Home Comparison of capillary finger stick and venous blood sampling for 34 routine chemistry analytes: potential for in hospital and remote blood sampling
Article Open Access

Comparison of capillary finger stick and venous blood sampling for 34 routine chemistry analytes: potential for in hospital and remote blood sampling

  • Martijn J.H. Doeleman , Anne-Fleur Koster , Anouk Esseveld , Hans Kemperman , Joost F. Swart , Sytze de Roock and Wouter M. Tiel Groenestege ORCID logo EMAIL logo
Published/Copyright: November 18, 2024
Download Article (PDF)
Become an author with De Gruyter Brill
Submit Manuscript Author Information
Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 63 Issue 4

Abstract

Objectives

This study examined the comparability of venous and capillary blood samples with regard to routine chemistry analytes.

Methods

Venous and capillary blood samples were collected from adult patients to assess comparability of alanine transaminase, albumin, alkaline phosphatase, apolipoprotein B, aspartate aminotransferase, total bilirubin, calcium, chloride, creatin kinase, creatinine, C-reactive protein, ferritin, folic acid, free T4, gamma glutamyltransferase, glucose, high density lipoprotein cholesterol, iron, lipase, lipoprotein a, magnesium, phosphate, postassium, prostate specific antigen, sodium, total cholesterol, total protein, transferrin, triglycerides, thyroid stimulating hormone, urate, urea, vitamin B12 and 25-hydroxyvitamin-D3. Furthermore, hemolysis-icterus-lipemia Index (HIL-Index) was measured for all samples. All measurements were performed using the Siemens Atellica® CH or IH Analyzer. Deming regression analysis and mean relative differences between venous and capillary measurements of each analyte were contrasted with the desirable total allowable error (TEa) and Clinical Laboratory Improvement Amendments (CLIA) 2024 proposed acceptance limits for proficiency testing.

Results

Deming regression and mean relative differences demonstrated excellent comparability between venous and capillary samples for most measured analytes.

Conclusions

Capillary and venous samples showed comparable results for almost all studied chemistry analytes. Of the 33 studied analytes for which TEa criteria where available, 30 met TEa criteria. CLIA 2024 criteria where available for 29 of the studied analytes of which only glucose did not meet the criteria. In conclusion, capillary blood draw is a suitable alternative for venous blood sampling for measuring most of the investigated analytes. This benefits patients with fear of needles and might pave the way for remote self-sampling.

Keywords: chemistry analytes; capillary sampling; finger stick; comparability; remote blood sample collection; alternative blood sampling

Introduction

Laboratory testing of routine chemistry analytes is an essential part of the clinical care of patients with both acute and chronic conditions. The standard procedure to acquire a blood sample for laboratory testing is venipuncture, which consists of obtaining a venous blood sample from the antecubital fossa. Venipuncture requires a trained phlebotomist and a physical interaction between the healthcare professional and the patient in question, resulting in additional costs and logistical requirements [1]. Furthermore, the procedure can be perceived as burdensome for the patient, especially in pediatric populations, patients with fear of needles or people with poor venous access [2], 3].

In recent years, accelerated by the COVID-19 pandemic and overall increasing burden on healthcare provisions, research has focused on how to empower patients to take control of their own clinical care and provide them with remote treatment and monitoring strategies. Compared to venous sampling, capillary sampling requires smaller volumes of blood and can be performed by patients themselves [4], 5]. Therefore, it is a more suitable method for remote or at-home blood sample collection which could potentially result in cost and time savings for both patients and healthcare professionals. Recent technological advancements have led to an increasing number of blood self-sampling devices focused on decentralized capillary sample collection of either liquid or dried blood. These devices may empower patients to perform self-sampling and alleviate logistic problems associated with remote sample collection [6]. Although capillary sampling is a well-established procedure for neonatal heel prick screening or point-of-care testing [7], [8], [9], there is limited literature regarding blood sampling with capillary tubes for analysis of routine chemistry analytes [10], 11]. For complete blood count parameters and routine coagulation assays this has been recently studied [12], 13].

Because the Siemens Atellica (immuno)chemistry analyzers are validated for venous samples only, comparability between venous and capillary measurements needs to be validated before capillary sampling can be implemented in clinical practice. The aim of this study was to determine the comparability of 34 routinely requested chemistry analytes measured in finger stick capillary blood and venous blood, in order to determine the feasibility of in hospital and remote self-sampling by finger stick.

Materials and methods

Study population

To assess comparability between venous and capillary blood measurements, venous and capillary samples were collected from up to 167 adult patients. All adult patients (≥18 years) presenting to the outpatient clinic of the Central Diagnostic Laboratory at the University Medical Center Utrecht (UMCU, Utrecht, The Netherlands) were eligible to participate in this study, regardless of underlying condition. After patients provided written informed consent, an additional capillary finger stick sample was collected. After anonymization of paired capillary and venous samples measurements were performed.

This study was conducted according to the guidelines for Good Clinical Practice (GCP) and Declaration of Helsinki (2013, revised version). The study protocol was approved by the Institutional Review Board at our hospital (20–676/C-22-800/D-23U-0136).

Sample collection

Venous and capillary blood sample collection was performed by a trained phlebotomist at the outpatient clinic. Venous blood was collected via venipuncture with the BD Vacutainer® blood collection system (Becton Dickinson, NJ, USA), at the cubital fossa. Subsequently, venous blood was collected in 3 mL Lithium Heparin tubes (Lithium Heparin 3 mL 56 U USP, BD Vacutainer®, Plymouth, UK). In addition to the venipuncture, a capillary blood sample was obtained by finger stick. First, the puncture site was cleaned using a tissue with isopropyl alcohol 70 % and allowed to air dry. The skin was punctured using a BD Microtainer® contact activated lancet (Becton Dickinson, NJ, USA) to a depth of 2.0 mm and the first drop of blood was wiped off. Subsequent drops were collected into Lithium Heparin microtubes (0.8 mL, MiniCollect® Complete, Greiner Bio-One GmbH, Kremsmünster, Austria). After collection, tubes were capped and inverted eight times.

Measurements

All assays were performed at the ISO15189 accredited Central Diagnostic Laboratory of the UMCU using the Siemens Atellica® CH or IH Analyzer, depending on the analyte, according to manufacturer instructions. For photometric tests, samples diluted 1:5 (50 μL sample + 200 μL CH diluent generates up to 15 test results). Integrated multisensor technology for electrolyte testing produces with 25 μL results for sodium, potassium and chloride. Samples for comparability between venous and capillary measurements were analyzed within 4 h after blood collection. The analyzer was maintained according recommendations of the manufacturer and results were guaranteed by a rigorous quality control program using internal and external quality control schemes. Analytes measured in both venous and capillary samples to study compatibility were (with required sample volumes between parentheses): alanine transaminase (ALAT) (25 μL), albumin (4 μL), alkaline phosphatase (ALP) (10 μL), apolipoprotein B (ApoB) (5 μL), aspartate aminotransferase (ASAT) (25 μL), total bilirubin (10 μL), calcium (16 μL), chloride (25 μL), creatin kinase (CK) (6 μL), creatinine (13 μL), C-reactive protein (CRP) (10 μL), ferritin (10 μL), folic acid (100 μL), free T4 (fT4) (25 μL), gamma glutamyltransferase (GGT) (10 μL), glucose (10 μL), high density lipoprotein cholesterol (HDL) (14 μL), iron (25 μL), lipase (3 μL), lipoprotein a (Lp(a)) (9 μL), magnesium (12 μL), phosphate (8 μL), postassium (25 μL), prostate specific antigen (PSA) (35 μL), sodium (25 μL), total cholesterol (4 μL), total protein (18 μL), transferrin (2 μL), triglycerides (4 μL), thyroid stimulating hormone (TSH) (75 μL), urate (11 μL), urea (7 μL), vitamin B12 (100 μL) and 25-hydroxyvitamin D3 (vitamin D) (20 μL). HIL-interference tresholds, if applicable, where similarly for venous and capillary samples. An overview of the total study population is presented in Table 1.

Table 1:

Overview of study population characteristics.

First cohort1 Second cohort2 Third cohort3
Number of total patients 66 30 133
Age, years, mean (range) 56 (22–81) 55 (26–83) 59 (19–88)
Female, n (%) 20 (30) 10 (33) 65 (49)

Statistical analysis

Deming regression and mean difference with 95 % confidence intervals (CI) were calculated to assess the comparability between capillary and venous samples. For each of the analytes, the mean relative difference, including 95 % confidence interval, was compared to the desirable total allowable error (TEa) derived from the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) database [14]. The TEa consists of the within subject coefficient of variation (CVi) and between subject coefficient of variation (CVg) and was calculated according to the formula: 0.25 * ( C V i 2 + C V g 2 ) 0.5 + 1.65 * 0.5 * C V i . In addition, the mean relative difference was compared to the 2024 Clinical Laboratory Improvement Amendments (CLIA) acceptance limits for proficiency testing. Measurement results classified as invalid by the Siemens Atellica® CH and IH Analyzers were excluded from all analyses. All data were analyzed using R version 4.0.3 [15] with p-values <0.05 considered as statistically significant.

Results

Deming regression showed very strong linear correlations and excellent comparability between capillary and venous results for measured analytes (Table 2 and Supplementary Figure S1). Observed deviations from equality were very small. For each of the analytes, the mean relative difference, including 95 % confidence interval, was compared to the desirable total allowable error (TEa) derived from the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) database (Figure 1). All analytes except chloride, glucose and sodium did not meet the EFLM desirable TEa criteria (Table 2). For folic acid no TEa was available. Contrasted to the 2024 Clinical Laboratory Improvement Amendments (CLIA) acceptance limits all analytes for which CLIA criteria where available, with the exception of glucose, where within the proposed limits. For ApoB, Lp(a), lipase, transferrin and vitamin D no CLIA limits are available. Lowest correlations where found for folic acid with R=0.84 and potassium with R=0.67 whereas all other R values were ≥0.92.

Table 2:

Differences and deming regression characteristics between capillary and venous measurements contrasted with desirable total allowable error (TEa) and clinical laboratory improvement amendments (CLIA) proposed acceptance limits for proficiency testing.

Test Mean relative difference % [95 % CI] Mean absolute difference [95 % CI] Range Unit Deming regression R TEa, % Within TEa? CLIA criteria Within CLIA?
Intercept [95 % CI] Slope [95 % CI]
ALAT −1.41 [−2.58 to −0.24] −0.44 [−0.68 to −0.21] 10.00–95.00 U/L 0.00 [−0.50 to 0.49] 0.98 [0.97 to 1.00] 1.00 16.1 Yes 15 % or 6 U/L Yes
Albumin −1.46 [−1.84 to −1.07] −0.59 [−0.75 to −0.42] 26.00–45.70 g/L 0.27 [−1.61 to 2.15] 0.98 [0.93 to 1.03] 0.99 3.4 Yes 8 % Yes
ALP −2.16 [−2.55 to −1.78] −1.81 [−2.14 to −1.48] 27.00–535.00 U/L −0.41 [−1.02 to 0.21] 0.98 [0.98 to 0.99] 1.00 10.5 Yes 20 % Yes
ApoB −1.59 [−2.16 to −1.03] −0.01 [−0.01 to 0.00] 0.09–1.72 g/L 0.00 [−0.01 to 0.00] 0.99 [0.99 to 1.00] 1.00 10.6 Yes NA NA
ASAT 3.96 [ 1.37 to 6.56] 0.63 [0.12 to 1.15] 10.00–68.00 U/L 0.79 [−0.57 to 2.15] 0.99 [0.93 to 1.05] 0.95 13.6 Yes 15 % or 6 U/L Yes
Bilirubin −6.10 [−7.54 to −4.65] −0.71 [−0.86 to −0.56] 3.00–44.00 umol/L −0.12 [−0.32 to 0.09] 0.95 [0.94 to 0.96] 1.00 24.8 Yes 20 % or 0.4 mg/dL Yes
Calcium −0.34 [−0.76 to 0.09] −0.01 [−0.02 to 0.00] 2.09–2.76 mmol/L 0.21 [−0.05 to 0.47] 0.91 [0.80 to 1.02] 0.92 2.3 Yes 1.0 mg/dL Yes
Chloride 1.67 [1.35 to 1.98] 1.75 [1.42 to 2.08] 94.00–113.00 mmol/L 12.54 [2.95 to 22.13] 0.90 [0.81 to 0.99] 0.92 1.2 No 5 % Yes
CK −0.88 [−2.15 to 0.40] −0.57 [−1.48 to 0.34] 27.00–285.00 U/L 0.05 [−2.17 to 2.26] 0.99 [0.97 to 1.02] 1.00 22.6 Yes 20 % Yes
Creatinine −4.97 [−5.66 to −4.27] −4.02 [−4.55 to −3.48] 45.00–352.00 umol/L −4.69 [−6.09 to −3.29] 1.01 [0.99 to 1.02] 1.00 7.4 Yes 10 % or 0.2 mg/dL Yes
CRP −2.94 [−6.50 to 0.61] −0.22 [−0.37 to −0.06] 0.01–87.00 mg/L −0.14 [−0.38 to 0.09] 0.99 [0.95 to 1.03] 0.99 50.7 Yes 30 % or 1 mg/L Yes
Ferritin −0.89 [−3.70 to 1.92] −3.43 [−8.05 to 1.19] 7.00–1,043.00 ug/L 4.39 [−5.68 to 14.47] 0.92 [0.78 to 1.07] 1.00 13.8 Yes 20 % Yes
Folic acid 8.05 [1.74 to 14.35] 2.94 [0.71 to 5.17] 25.10–53.10 nmol/L −8.38 [−25.93 to 9.16] 1.31 [0.79 to 1.82] 0.84 NA NA 30 % or 1 ng/mL Yes
fT4 −3.08 [−3.92 to −2.24] −0.48 [−0.63 to −0.33] 10.50–23.40 pmol/L −1.17 [−3.35 to 1.00] 1.04 [0.90 to 1.19] 0.96 6.3 Yes 15 % or 0.3 ng/dL Yes
GGT −0.36 [−1.70 to 0.98] −0.65 [−1.03 to −0.26] 9.00–457.00 U/L 0.51 [−0.06 to 1.07] 0.97 [0.96 to 0.99] 1.00 18.9 Yes 15 % or 5 U/L Yes
Glucose 7.62 [3.00 to 12.25] 0.44 [0.22 to 0.66] 4.10–18.10 mmol/L 0.35 [−0.16 to 0.85] 1.01 [0.96 to 1.07] 0.98 6.1 No 8 % or 6 mg/dL No
HDL −1.94 [−2.35 to −1.54] −0.03 [−0.03 to −0.02] 0.68–3.63 mmol/L −0.01 [−0.03 to 0.01] 0.99 [0.97 to 1.01] 1.00 10.9 Yes 20 % or 6 mg/dL Yes
Iron −0.57 [−1.46 to 0.31] −0.14 [−0.27 to −0.01] 4.00–35.00 umol/L 0.31 [0.00 to 0.61] 0.97 [0.95 to 0.99] 1.00 32.4 Yes 15 % Yes
Lipase −1.46 [−2.23 to −0.70] −0.62 [−0.92 to −0.33] 22.00–86.00 U/L 0.20 [−0.58 to 0.98] 0.98 [0.96 to 1.00] 1.00 12.9 Yes NA NA
Lp(a) 0.01 [−3.54 to 3.57] −0.43 [−0.73 to −0.14] 1.59–109.36 mg/dL 0.14 [−0.11 to 0.39] 0.98 [0.97 to 0.99] 1.00 29.8 Yes NA NA
Magnesium −0.80 [−1.43 to −0.17] −0.01 [−0.01 to 0.00] 0.45–0.97 mmol/L −0.02 [−0.06 to 0.01] 1.02 [0.97 to 1.07] 0.97 4 Yes 15 % Yes
Phosphate −2.84 [−4.06 to −1.63] −0.03 [−0.05 to −0.02] 0.61–1.40 mmol/L 0.00 [−0.08 to 0.07] 0.98 [0.91 to 1.04] 0.97 9.6 Yes 10 % or 0.3 mg/dL Yes
Potassium 1.23 [−0.57 to 3.03] 0.04 [−0.04 to 0.11] 3.30–5.20 mmol/L 0.98 [0.00 to 1.96] 0.77 [0.54 to 1.01] 0.67 4.9 Yes 0.3 mmol/L Yes
PSA 2.26 [−2.15 to 6.66] −0.03 [−0.08 to 0.02] 0.00–26.38 ug/L 0.04 [0.01 to 0.07] 0.97 [0.95 to 0.98] 1.00 16.2 Yes 20 % or 0.2 ng/mL Yes
Sodium −0.69 [−0.90 to −0.48] −0.98 [−1.29 to −0.68] 127.00–146.00 mmol/L 6.50 [−4.83 to 17.83] 0.95 [0.87 to 1.03] 0.94 0.6 No 4 mmol/L Yes
Total cholesterol −0.83 [−1.24 to −0.43] −0.04 [−0.06 to −0.02] 2.28–7.99 mmol/L 0.03 [−0.03 to 0.10] 0.98 [0.97 to 1.00] 1.00 8.8 Yes 10 % Yes
Total protein −1.82 [−2.22 to −1.43] −1.33 [−1.62 to −1.04] 58.00–84.00 g/L 3.38 [−0.18 to 6.94] 0.93 [0.88 to 0.98] 0.97 3.2 Yes 8 % Yes
Transferrin −1.68 [−2.31 to −1.04] −0.04 [−0.05 to −0.02] 1.51–3.03 g/L −0.02 [−0.13 to 0.09] 0.99 [0.94 to 1.04] 0.98 6.8 Yes NA NA
Triglycerides 4.27 [ 2.07 to 6.48] 0.05 [0.02 to 0.08] 0.50–3.90 mmol/L 0.02 [−0.05 to 0.10] 1.02 [0.96 to 1.08] 0.98 27 Yes 15 % Yes
TSH −2.52 [−3.31 to −1.74] −0.05 [−0.07 to −0.03] 0.00–8.32 mIU/L −0.02 [−0.08 to 0.04] 0.98 [0.95 to 1.02] 1.00 24.8 Yes 20 % or 0.2 mIU/L Yes
Urate 0.94 [0.45 to 1.44] 0.00 [0.00 to 0.00] 0.15–0.59 mmol/L 0.00 [0.00 to 0.01] 1.01 [0.99 to 1.02] 1.00 12.6 Yes 10 % Yes
Urea 5.80 [4.85 to 6.76] 0.35 [0.30 to 0.41] 2.40–26.70 mmol/L 0.17 [0.02 to 0.32] 1.03 [1.00 to 1.05] 1.00 17.8 Yes 9 % or 2 mg/dL Yes
Vitamin B12 3.48 [1.51 to 5.46] 10.70 [5.00 to 16.40] 161.00–1,291.00 pmol/L −1.61 [−11.19 to 7.96] 1.04 [1.02 to 1.06] 0.99 15.4 Yes 25 % or 30 pg/mL Yes
Vitamin D −6.39 [−11.14 to −1.65] −3.76 [−6.95 to −0.57] 25.00–107.00 nmol/L −9.81 [−19.64 to 0.02] 1.09 [0.93 to 1.26] 0.93 13.3 Yes NA NA

  1. ALP, alkaline phosphatase; ALAT, alanine transaminase; ApoB, apolipoprotein B; ASAT, aspartate aminotransferase; CI, confidence interval; CK, creatine kinase; CRP, C-reactive protein; fT4, free thyroxin; GGT, gamma glutamyltransferase; HDL, high density lipoprotein cholesterol; Lp(a), lipoprotein a; PSA, prostate-specific antigen; R, correlation coefficient; TSH, thyroid stimulating hormone; Vitamin D, 25-hydroxy vitamin D3. NA, not available.

Figure 1: Mean difference (%) with 95 % confidence interval (errorbars) for all analytes. ALAT, alanine transaminase; ALP, alkaline phosphatase; ApoB, apolipoprotein B; ASAT, aspartate aminotransferase; Bilirubin, total bilirubin; CK, creatine kinase; CRP, C-reactive protein; fT4, free thyroxin; GGT, gamma glutamyltransferase; HDL, high density lipoprotein cholesterol; Lp(a), lipoprotein a; PSA, prostate-specific antigen; TSH, thyroid stimulating hormone; vitamin D, 25-hydroxy vitamin D3.
Figure 1:

Mean difference (%) with 95 % confidence interval (errorbars) for all analytes. ALAT, alanine transaminase; ALP, alkaline phosphatase; ApoB, apolipoprotein B; ASAT, aspartate aminotransferase; Bilirubin, total bilirubin; CK, creatine kinase; CRP, C-reactive protein; fT4, free thyroxin; GGT, gamma glutamyltransferase; HDL, high density lipoprotein cholesterol; Lp(a), lipoprotein a; PSA, prostate-specific antigen; TSH, thyroid stimulating hormone; vitamin D, 25-hydroxy vitamin D3.

Moreover, analysis of bias showed small relative mean differences for all measured analytes (Supplementary Figures S2 and S3). A hemolysis index of one or greater was found more frequently in capillary samples (n=157) compared to venous samples (n=106) (Fisher’s Exact p-value <0.001). Icterus and Lipemia indices were not significantly different between venous and capillary samples (Table S1).

Discussion

The aim of this study was to assess comparability between venous and capillary samples, necessary to provide evidence for the validity of remote sample collection and delayed analysis.

Deming regression analyses demonstrated very strong linear correlations between venous and capillary samples for the studied analytes. Furthermore, mean relative differences and 95 % confidence interval limits did not exceed desirable TEa of albumin, ALAT, ALP, ApoB, ASAT, calcium, CK, creatinine, CRP, ferritin, fT4, GGT, HDL cholesterol, iron, lipase, Lp(a), magnesium, phosphate, postassium, PSA, total bilirubin, total cholesterol, total protein, transferrin, triglycerides, TSH, urate, urea, vitamin B12 and vitamin D. Measurement of all analytes in capillary samples, except glucose, met 2024 Clinical Laboratory Improvement Amendments (CLIA) acceptance limits when available.

In a study performed by Falch et al. no significant differences between capillary and venous sampling for measurement of urea, bilirubin, ASAT, ALAT, LD, insulin and fT4 were demonstrated [11]. Significant differences, although not clinical significant, where found for sodium, potassium, chloride, phosphate, creatinine and total protein. In addition they found that capillary sampling is not suitable for measurement of TSH. Of note, this study was performed over 30 years ago using analytical techniques which cannot undoubtedly be equated to current analytical methods. Results of a recent study of Maroto-García et al. included 18 biomarkers that were also studied in our study which were in line with our results [10].

A possible explanation for the observation that glucose, sodium and chloride exceed TEa limits is that the concentration of these analytes is more easily altered by capillary sampling which might cause increased leakage of ions from e.g. erythrocytes, compared with proteins. In addition, a negative bias was observed for several analytes which may be attributed to matrix-related differences between capillary and venous blood, including blood composition and analyte-specific bias. Moreover, the capillary sampling process may also lead to the mixing of interstitial fluid into the sample, resulting in a relative dilution of blood components and a negative bias when compared to venous samples.

This study is also subject to some limitations. First of all, the majority of measured values were within reference ranges of the measured analytes. Although there were less samples with abnormal results, comparability between venous and capillary samples was similar. The clinical impact of relative changes observed in this study is expected to be less at abnormal values compared to values within the reference range. Nevertheless, this cannot be concluded based solely on these results. Furthermore, desirable TEa was selected as limit of acceptable variation for comparability. Although this criterion allows to standardize results across laboratories, it is subject of debate due to the combination of bias and imprecision in one parameter [16]. Clinical thresholds will be different across diseases and patient populations, and thus standardized variability criteria, including CLIA acceptance limits, were used in this study to increase generalizability of our results. Before capillary self-sampling can be used in a home setting after which samples are being send by regular mail to the laboratory, further research studying analyte stability, is warranted.

In conclusion, depending on the intended use and when considered fit for purpose, capillary sampling shows to be an alternative for venous blood sampling in a hospital setting. For sufficiently stable analytes, blood sampling with a capillary tube might be suitable for self-sampling of blood at home and subsequent delayed analysis at the hospital laboratory.

Corresponding author: Wouter M. Tiel Groenestege, Utrecht University, P.O. Box 85500, Room number G03.548, 3508 GA, Utrecht, The Netherlands; and Central Diagnostic Laboratory, University Medical Center Utrecht, P.O. Box 85500, Room number G03.548, 3508 GA, Utrecht, The Netherlands, E-mail:

  1. Research ethics: This study was conducted according to the guidelines for Good Clinical Practice (GCP) and Declaration of Helsinki (2013, revised version). The study protocol was approved by the Institutional Review Board at our hospital (20–676/C-22-800/D-23U-0136).

  2. Informed consent: Informed consent was obtained from all individuals included in this study.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interests: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: The raw data can be obtained on request from the corresponding author.

References

1. Lei, BUW, Prow, TW. A review of microsampling techniques and their social impact. Biomed Microdevices 2019;21. https://doi.org/10.1007/s10544-019-0412-y.Search in Google Scholar PubMed PubMed Central

2. Lingervelder, D, Kip, MMA, Wiese, ED, Koffijberg, H, Ijzerman, MJ, Kusters, R. The societal impact of implementing an at-home blood sampling device for chronic care patients: patient preferences and cost impact. BMC Health Serv Res 2022;22. https://doi.org/10.1186/s12913-022-08782-w.Search in Google Scholar PubMed PubMed Central

3. Woods, K, Douketis, JD, Schnurr, T, Kinnon, K, Powers, P, Crowther, MA. Patient preferences for capillary vs. venous INR determination in an anticoagulation clinic: a randomized controlled trial. Thromb Res 2004;114:161–5. https://doi.org/10.1016/j.thromres.2004.05.013.Search in Google Scholar PubMed

4. Knitza, J, Tascilar, K, Vuillerme, N, Eimer, E, Matusewicz, P, Corte, G, et al.. Accuracy and tolerability of self-sampling of capillary blood for analysis of inflammation and autoantibodies in rheumatoid arthritis patients—results from a randomized controlled trial. Arthritis Res Ther 2022;24. https://doi.org/10.1186/s13075-022-02809-7.Search in Google Scholar PubMed PubMed Central

5. Linder, C, Neideman, M, Wide, K, Von Euler, M, Gustafsson, LL, Pohanka, A. Dried blood spot self-sampling by guardians of children with epilepsy is feasible: comparison with plasma for multiple antiepileptic drugs. Ther Drug Monit 2019;41:509–18. https://doi.org/10.1097/FTD.0000000000000605.Search in Google Scholar PubMed

6. Poland, DCW, Cobbaert, CM. Blood self-sampling devices: innovation, interpretation and implementation in total lab automation. Clin Chem Lab Med 2024;63:3–13. https://doi.org/10.1515/cclm-2024-0508.Search in Google Scholar PubMed

7. Fitzmaurice, DA, Geersing, G, Armoiry, X, Machin, S, Kitchen, S, Mackie, I. ICSH guidance for INR and D‐dimer testing using point of care testing in primary care. Int J Lab Hematol 2023;45:276–81. https://doi.org/10.1111/ijlh.14051.Search in Google Scholar PubMed

8. Enderle, Y, Foerster, K, Burhenne, J. Clinical feasibility of dried blood spots: analytics, validation, and applications. J Pharm Biomed Anal 2016;130:231–43. https://doi.org/10.1016/j.jpba.2016.06.026.Search in Google Scholar PubMed

9. Chen, H, Liu, K, Li, Z, Wang, P. Point of care testing for infectious diseases. Clin Chim Acta 2019;493:138–47. https://doi.org/10.1016/j.cca.2019.03.008.Search in Google Scholar PubMed PubMed Central

10. Maroto-García, J, Deza, S, Fuentes-Bullejos, P, Fernández-Tomás, P, Martínez-Espartosa, D, Marcos-Jubilar, M, et al.. Analysis of common biomarkers in capillary blood in routine clinical laboratory. Preanalytical and analytical comparison with venous blood. Diagnosis 2023;10:281–97. https://doi.org/10.1515/dx-2022-0126.Search in Google Scholar PubMed

11. Falch, DK. Clinical chemical analyses of serum obtained from capillary versus venous blood, using microtainers® and vacutainers®. Scand J Clin Lab Invest 1981;41:59–62. https://doi.org/10.3109/00365518109092015.Search in Google Scholar PubMed

12. Doeleman, MJH, Esseveld, A, Huisman, A, de Roock, S, Tiel Groenestege, WM. Stability and comparison of complete blood count parameters between capillary and venous blood samples. Int J Lab Hematol 2023;45:659–67. https://doi.org/10.1111/ijlh.14080.Search in Google Scholar PubMed

13. Fliervoet, LAL, Tiel Groenestege, WM, Huisman, A. Comparison of capillary and venous blood sampling for routine coagulation assays. Clin Biochem 2022;104:30–5. https://doi.org/10.1016/j.clinbiochem.2022.01.010.Search in Google Scholar PubMed

14. Aarsand, A, Fernandez-Calle, P, Webster, C, Coskun, A, Gonzales-Lao, E, Diaz-Garzon, J, et al.. The EFLM biological variation database; 2022. https://biologicalvariation.eu/ [Accessed 30 Apr 2023].Search in Google Scholar

15. R Core Team. R: a language and environment for statistical computing; 2017. https://www.r-project.org/.Search in Google Scholar

16. Oosterhuis, WP. Gross overestimation of total allowable error based on biological variation. Clin Chem 2011;57:1334–6. https://doi.org/10.1373/clinchem.2011.165308.Search in Google Scholar PubMed

Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/cclm-2024-0812).

Received: 2024-07-12
Accepted: 2024-11-01
Published Online: 2024-11-18
Published in Print: 2025-03-26

© 2024 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Beyond test results: the strategic importance of metadata for the integration of AI in laboratory medicine
  4. Reviews
  5. Reference, calibration and referral laboratories – a look at current European provisions and beyond
  6. How has the external quality assessment/proficiency testing of semen analysis been developed in the past 34 years: a review
  7. Opinion Papers
  8. Data flow in clinical laboratories: could metadata and peridata bridge the gap to new AI-based applications?
  9. A comprehensive survey of artificial intelligence adoption in European laboratory medicine: current utilization and prospects
  10. Guidelines and Recommendations
  11. Guidelines for the correct use of the nomenclature of biochemical indices of bone status: a position statement of the Joint IOF Working Group and IFCC Committee on Bone Metabolism
  12. Candidate Reference Measurement Procedures and Materials
  13. Absolute quantitation of human serum cystatin C: candidate reference method by 15N-labeled recombinant protein isotope dilution UPLC-MS/MS
  14. General Clinical Chemistry and Laboratory Medicine
  15. Performance evaluation of the introduction of full sample traceability system within the specimen collection process
  16. Pre-analytical stability of haematinics, lactate dehydrogenase and phosphate in whole blood at room temperature up to 24 h, and refrigerated serum stability of lactate dehydrogenase, folate and vitamin B12 up to 72 h using the CRESS checklist
  17. Comparison of capillary finger stick and venous blood sampling for 34 routine chemistry analytes: potential for in hospital and remote blood sampling
  18. Performance evaluation of enzymatic total bile acid (TBA) routine assays: systematic comparison of five fifth-generation TBA cycling methods and their individual bile acid recovery from HPLC-MS/MS reference
  19. Clinical performance of a new lateral flow immunoassay for xylazine detection
  20. Evaluation of revised UK-NEQAS CSF-xanthochromia method for subarachnoid hemorrhage: outcome data provide evidence for clinical value
  21. Strategies to verify equimolar peptide release in mass spectrometry-based protein quantification exemplified for apolipoprotein(a)
  22. Evaluation of the clinical performance of anti-mutated citrullinated vimentin antibody and 14-3-3 eta testing in rheumatoid arthritis
  23. Diagnostic performance of specific biomarkers for interstitial lung disease: a single center study
  24. Reference Values and Biological Variations
  25. Neonatal reference intervals for serum steroid hormone concentrations measured by LC-MS/MS
  26. Paediatric reference intervals for haematology parameters analysed on Sysmex XN-9000: a comparison of methods in the framework of indirect sampling
  27. Cardiovascular Diseases
  28. Analytical characteristics and performance of a new hs-cTnI method: a multicenter-study
  29. Diabetes
  30. Use of labile HbA1c as a screening tool to minimize clinical misinterpration of HbA1c
  31. Letters to the Editor
  32. Current trends and future projections in the clinical laboratory test market: implications for resource management and strategic planning
  33. Particulate matter in water: an overlooked source of preanalytical error producing erroneous chemistry test results
  34. “Activation” of macro-AST by pyridoxal-5-phosphate in the assay for aspartate aminotransferase
  35. The correlation of albumin with total protein concentrations in cerebrospinal fluid across three automated analysers – relevance to the diagnosis of subarachnoid haemorrhage in clinical chemistry practice
  36. Adult reference intervals for serum thyroid‐stimulating hormone using Abbott Alinity i measuring system
  37. Cell population data in venous thrombo-embolism and erysipelas: a potential diagnostic tool?
  38. Diagnostic performances and cut-off verification of blood pTau 217 on the Lumipulse platform for amyloid deposition in Alzheimer’s disease
  39. The first case of Teclistamab interference with serum electrophoresis and immunofixation
  40. Congress Abstracts
  41. Annual meeting of the Royal Belgian Society of Laboratory Medicine (RBSLM): “A Neurological Journey: Brain Teasers for Laboratory Medicine”
https://doi.org/10.1515/cclm-2024-0812
Keywords for this article
chemistry analytes; capillary sampling; finger stick; comparability; remote blood sample collection; alternative blood sampling
Creative Commons
BY 4.0

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Beyond test results: the strategic importance of metadata for the integration of AI in laboratory medicine
  4. Reviews
  5. Reference, calibration and referral laboratories – a look at current European provisions and beyond
  6. How has the external quality assessment/proficiency testing of semen analysis been developed in the past 34 years: a review
  7. Opinion Papers
  8. Data flow in clinical laboratories: could metadata and peridata bridge the gap to new AI-based applications?
  9. A comprehensive survey of artificial intelligence adoption in European laboratory medicine: current utilization and prospects
  10. Guidelines and Recommendations
  11. Guidelines for the correct use of the nomenclature of biochemical indices of bone status: a position statement of the Joint IOF Working Group and IFCC Committee on Bone Metabolism
  12. Candidate Reference Measurement Procedures and Materials
  13. Absolute quantitation of human serum cystatin C: candidate reference method by 15N-labeled recombinant protein isotope dilution UPLC-MS/MS
  14. General Clinical Chemistry and Laboratory Medicine
  15. Performance evaluation of the introduction of full sample traceability system within the specimen collection process
  16. Pre-analytical stability of haematinics, lactate dehydrogenase and phosphate in whole blood at room temperature up to 24 h, and refrigerated serum stability of lactate dehydrogenase, folate and vitamin B12 up to 72 h using the CRESS checklist
  17. Comparison of capillary finger stick and venous blood sampling for 34 routine chemistry analytes: potential for in hospital and remote blood sampling
  18. Performance evaluation of enzymatic total bile acid (TBA) routine assays: systematic comparison of five fifth-generation TBA cycling methods and their individual bile acid recovery from HPLC-MS/MS reference
  19. Clinical performance of a new lateral flow immunoassay for xylazine detection
  20. Evaluation of revised UK-NEQAS CSF-xanthochromia method for subarachnoid hemorrhage: outcome data provide evidence for clinical value
  21. Strategies to verify equimolar peptide release in mass spectrometry-based protein quantification exemplified for apolipoprotein(a)
  22. Evaluation of the clinical performance of anti-mutated citrullinated vimentin antibody and 14-3-3 eta testing in rheumatoid arthritis
  23. Diagnostic performance of specific biomarkers for interstitial lung disease: a single center study
  24. Reference Values and Biological Variations
  25. Neonatal reference intervals for serum steroid hormone concentrations measured by LC-MS/MS
  26. Paediatric reference intervals for haematology parameters analysed on Sysmex XN-9000: a comparison of methods in the framework of indirect sampling
  27. Cardiovascular Diseases
  28. Analytical characteristics and performance of a new hs-cTnI method: a multicenter-study
  29. Diabetes
  30. Use of labile HbA1c as a screening tool to minimize clinical misinterpration of HbA1c
  31. Letters to the Editor
  32. Current trends and future projections in the clinical laboratory test market: implications for resource management and strategic planning
  33. Particulate matter in water: an overlooked source of preanalytical error producing erroneous chemistry test results
  34. “Activation” of macro-AST by pyridoxal-5-phosphate in the assay for aspartate aminotransferase
  35. The correlation of albumin with total protein concentrations in cerebrospinal fluid across three automated analysers – relevance to the diagnosis of subarachnoid haemorrhage in clinical chemistry practice
  36. Adult reference intervals for serum thyroid‐stimulating hormone using Abbott Alinity i measuring system
  37. Cell population data in venous thrombo-embolism and erysipelas: a potential diagnostic tool?
  38. Diagnostic performances and cut-off verification of blood pTau 217 on the Lumipulse platform for amyloid deposition in Alzheimer’s disease
  39. The first case of Teclistamab interference with serum electrophoresis and immunofixation
  40. Congress Abstracts
  41. Annual meeting of the Royal Belgian Society of Laboratory Medicine (RBSLM): “A Neurological Journey: Brain Teasers for Laboratory Medicine”
Sign up now to receive a 20% welcome discount
Institutional Access
How does access work?
Have an idea on how to improve our website?
Please write us.
© 2025 De Gruyter Brill
Downloaded on 13.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/cclm-2024-0812/html
Scroll to top button