Prediction models for SIRS, sepsis and associated organ dysfunctions in paediatric intensive care: study protocol for a diagnostic test accuracy study

Böhnke J*, Rübsamen N*, Mast M, Rathert H, ELISE Study Group, Karch A, Jack T, Wulff A

Forschungsartikel (Zeitschrift) | Peer reviewed

Zusammenfassung

INTRODUCTION - OBJECTIVES - METHODS AND ANALYSIS - ETHICS AND DISSEMINATION - TRIAL REGISTRATION NUMBER - PROTOCOL VERSION; Systemic inflammatory response syndrome (SIRS), sepsis and associated organ dysfunctions are life-threating conditions occurring at paediatric intensive care units (PICUs). Early recognition and treatment within the first hours of onset are critical. However, time pressure, lack of personnel resources, and the need for complex age-dependent diagnoses impede an accurate and timely diagnosis by PICU physicians. Data-driven prediction models integrated in clinical decision support systems (CDSS) could facilitate early recognition of disease onset.; To estimate the sensitivity and specificity of previously developed prediction models (index tests) for the detection of SIRS, sepsis and associated organ dysfunctions in critically ill children up to 12 hours before reference standard diagnosis is possible.; We conduct a monocentre, prospective diagnostic test accuracy study. Clinicians in the PICU of the tertiary care centre Hannover Medical School, Germany, continuously screen and recruit patients until the adaptive sample size (originally intended sample size of 500 patients) is enrolled. Eligible are children (0-17 years, all sexes) who stay in the PICU for ≥12 hours and for whom an informed consent is given. All eligible patients are independently assessed for SIRS, sepsis and organ dysfunctions using corresponding predictive and knowledge-based CDSS models. The knowledge-based CDSS models serve as imperfect reference standards. The assessments are used to estimate the sensitivities and specificities of each predictive model using a clustered nonparametric approach (main analysis). Subgroup analyses ('age groups', 'sex' and 'age groups by sex') are predefined.; This study obtained ethics approval from the Hannover Medical School Ethics Committee (No. 10188_BO_SK_2022). Results will be disseminated as peer-reviewed publications, at scientific conferences, and to patients in an appropriate dissemination approach.; This study was registered with the German Clinical Trial Register (DRKS00029071) on 2022-05-23.; 10188_BO_SK_2022_V.2.0-20220330_4_Studienprotokoll.

Details zur Publikation

FachzeitschriftBMJ Paediatrics Open
Jahrgang / Bandnr. / Volume6
Ausgabe / Heftnr. / Issue1
Seitenbereiche001618-e001618
StatusVeröffentlicht
Veröffentlichungsjahr2022 (31.10.2022)
Sprache, in der die Publikation verfasst istEnglisch
DOI10.1136/bmjpo-2022-001618
Stichwörterdiagnostic study; clinical decision support system

Autor*innen der Universität Münster

Böhnke, Julia
Institut für Epidemiologie und Sozialmedizin
Böhnke, Julia
Institut für Epidemiologie und Sozialmedizin
Karch, André
Institut für Epidemiologie und Sozialmedizin
Rübsamen, Nicole
Institut für Epidemiologie und Sozialmedizin