necessitates careful preanalytic considerations and sample quality control becomes crucial. This study comprehensively analyzed the profiles of 356 miRNAs by quantitative RT-PCR in various blood sample types, with various processing protocols. The comprehensive analysis investigated the correlations of individual miRNAs with certain confounding factors. On the basis of these profiles, a panel of 7 miRNAs was established for the quality control of samples corresponding to hemolysis and platelet contamination. The panel was used to investigate the confounding impacts based on the size of the blood collection tube, the centrifugation protocol, post-freeze-thaw spinning, and whole blood storage. A standard dual-spin workflow for the processing of blood had been established for optimal sample quality. The real-time stability of 356 miRNAs was also investigated with demonstration of the temperature and time-induced miRNA degradation profile. Stability-related miRNAs were identified from real-time stability study and further incorporated into the quality control panel. This quality control panel enables the assessment of sample quality for more robust and reliable detection of circulating miRNAs.