The prevalence of hemolysis – a survey using hemolysis index

Liu, Dan; Li, Yanxin; Huang, Yi

doi:10.1515/cclm-2016-0698

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…On the Roche Cobas and Siemens Vista platforms, this occurs when the 'hemolytic index' is higher than the allowed set value [8]. Hemolytic samples in itself are not rare and may occur in vitro in up to 1-10% of all samples due to pre-analytical factors related to blood drawing, specimen handling and storage, without any underlying disease [9]. However, extreme hemolysis is unlikely to be caused by preanalytical factors.…”

mentioning

confidence: 99%

Massive hemolysis due to Clostridium perfringens: a laboratory’s perspective

Smit

Helm

Bosma

et al. 2020

Clinical Chemistry and Laboratory Medicine (CCLM)

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mentioning

confidence: 99%

Massive hemolysis due to Clostridium perfringens: a laboratory’s perspective

Smit

Helm

Bosma

et al. 2020

Clinical Chemistry and Laboratory Medicine (CCLM)

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“…19 In a study on the hemolysis index, it was stated that the hemolysis rate of inpatient samples (5.61%) was significantly higher than that of outpatient samples (2.21%). 20 In this study, the inpatient group was the group with the second-highest rejected sample rate. In the rejected samples in the inpatient group, the highest rejected sample rate belongs to the biochemistry sample type.…”

Section: Discussionmentioning

confidence: 94%

Pre-analytical rejection rates of clinical samples based on patients’ health status

Keski̇n

Acı

2022

Baghdad J. Biochem. Appl. Biol. Sci.

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Background and objective: The pre-analytical rejection rate is the proportion of samples rejected at the stage that includes the initial procedures of the testing process performed outside the laboratory walls by healthcare professionals. This study aimed to evaluate the pre-analytical rejection rate by considering the health status of the patients and the sample types and to examine the measures that can be taken against it. Methods: The data of the samples that came to the laboratory for analysis for one year were included. These data were categorized according to sample types in complete blood count, biochemistry, hormones, urine, blood gases, coagulation, erythrocyte sedimentation rate (ESR), glycosylated hemoglobin (HbA1c). It was also categorized by emergency, outpatient, inpatient, and critically ill status. Considering the health status of the patients, the pre-analytical rejection rates determined in these sample types were compared. Results: Complete blood count (0.40%) in emergency patients, HbA1c (0.78%) in outpatients, biochemistry (0.62%) in inpatients, hormones (0.29%), urine (6.19%) blood gases (1.03%), coagulation (1.26%), ESR (3.23%) in critical patients, sample types had the highest pre-analytical rejection rate. Conclusions: The source of causes that affect pre-analytical rejection rates, such as hemolyzed sample, clotted sample, or insufficient sample, may be due to the patient's bed rest, critical or emergency. An underlying disease, treatment, or frequent phlebotomy may also be a factor. The source of the causes that affect the pre-analytical rejection rates, such as incorrect request, incorrect registration, and incorrect tube, can usually be attributed to non-laboratory healthcare personnel.

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Determination of hemolysis cut-offs for biochemical and immunochemical analytes according to their value

Dupuy

Bargnoux

Kuster

et al. 2020

Clinical Chemistry and Laboratory Medicine (CCLM)

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AbstractBackgroundAll general biochemistry instruments allow the measure of hemolysis index (HI), and suppliers provide an acceptable HI for each assay without consideration of the analyte value or its clinical application. Our first objective was to measure the impact of hemolysis degree on plasma biochemical and immunochemical analytes to determine the maximum allowable HI for each of them using four calculation methods as significant bias in comparison to manufacturer’s data. The second objective was to assess whether the maximum allowable HI varied according to the analyte values.MethodsTwenty analytes were measured in hemolyzate-treated plasma to determine the HI leading to a significant change compared to baseline value. Analytes were assessed at one (3 analytes), two (5 analytes) and three (12 analytes) values according to their sensitivity to hemolysis and their clinical impact. We used four calculation methods as significant limit from baseline value: the total change limit (TCL), the 10% change (10%Δ), the analytical change limit and the reference change value.ResultsAllowable HI was significantly different according to the threshold chosen for most analytes and was also dependent on the analyte value for alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, creatine kinase, iron, haptoglobin and high sensitivity troponin T. No hemolysis interference was observed for albumin, creatinine, C-reactive protein, and procalcitonin even at an HI value of 11 g/L.ConclusionsThis study highlights that TCL is the most appropriate calculation method to determine allowable HI in practice for biochemical and immunochemical parameters using Cobas 8000© from Roche Diagnostics. In addition, different allowable HI were found according to analyte value leading to optimization of resampling to save time in patient care.

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The prevalence of hemolysis – a survey using hemolysis index

Cited by 4 publications

References 2 publications

Massive hemolysis due to Clostridium perfringens: a laboratory’s perspective

Massive hemolysis due to Clostridium perfringens: a laboratory’s perspective

Pre-analytical rejection rates of clinical samples based on patients’ health status

Determination of hemolysis cut-offs for biochemical and immunochemical analytes according to their value

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