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Biochemia Medica, Vol. 36 No. 2, 2026.

Erratum

https://doi.org/10.11613/BM.2026.021201

Corrigendum to: Refining quality control strategies in highly automated laboratories: experience in the integration of multistage statistical designs and risk management

Maria Costa-Pallaruelo ; Biochemistry Department, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, Barcelona, Spain
Alvaro Garcia-Osuna ; Biochemistry Department, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, Barcelona, Spain
Marina Canyelles ; Biochemistry Department, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, Barcelona, Spain
Cecilia Martinez-Bru ; Core Laboratory, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
Nicoleta Nan ; Biochemistry Department, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, Barcelona, Spain
Rosa Ferrer-Perez ; Biochemistry Department, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, Barcelona, Spain
Francisco Blanco-Vaca ; Biochemistry Department, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, Barcelona, Spain
Leonor Guinon ; Biochemistry Department, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, Barcelona, Spain

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Hrčak ID:

348232

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https://hrcak.srce.hr/348232

Publication date:

15.6.2026.

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Copyright statement: Croatian Society of Medical Biochemistry and Laboratory Medicine.

Copyright: 2025, Croatian Society of Medical Biochemistry

License (open-access):

This is an Open Access article distributed under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Date received: 02 February 2026

Date accepted: 10 March 2026

Publication date: 15 April 2026

Publication date: 15 June 2026

Volume: 36

Issue: 2

Electronic Location Identifier: 021201

Related article (corrected article):

Publisher ID: bm-36-2-021201

DOI: 10.11613/BM.2026.021201

Article Information (continued)

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Subject: Corrigendum

Corrigendum to: Refining quality control strategies in highly automated laboratories: experience in the integration of multistage statistical designs and risk management

Maria Costa-Pallaruelo[*][1][2]

Alvaro Garcia-Osuna[1][2]

Marina Canyelles[1][2]

Cecilia Martinez-Bru[2]

Nicoleta Nan[1]

Rosa Ferrer-Perez[1][2]

Francisco Blanco-Vaca[1]

Leonor Guinon[1][2][3]

 

[1] Biochemistry Department, Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, Barcelona, Spain

[2] Core Laboratory, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain

[3] Quality Department Laboratories, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain

Author notes:

Correspondence to: [*] Corresponding author: mcostap@santpau.cat

This is a correction of Biochem Med (Zagreb) 2025;35(3):030704. DOI:https://doi.org/10.11613/BM.2025.030704.

Since the publication of the article, the authors have noticed an error in the calculation of the sigma metric. The corrected calculations are presented below. We apologize to the readers for any inconvenience this error may have caused.

During a post-publication review of the calculations, an error was identified in the formula used for the calculation of the sigma metric. Specifically, the calculations were performed without considering the absolute value in the formula: Sigma (σ) = (TEa − |SE|) / CV (where TEa represents the allowable total error, SE the systematic error and CV the coefficient of variation).

Consequently, the sigma values reported for the evaluated parameters were affected. After identifying this issue, the sigma metrics were recalculated using the correct formula including the absolute value of SE. Subsequently, all related analyses and procedures based on these sigma values were repeated using the corrected calculations.

All corrections are underlined to facilitate identification of the changes from the previously published version.

Corrections in the Abstract

Results: Additionally, to streamline management, the QCP covering the greatest number of parameters per analyzer was prioritized, which ultimately resulted in the adoption of only three general QCP. Only 4 individualized QCP were required to cover 9 parameters with lower sigma values.

Corrections in the Methods section

For each quality control level in each analyzer, the sigma value was calculated using the equation: Sigma (σ) = (TEa - |SE|) / CV.

Corrections in the Results section

The mean sigma values obtained for each parameter in each of the analyzers are shown in Tables 2 and 3, respectively. All Alinity systems showed 9 to 14 parameters with sigma values ≥ 6, 4 to 8 parameters with sigma between 5 and 6, 3 to 5 parameters with sigma between 4 and 5 and up to 2 parameters with sigma < 4.

This resulted in the adoption of only three QC plans (QCP 1, 2 and 3) out of the seven initially defined. As shown in Table 8, only nine parameters with lower sigma values required individualized QC plans due to their need for stricter QC rules. These nine parameters were effectively covered by four individual QCPs.

Corrections in the Discussion section

Second, for measurement procedures with sigma values between 4.65 and 6, QC rules can be selected based on the desired run size, while maintaining an acceptable Max E(Nuf). For measurement procedures with sigma values between 4 and 4.65, achieving an acceptable Max E(Nuf) requires applying more complex QC rules, such as multiple control rules 13s/22s/R4s/41s (MR N4), in the “startup” stage to reach an appropriate Ped, regardless of the desired run size.

Corrections in Tables

Table 2 Mean sigma values for the parameters measured in Alinity c systems
Parameterσ, mean
Alinity c1Alinity c2Alinity c3Alinity c4
Albumin≥ 6≥ 65.565.39
AP≥ 65.30≥ 65.94
ALT4.754.685.815.16
Amylasena≥ 6≥ 6na
AST≥ 6na4.97≥ 6
Calcium5.845.665.145.82
Cholesterolna5.064.514.96
Chloride4.143.314.63na
CKna≥ 6≥ 6≥ 6
Creatinine≥ 6≥ 6≥ 6≥ 6
Direct Bilirubin≥ 6na≥ 6na
GGT≥ 64.19≥ 6≥ 6
Glucose5.61≥ 6≥ 6≥ 6
HDLnanana4.21
LD≥ 6na≥ 6≥ 6
Magnesium3.00na2.453.31
CRP≥ 6≥ 6≥ 6≥ 6
Potassium5.775.815.32na
Sodium3.123.493.22na
Total Bilirubin≥ 6≥ 6≥ 65.14
Total Protein≥ 6≥ 6≥ 6≥ 6
Triglyceride≥ 6na≥ 6≥ 6
Urea≥ 6≥ 64.785.69
Uric Acidna≥ 64.55na
Albumin Una5.54nana
Calcium Una≥ 6nana
Creatinine U≥ 6≥ 6nana
Glucose Una≥ 6nana
Phosphorus Una5.23nana
Potassium U≥ 6≥ 6nana
Sodium U4.615.00nana
Urea U5.625.21nana
σ - sigma. AP - alkaline phosphatase. ALT - alanine aminotransferase. AST - aspartate aminotransferase. CK - creatine kinase. HDL - high density lipoprotein. LD - lactate dehydrogenase. GGT - gamma-glutamyl transferase. CRP - C-reactive protein. U - urine. na - parameter not available.
Table 5 Quality control plans for the parameters measured in Alinity c systems
ParameterAlinity c1Alinity c2Alinity c3Alinity c4
QCPCategoryQCPCategoryQCPCategoryQCPCategory
Albumin1B1C1C1D
AP1B1C1C1D
ALT5B5B1C2D
Amylasenana1D1Enana
AST1Cnana3C1D
Calcium1B1C2C1D
Cholesterolnana2C4E2D
Chloride4E-E7Enana
CKnana1D1E1E
Creatinine1A1B1C1C
D Bil1Enana1Enana
GGT1B6C1C1D
Glucose1B1B1C1D
HDLnananananana4D
LD1Cnana1E1E
Magnesium-Cnana-E-E
CRP1C1C1C1D
Potassium1B1B2Anana
Sodium-B-B-Anana
T Bil1B1C1C2D
Total Protein1C1C1C1D
Triglyceride1Cnana1E1D
Urea1A1A5C1C
Uric Acidnana1E4Enana
Albumin Unana1Dnananana
Calcium Unana1Enananana
Creatinine U1E1Enananana
Glucose Unana1Enananana
Phos Unana1Enananana
Potassium U1E1Enananana
Sodium U7E2Enananana
Urea U1E1Enananana
AP - alkaline phosphatase. ALT - alanine aminotransferase. AST - aspartate aminotransferase. CK - creatine kinase. D Bil – direct bilirubin. HDL - high density lipoprotein. LD - lactate dehydrogenase. GGT - gamma-glutamyl transferase. CRP - C reactive protein. Phos – phosphorus. QCP - quality control plan. T Bil - total bilirubin. U - urine. na - not available. “-“ - sigma < 4.
Table 7 Framework for selecting a quality control plan based on the sigma level of measurement procedures
Sigma level“Startup” stage“Monitor” stage
≥ 612.5s N1QC rules could be selected based on the desired run size*
4.65-6QC rules could be selected based on the workload*QC rules could be selected based on the desired run size*
4-4.65MR N4QC rules could be selected based on the desired run size*
< 4na†na†
*QC rule could be selected based on the “sigma metric statistical QC run size nomogram” proposed by Westgard et al (1). †No QC strategy is available, as no “startup” QC rule achieves a Ped ≥ 0.9. Improvement of the analytical performance is needed. QC - quality control. N - number of quality control measurements per QC event.
Table 8 Quality control plan implemented by analyzer and individualized quality control plans for specific parameters
AnalyzerQCPIndividualized QCP, parameter
Alinity1 c115, ALT; 4, chloride; 7, sodium U
Alinity1 c225, ALT; 6, GGT
Alinity2 c334, cholesterol and uric acid; 5, urea; 7, chloride
Alinity3 c424, HDL
Cobas Pro13-
Cobas Pro234, NT-proBNP
ALT - alanine aminotransferase. HDL - high density lipoprotein. NT-proBNP - N-terminal pro brain natriuretic peptide. QCP - quality control plan.
Supplementary table 1 Allowable total error (and source of the analytical performance specification) applied to each parameter measured in Alinity c systems
TEaSource
Albumin8.25p90 SEQC
AP21.00MCS
ALT18.70EFLM des
Amylase13.10EFLM des
AST18.70EFLM min
Calcium9.10MCS
Cholesterol8.30EFLM des
Chloride6.00MCS
CK8.50p90 SEQC
Creatinine22.00MCS
D Bil23.40EFLM des
GGT9.20EFLM opt
Glucose9.30EFLM min
HDL14.90EFLM min
LD21.00MCS
Magnesium9.40MCS
CRP26.00EFLM opt
Potassium7.30EFLM min
Sodium3.20MCS
T Bil37.00EFLM min
Total Protein9.00MCS
Triglyceride26.20EFLM des
Urea17.10EFLM des
Uric Acid12.50EFLM des
Albumin U14.00MCS
Calcium U16.00MCS
Creatinine U13.00MCS
Glucose U8.40MCS
Phos U11.00MCS
Potassium U8.60MCS
Sodium U7.20MCS
Urea U13.00MCS
AP - alkaline phosphatase. ALT - alanine aminotransferase. AST - aspartate aminotransferase. CK - creatine kinase. CRP - C-reactive protein. D Bil - direct bilirubin. EFLM des - desirable analytical performance specification (APS) according to the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) biological variation database (10). EFLM min - minimum APS according to the EFLM biological variation database (10). EFLM opt - optimal APS according to the EFLM biological variation database (10). HDL - high density lipoprotein. LD - lactate dehydrogenase. GGT - gamma-glutamyl transferase. MCS - Spanish minimum consensus specification, based on state-of-the-art performance (12). p90 SEQC - 90th percentile of measurement errors provided by the Spanish Society of Laboratory Medicine (SEQCML) from the external quality assessment schemes, used as a state-of-the-art APS. Phos – phosphorus. QCP - quality control plan. SOTA - state-of-the-art. T Bil - total bilirubin. TEa - allowable total error. U – urine.

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