| Literature DB >> 31366007 |
Justyna Wajda1, Paulina Dumnicka2, Małgorzata Maraj3, Piotr Ceranowicz4, Marek Kuźniewski5, Beata Kuśnierz-Cabala6.
Abstract
Acute kidney injury (AKI) is a serious complication of acute pancreatitis (AP), which occurs in up to 70% of patients with severe AP and significantly increases the risk of mortality. At present, AKI is diagnosed based on dynamic increase in serum creatinine and decreased urine output; however, there is a need for earlier and more accurate biomarkers. The aim of the study was to review current evidence on the laboratory tests that were studied as the potential biomarkers of AKI in AP. We also briefly summarized the knowledge coming from the studies including sepsis or ICU patients since severe acute pancreatitis is associated with systemic inflammation and organ failure. Serum cystatin C and serum or urine NGAL have been shown to predict or diagnose AKI in AP; however, this evidence come from the single center studies of low number of patients. Other markers, such as urinary kidney injury molecule-1, cell cycle arrest biomarkers (tissue inhibitor metalloproteinase-2 and urine insulin-like growth factor-binding protein 7), interleukin-18, liver-type fatty acid-binding protein, or calprotectin have been studied in other populations suffering from systemic inflammatory states. In AP, the potential markers of AKI may be significantly influenced by either dehydration or inflammation, and the impact of these factors may be difficult to distinguish from kidney injury. The subject of AKI complicating AP is understudied. More studies are needed, for both exploratory (to choose the best markers) and clinical (to evaluate the diagnostic accuracy of the chosen markers in real clinical settings).Entities:
Keywords: acute kidney injury; acute pancreatitis; biomarkers; diagnostic accuracy; inflammation
Year: 2019 PMID: 31366007 PMCID: PMC6696144 DOI: 10.3390/ijms20153714
Source DB: PubMed Journal: Int J Mol Sci ISSN: 1422-0067 Impact factor: 5.923
The data on the prevalence of acute kidney injury (AKI) in patients with acute pancreatitis (AP).
| Reference | Study Design and Patients | Definition of AKI | Prevalence of AKI | Remarks |
|---|---|---|---|---|
| Lin et al., 2011 [ | Retrospective study of 1734 patients with AP admitted to ICU | AKI was identified using the ICD-9 code 584 (AKI). | 15.05% of ICU patients with AP | Mortality was 23.76% in AP with AKI versus 8.08% in AP without AKI. |
| Pavlidis et al., 2013 [ | Retrospective analysis of 50 patients with SAP admitted to ICU | AKI was defined according to AKIN criteria. | 54% of patients with SAP; 44% of patients with SAP required RRT | AKI more common among non-survivors (100%) than survivors (42%) |
| Zhou et al., 2015 [ | Retrospective multi-center analysis of 414 patients with SAP admitted to ICU | AKI was defined according to AKIN criteria based on serum creatinine. | 69.3% of patients with SAP; 59.2% of patients with SAP required RRT | Mortality was 44.9% in AP with AKI versus 20.5% in AP without AKI |
| Kumar et al., 2015 [ | Retrospective analysis of 72 patients with SAP admitted to a tertiary center | AKI was defined and classified according to the RIFLE criteria | 19.4% of patients with SAP; 13.9% of patients with SAP required RRT | Mortality was 57% in AP with AKI versus 0 in AP without AKI |
| Párniczky et al., 2016 [ | Prospective multicenter study of 600 patients with AP (61% MAP, 30% MSAP, 9% SAP) | Renal failure as an organ complication in patients with SAP; no strict definition given | 36% of patients with SAP | Mortality was 43.8% in SAP with renal failure versus 21.4% in SAP without renal failure |
| Gougol et al., 2017 [ | Prospective observation of 500 AP patients admitted to a tertiary center | Isolated renal failure according to the modified Marshall scoring system | Isolated renal failure reported in 15% of patients with SAP | No deaths in isolated renal failure versus 22.4% mortality in MOF |
| Devani et al., 2018 [ | 3,466,493 patients hospitalized with AP (ICD-9 code) between 2003–2012, from Nationwide Inpatient Sample database | AKI was identified using the ICD-9 codes for AKI (584; 584.5; 584.6; 584.7; 584.8; 584.9) | Prevalence of AKI in AP nearly tripled from 4.1% in 2003 to 11.7% in 2012. Overall prevalence within the study period was 7.9%. | Mortality of patients with AKI complicating AP decreased from 17.4% in 2003 to 6.4% in 2012. |
| Chai et al., 2018 [ | Retrospective analysis of 237 patients with AP (79% MAP, 16% MSAP, 5% SAP) | 2012 KDIGO criteria, any stage | 7.6% of all patients with AP | 50% of patients with AKI had stage 1 AKI according to 2012 KDIGO criteria |
| Manokaran et al., 2018 [ | 100 patients with SAP from tertiary hospital | KDIGO 2012, any stage | 32% of patients with SAP | Mortality 12.5% in SAP with AKI versus 1.5% in SAP without AKI |
Abbreviations: SAP, severe acute pancreatitis; AKIN, Acute Kidney Injury Network; RIFLE, risk, injury, failure, loss of kidney function, end-stage kidney disease; MOF, multi-organ failure; ICD-9, International Classification of Diseases-9; ICU, intensive care unit; MAP, mild acute pancreatitis; MSAP, moderately-severe acute pancreatitis; KDIGO, Kidney Disease: Improving Global Outcomes; RRT, renal replacement therapy.
Figure 1Pathophysiological factors influencing the development of AKI in AP.
The recent evidence on AKI in AP coming from animal studies.
| Reference | Description of the Study and Results |
|---|---|
| Zhang et al., 2014 [ | Sprague-Dawley rats with SAP was induced by retrograde infusion of 5% sodium taurocholate into the bile-pancreatic duct were treated with caspase-1/interleukin-1β-converting-enzyme inhibitor. The inhibitor attenuated intrarenal IL-1β and caspase-1 expression, the histopathologic changes in kidneys and increased serum creatinine observed in SAP. |
| Li et al., 2015 [ | SAP was induced in Male Sprague-Dawley rats by retrograde injection of 5% sodium deoxycholate into bile-pancreatic duct. Serum creatinine and blood urea nitrogen significantly increased in rats with SAP 12 h after surgery. Histological changes in kidney tissue and injury to renal endothelial cells were most pronounced at 36-48 h post-surgery. These changes were preceded by increase in mRNA and protein expression of matrix metalloproteinase-9 (MMP-9), also in active form, and vasodilator-stimulated phosphoprotein (VASP) at 12-24 h post-surgery. |
| Wu et al., 2017 [ | Severe hypertriglyceridemia in ApoC III transgenic mice aggravated kidney injury in the course of AP established by retrograde injection of 0.5% sodium taurocholate to pancreatic duct. ApoC III transgenic mice developed more severe pancreatic damage and more advanced histological changes in the kidneys associated with higher serum creatinine than wild type mice. |
| Kong et al., 2018 [ | Sprague-Dawley rats with AP induced by retrograde infusion of body weight of 3.5% sodium taurocholate solution into the biliary-pancreatic duct were pretreated with antithrombin III (AT III), or AT III was administered postoperatively. Both ways of AT III administration attenuated increase in serum creatinine, renal tubular detachment, brush border loss, and necrosis of tubular cells. |
| Gori et al., 2019 [ | The authors studied the diagnostic utility of urinalysis and urinary gamma glutamyl transpeptidase-to-urinary creatinine (GGT/Cr) in dogs with spontaneously developed AP. Non-survivors showed higher dipstick bilirubin levels and urine protein-to creatinine ratio >2 than survivors. The GGT/Cr was not useful in the prognosis of outcome. |
| Gori et al., 2019 [ | The authors studied the prevalence of AKI complicating spontaneously developed AP in 65 dogs. Higher serum urea and creatinine and oligo- or anuria predicted death of the animals. AKI was diagnosed in 26.2% of dogs. |
Laboratory markers evaluated for prognosis or diagnosis of AKI in patients with AP.
| Marker | Reference | Study Design and Patients | Definition of AKI | Cut-off Value | Diagnostic Sensitivity | Diagnostic Specificity | AUC |
|---|---|---|---|---|---|---|---|
| Serum cystatin C | Chai et al., 2018 [ | Retrospective analysis of 237 patients diagnosed with AP: 5% diagnosed with SAP; 7.6% of all AP patients diagnosed with AKI | KDIGO criteria | 1.865 mg/L | 88.9% | 100% | 0.948 (95% CI: 0.875–1.0) |
| Serum NGAL | Siddappa et al., 2018 [ | Prospective study of 50 patients with AP admitted to tertiary center: 23 patients diagnosed with SAP, 21 with AKI | Modified Marshall scoring system and AKIN criteria | 790.9 ng/mL | 64% | 96% | 0.8 |
| Urine NGAL | 221 ng/mL | 82% | 80% | 0.9 | |||
| Serum procalcitonin | Huang et al., 2013 [ | 305 patients with AP admitted to ICU: 52 cases of AKI | RIFLE criteria | 3.30 ng/mL | 97.2% | 92.3% | 0.986 (95% CI: 0.966–1.000) |
| Serum uromodulin | Kuśnierz-Cabala et al., 2017 [ | Prospective study of 66 patients with AP: 5 diagnosed with SAP, 11 diagnosed with AKI | KDIGO criteria | no data | 0.684 (95% CI: 0.508–0.860) | ||
| Serum uromodulin to creatinine ratio | 0.846 (95% CI: 0.706–0.987) | ||||||
| Serum angiopoietin-2 | Sporek et al., 2016 [ | Prospective study of 65 patients with AP: 5 diagnosed with SAP, 11 diagnosed with AKI | KDIGO criteria | Higher concentrations of angiopoietin-2 was observed in patients with AKI during first 72 h from the onset of AP. OR for AKI 1.12 (1.02–1.24) at 24 h; 1.37 (1.12–1.68) at 48 h, and 1.49 (1.17–1.90) at 72 h per 1 ng/mL increase in angiopoietin-2 | |||
| Serum soluble fms-like tyrosine kinase-1 (sFlt-1) | Dumnicka et al., 2016 [ | Prospective study of 65 patients with AP: 5 diagnosed with SAP, 11 diagnosed with AKI | Modified Marshall scoring system | OR for renal failure at 24 h from the onset of AP symptoms 1.31 (1.06–1.63) per 10 pg/mL increase in sFlt-1 | |||
Abbreviations: AUC, area under the receiver operating characteristic curve; OR, odds ratio; CI, confidence interval; NGAL, neutrophil gelatinase-associated lipocalin.
Novel laboratory markers of renal dysfunction or injury associated with prognosis or diagnosis of AP severity.
| Marker | Reference | Study Design and Patients | Severity Assessment | Cut-off Value | Diagnostic Sensitivity | Diagnostic Specificity | AUC (95% CI) |
|---|---|---|---|---|---|---|---|
| Serum NGAL | Sporek et al., 2016 [ | Prospective observation of 65 adult patients admitted with AP; NGAL was measured at 24, 48 and 72 h from the onset of AP | Moderately severe and severe AP according to 2012 Atlanta Classification versus mild AP | 165 μg/L (at 24 h) | 63% | 80% | 0.727 (0.582–0.872) |
| 183 μg/L (at 48 h) | 90% | 72% | 0.860 (0.773–0.948) | ||||
| 182 μg/L (at 72 h) | 84% | 78% | 0.843 (0.730–0.956) | ||||
| Urine NGAL | Lipinski et al., 2015 [ | Observational cohort study of 104 patients with acute pancreatitis | SAP according to 2012 Atlanta Classification; organ failure according to modified Marshall scoring system | Prediction of SAP: 68.9 ng/mL | 81.2% | 71.5% | 0.750 (0.622–0.890) |
| Prediction of MOF: 86.5 ng/mL | 75% | 76% | 0.870 (0.779–0.964) | ||||
| Prediction of death: 86.5 ng/mL | 75% | 74% | 0.800 (0.632–0.968) |