Evidence map›Paper›PMID 36484086›Full record

ArticleThe journal of pathology. Clinical research2023

Real-life data from standardized preanalytical coding (SPREC) in tissue biobanking and its dual use for sample characterization and process optimization.

Magdalena Skoworonska, Annika Blank, Irene Centeno, Caroline Hammer, Aurel Perren, Inti Zlobec, Tilman T Rau

Abstract read
In one paragraph

Article in The journal of pathology. Clinical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Standard PREanalytical Code Version 4.0.Biopreservation and biobanking · 2025
    Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Magdalena SkoworonskaInstitute of Pathology, University of Bern, Bern.
Annika BlankInstitute of Pathology, University of Bern, Bern.
Irene CentenoInstitute of Pathology, University of Bern, Bern.
Caroline HammerInstitute of Pathology, University of Bern, Bern.
Aurel PerrenInstitute of Pathology, University of Bern, Bern.ORCID 0000-0002-6819-6092
Inti ZlobecInstitute of Pathology, University of Bern, Bern.ORCID 0000-0001-6741-3000
Tilman T RauInstitute of Pathology, University of Bern, Bern.ORCID 0000-0002-1251-950X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The standardized preanalytical code (SPREC) aggregates warm ischemia (WIT), cold ischemia (CIT), and fixation times (FIT) in a precise format. Despite its growing importance underpinned by the European in vitro diagnostics regulation or broad preanalytical programs by the National Institutes of Health, little is known about its empirical occurrence in biobanked surgical specimen. In several steps, the Tissue Bank Bern achieved a fully informative SPREC code with insights from 10,555 CIT, 4,740 WIT, and 3,121 FIT values. During process optimization according to LEAN six sigma principles, we identified a dual role of the SPREC code as a sample characteristic and a traceable process parameter. With this preanalytical study, we outlined real-life data in a variety of organs with specific differences in WIT, CIT, and FIT values. Furthermore, our FIT data indicate the potential to adapt the SPREC fixation toward concrete paraffin-embedding time points and to extend its categories beyond 72 h due to weekend delays. Additionally, we identified dependencies of preanalytical variables from workload, daytime, and clinics that were actionable with LEAN process management. Thus, streamlined biobanking workflows during the day were significantly resilient to workload peaks, diminishing the turnaround times of native tissue processing (i.e. CIT) from 74.6 to 46.1 min under heavily stressed conditions. In conclusion, there are surgery-specific preanalytics that are surgico-pathologically limited even under process optimization, which might affect biomarker transfer from one entity to another. Beyond sample characteristics, SPREC coding is highly beneficial for tissue banks and Institutes of Pathology to track WIT, CIT, and FIT for process optimization and monitoring measurements.

Indexed as

Biological Specimen BanksCold IschemiaHumansUnited Statesbiobankingcold ischemia timefixation timeLEANSPRECwarm ischemia time

Identifiers

PMID36484086
PMCPMC9896154

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.