Recommendations for the use of biomarkers for the management of adults with sepsis: a scoping review and critical appraisal.

OBJECTIVE

A synthesis and appraisal of the recommendations for biomarkers in practice guidelines concerning sepsis is required to consolidate evidence-based practice. We generated an evidence gap map (EGM) on the use of biomarkers for managing adults with sepsis.

DESIGN

Scoping review.

DATA SOURCES

MEDLINE, Guidelines International Network, Pan American Health Organization, Trip Database and UpToDate were searched from 2016 to March 2025.

ELIGIBILITY CRITERIA

Guidance documents (GD) that searched at least one literature source and provided clinical recommendations for the use of biomarkers for the management (diagnosis and prognosis, including treatment response) of adults with sepsis.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently applied the eligibility criteria and extracted data. We used the AGREE-II (Appraisal of Guidelines for Research and Evaluation) tool to assess the GD quality. GDs that scored ≥50% on the AGREE-II 'Rigour of development' domain were considered robust. We also applied the GRADE (Grading of Recommendations Assessment, Development and Evaluation) system to evaluate if the recommendations were strong or conditional.

RESULTS

We found 10 GDs, with only half (4/8) having a robust methodology. There were 31 recommendations concerning biomarkers. Among these, 24 (77.4%) recommendations were about single biomarkers, with lactate (23; 74.2%) and procalcitonin (8; 25.8%) most frequently recommended. Biomarker testing focused on prognosis in 28 (90.3%) recommendations. Overall, 16 (51.6%) recommendations were graded strong and 13 (42.0%) were conditional, which we displayed in an EGM.

CONCLUSIONS

The methodology of GDs concerning adult sepsis was poor. Our review calls for more prudent use of biomarkers in specific prognostic scenarios and in combination with standard clinical assessments. Enhancing the methodological quality of future GDs is essential to generate more valid and robust recommendations for optimising patient care.