SEARCHCOHORTemergency medicine, critical care

cohort·emergency medicine, critical care, infectious disease, clinical trial, observational study·PMC10028723

Role of Neutrophil Gelatinase-associated Lipocalin (NGAL) and Other Clinical Parameters as Predictors of Bacterial Sepsis in Patients Presenting to the Emergency Department with Fever

Indian Journal of Critical Care Medicine : Peer-reviewed, Official Publication of Indian Society of Critical Care Medicine · 11 authors, 6 centres

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TL;DR

This prospective study developed a scoring tool combining plasma NGAL with clinical parameters to predict bacterial sepsis in fever patients. A score greater than 7 was found to be highly suggestive of bacterial sepsis.

Full summary

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Plasma NGAL and standard clinical parameters were measured at admission. Bacterial sepsis was defined by positive blood culture or clinical diagnosis. The optimal NGAL cut-off for predicting sepsis was 570 ng/mL (AUC 0.69). A score >7 was highly suggestive of bacterial sepsis with an interval likelihood ratio of 7.77, while a score <3 effectively ruled it out.

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cohort

SPECIALTY

emergency medicine

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AI pipeline

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ORIGINAL PAPER

PMC10028723

Role of Neutrophil Gelatinase-associated Lipocalin (NGAL) and Other Clinical Parameters as Predictors of Bacterial Sepsis in Patients Presenting to the Emergency Department with Fever

Indian Journal of Critical Care Medicine : Peer-reviewed, Official Publication of Indian Society of Critical Care Medicine

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ABSTRACT

A bstract Background Bacterial sepsis is associated with significant morbidity and mortality. However, to date, there is no single test that predicts sepsis with reproducible results. We proposed that using a combination of clinical and laboratory parameters and a novel biomarker, plasma neutrophil gelatinase-associated lipocalin (NGAL) may aid in early diagnosis. Method A prospective cohort study was conducted at a tertiary care center in South India (June 2017 to April 2018) on patients with acute febrile episodes fulfilling the Systemic Inflammatory Response Syndrome (SIRS) criteria. Plasma NGAL and standard clinical and laboratory parameters were collected at the admission. Bacterial sepsis was diagnosed based on blood culture positivity or clinical diagnosis. Clinically relevant plasma NGAL cut-off values were identified using the receive operating characteristic (ROC) curve. Clinically relevant clinical parameters along with plasma NGAL's risk ratios estimated from the multivariable Poisson regression model were rounded and used as weights to create a new scoring tool. Results Of 100 patients enrolled, 37 had bacterial sepsis. The optimal plasma NGAL cut-off value to predict sepsis was 570 ng/mL [area under the curve (AUC): 0.69]. The NGAL sepsis screening tool consists of the following clinical parameter: diabetes mellitus, the presence of rigors, quick sequential organ failure assessment (qSOFA) >2, a clear focus of infection, and the plasma NGAL >570 ng/mL. A score of <3 ruled out bacterial sepsis and a score >7 were highly suggestive of bacterial sepsis with an interval likelihood ratio (LR) of 7.77. Conclusion The NGAL sepsis screening tool with a score >7 can be used in the emergency department (ED) to identify bacterial sepsis. How to cite this article Paul A, Newbigging NS, Lenin A, Gowri M, Varghese JS, Nell AJ, et al. Role of Neutrophil Gelatinase-associated Lipocalin (NGAL) and Other Clinical Parameters as Predictors of Bacterial Sepsis in Patients Presenting to the Emergency Department with Fever. Indian J Crit Care Med 2023;27(3):176–182.

CITATION EXPORT

Anna Paul, Nalini Sarah Newbigging, Audrin Lenin et al.. Role of Neutrophil Gelatinase-associated Lipocalin (NGAL) and Other Clinical Parameters as Predictors of Bacterial Sepsis in Patients Presenting to the Emergency Department with Fever. Indian Journal of Critical Care Medicine : Peer-reviewed, Official Publication of Indian Society of Critical Care Medicine. (2023). https://doi.org/10.5005/jp-journals-10071-24419

AUTHORS

11 · 6 CENTRES

Anna Paul, Nalini Sarah Newbigging, Audrin Lenin, Mahasampath Gowri, Jithin Sam Varghese, Arun Jose Nell, Kundavaram Paul Prabhakar Abhilash, Aditya John Binu, Vignesh Kumar Chandiraseharan, Ramya Iyyadurai, George M Varghese

1–3,8–10Department of General Medicine, Christian Medical College, Vellore, Tamil Nadu, India
4Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, India
5Nutrition and Health Sciences Doctoral Program, Laney Graduate School, Emory University, Atlanta, GA, United States of America
6Department of Clinical Biochemistry, Christian Medical College, Vellore, Tamil Nadu, India
7Department of Emergency, Christian Medical College, Vellore, Tamil Nadu, India
11Department of Infectious Diseases, Christian Medical College, Vellore, Tamil Nadu, India