Diagnostic Accuracy of Neutrophil-Creatinine Index for Predicting Severe Acute Pancreatitis Using the Revised Atlanta Classification As Gold Standard

The NCI is a simple and inexpensive parameter that can predict SAP with high accuracy at admission. It may serve as a practical adjunct to existing scores and biomarkers, especially in resource-limited settings.

Authors

Institutions

Publication Details

Journal
Cureus
Published
2025-11-07
DOI
https://doi.org/10.7759/cureus.96303
Primary Topic
Pancreatitis Pathology and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Diagnostic Accuracy of Neutrophil-Creatinine Index for Predicting Severe Acute Pancreatitis Using the Revised Atlanta Classification As Gold Standard

Tashfeen Farooq, Iffat Noureen, Rameez Imtiaz, Muhammad Hanif et al.
Cureus
Pancreatitis Pathology and Treatment
article

Diagnostic Accuracy of Neutrophil-Creatinine Index for Predicting Severe Acute Pancreatitis Using the Revised Atlanta Classification As Gold Standard

Tashfeen Farooq, Iffat Noureen, Rameez Imtiaz, Muhammad Hanif, Fatima Rauf, Suman Aamir, Muhammad Saeed, Usman Qureshi, Huma Sabir Khan
article en

Abstract

The NCI is a simple and inexpensive parameter that can predict SAP with high accuracy at admission. It may serve as a practical adjunct to existing scores and biomarkers, especially in resource-limited settings.

CureusVol. 17(11)
Rawalpindi Medical University (PK), Red Deer Regional Hospital (CA), Benazir Bhutto Hospital (PK)
Openalex Percentile: Top 49%
Pancreatitis Pathology and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.