Review
Copyright ©The Author(s) 2021.
World J Gastroenterol. Aug 14, 2021; 27(30): 5019-5036
Published online Aug 14, 2021. doi: 10.3748/wjg.v27.i30.5019
Table 1 Revised Atlanta classification and determinant-based classification of acute pancreatitis
Revised Atlanta classification of disease severity
Mild APNo organ failure
No local or systemic complications
Moderately severe APOrgan failure that resolved within 48 h (transient organ failure) and /or
Local or systemic complications without persistent organ failure
Severe APPersistent organ failure > 48 h
Single organ failure
Multiple organ failure
A modified Marshal score defines a persistent organ failure
Determinant-based classification of disease severity
RACAPDBCAPS
Mild APMild AP
Absence of organ failureAbsence of organ failure
Absence of local complicationsAbsence of (peri-) pancreatic necrosis
Moderately severe APModerate AP
Local complications and/orSterile (peri-) pancreatic necrosis and/or
Transient organ failureTransient organ failure
Severe APSevere AP
Persistent organ failurePersistent organ failure or
Infected (peri-) pancreatic necrosis
Critical AP persistent organ failure
Infected (peri-) pancreatic necrosis
Table 2 Prediction scoring systems used in acute pancreatitis diagnosis
No.
Multifactorial scoring system
Timeline
Threshold
Area under the curve
Ref.
1Ranson score48 h≥ 30.81–0.88[33-35]
2Glasgow score48 h20.73–0.784[36,37]
3Acute Physiology and Chronic Health Evaluation-II score (APACHE-II)24 h70.80–0.895[33,38,39]
4Acute Physiology and Chronic Health Evaluation II score-Obesity (APACHE:-O)24 h70.893[40]
5Bedside Index of Severity score (BISAP)24 h≥ 30.79–0.875[33-35,41]
6Pancreatitis Activity Scoring System (PASS)24 h> 1600.71[36]
7Systemic inflammatory response syndrome (SIRS)24 h≥ 20.73[34,39]
Table 3 Blood biomarkers predicting disease severity in acute pancreatitis
No.
Blood biomarkers
Timeline
Threshold
Area under the curve
Ref.
1Interleukin 8Preoperative196 pg/mL0.778[42]
2Interleukin 624 h50 pg/mL0.9[39]
3Hepcidin24 h234.4 ng/mL0.82[43]
4Red blood cell distribution width24 h13.35%0.787[44]
5Procalcitonin24 h1.77 ng/mL0.797 [45]
6Blood urea nitrogen24 h5.945 mg/dL0.677[44]
7Oleic acid chlorohydrin24 h32.40 nM1[46]
8C-reactive protein24 h150 mg/L0.61[47]
9C-reactive protein48 h150 mg/L0.73–0.91[33,39,47]
Table 4 MicroRNAs used as biomarkers in the diagnosis of acute pancreatitis
No.
miRNAs
Patients
Sample
Expression change
Reference gene
Ref.
1miR-216aAPPlasmaUpNone[49]
2miR-551b-5pAPPlasmaUpmiR-16[50]
3miR-216a-5p, miR-375, and miR-551b-5pAPSerumUpmiR-103a-3p[51]
4miR-7, miR-9, miR-122, and miR-141APSerumUpExogenous reference genes[52]
5miR-216aAPPlasmaUpU6[53]
6miR-551-5pAPPBMC-UpU6[54]
7miR-155APSerumUpU6[55]
8miR-29aAPPlasmaUpU6[56]
9miR-24-3p, miR-222-3p, miR-361-5p, and miR-1246HTG-APSerumUpU6[57]
10miR-1260b, miR-762, miR-22-3p, miR-23b, and miR-23aAP-associated ALISerumUpU6[58]
11miR-92b, miR-10a, and miR-7APPlasmaDownmiR-16[50]
12miR-155APSerumDownNot mentioned[59]
13miR-181a-5pHTG-APSerumDownU6[57]
14miR-550a, miR-324-5p, miR-484, miR-331-3p, miR-140-3p, miR-342-3p, and miR-150AP-associated ALISerumDownU6[58]
15miR-127AP-associated ALI PlasmaDownmiR-16[60]
Table 5 Altered microbiome composition in acute pancreatitis vs healthy controls
No.Techniques used for microbiome profilingHealthy controlAcute pancreatitisRef.
1qPCR (Fecal samples)FirmicutesFirmicutes[84]
BacteroidetesBacteroidetes
ProteobacteriaProteobacteria
ActinobacteriaActinobacteria
TenericutesTenericutes
216S rRNA gene sequencing (Fecal samples)ProteobacteriaBacteroidetes[83]
Proteobacteria
Escherichia/Shigella
Enterococcus
Enterobacteriaceae
Prevotella
Faecalibacterium
Bifidobacterium
316S rRNA gene sequencing (Fecal samples)NABacteroidetes[85]
Proteobacteria
Firmicutes
Actinobacteria
416S rRNA gene sequencing (Fecal samples)NAEnterobacteriaceae[21]
Enterococcus
Bifidobacteria
Table 6 Altered microbiome composition observed in acute pancreatitis of increasing severity
No.Techniques used for microbiome profilingMAPMSAPSAPRef.
1qPCR (Fecal samples), performed only on MAP and SAP patientsEnterococcusNAEnterococcus[79]
EnterobacteriaceaeEnterobacteriaceae
BifidobacteriumBifidobacterium
216S rRNA gene sequencing (Fecal samples)FinegoldiaNAAcinetobacter[83]
Stentrophomonas
Geobacillus
Bacteroides
Alloprevotella
Blautia
Gemella
316S rRNA sequencing (Fecal sample)EnterobacteriaceaeNAEnterobacteriaceae[85]
EnterococcusEnterococcus
BifidobacteriumBifidobacterium
Blautia
416S rRNA gene sequencing (Rectal swab)BacteroidesBacteroidesBacteroides[82]
Escherichia/ShigellaEscherichia/ShigellaEscherichia/Shigella
EnterococcusEnterococcusEnterococcus
Eubacterium hallii
FinegoldiaAnaerococcusAcinetobacter
Stenotrophomonas
BlautiaEubacterium halliiBacteroides
Blautia
5Shotgun metagenomics (Fecal sample)ThermoproteiSulfolobusSulfolobus[86]
CrenarchaeotaMethanobrevibacter ruminantiumMethanomicrobiales - archaeon 53_19
StreptococcusMethanosarcina - ThermophilaEnterococcus
Anaerostipes hadrusAnaerostipes hadrusBlautia
Escherichia coli