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Risk assessment in acute pancreatitis†

  1. R. Mofidi,
  2. P. V. Patil,
  3. S. A. Suttie,
  4. R. W. Parks*

Article first published online: 5 JAN 2009

DOI: 10.1002/bjs.6431

Issue

British Journal of Surgery

British Journal of Surgery

Volume 96, Issue 2, pages 137–150, February 2009

Additional Information

How to Cite

Mofidi, R., Patil, P. V., Suttie, S. A. and Parks, R. W. (2009), Risk assessment in acute pancreatitis. Br J Surg, 96: 137–150. doi: 10.1002/bjs.6431

Author Information

  1. Department of Clinical and Surgical Sciences (Surgery), University of Edinburgh, Edinburgh, UK

*Department of Clinical and Surgical Sciences (Surgery), Royal Infirmary of Edinburgh, 51 Little France Crescent, Edinburgh EH16 4SA, UK

  1. †

    Presented in part to a meeting of the International Hepato-Pancreato-Biliary Association, Mumbai, India, February 2008

Publication History

  1. Issue published online: 21 JAN 2009
  2. Article first published online: 5 JAN 2009
  3. Manuscript Accepted: 4 DEC 2008

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Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Definition of severe acute pancreatitis
  6. Severity scoring criteria for acute pancreatitis
  7. Markers of severity of the inflammatory process
  8. Markers of leakage of pancreatic enzymes
  9. Markers of trypsinogen activation
  10. Haemoconcentration
  11. Imaging and the diagnosis of severe acute pancreatitis
  12. Artificial neural networks and other novel predictive models
  13. Overview
  14. Acknowledgements
  15. References

Background:

Acute pancreatitis has a variable natural history and in a proportion of patients is associated with severe complications and a significant risk of death. The various tools available for risk assessment in acute pancreatitis are reviewed.

Methods:

Relevant medical literature from PubMed, Ovid, Embase, Web of Science and The Cochrane Library websites to May 2008 was reviewed.

Results and conclusion:

Over the past 30 years several scoring systems have been developed to predict the severity of acute pancreatitis in the first 48–72 h. Biochemical and immunological markers, imaging modalities and novel predictive models may help identify patients at high risk of complications or death. Recently, there has been a recognition of the importance of the systemic inflammatory response syndrome and organ dysfunction. Copyright © 2009 British Journal of Surgery Society Ltd. Published by John Wiley & Sons, Ltd.

Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Definition of severe acute pancreatitis
  6. Severity scoring criteria for acute pancreatitis
  7. Markers of severity of the inflammatory process
  8. Markers of leakage of pancreatic enzymes
  9. Markers of trypsinogen activation
  10. Haemoconcentration
  11. Imaging and the diagnosis of severe acute pancreatitis
  12. Artificial neural networks and other novel predictive models
  13. Overview
  14. Acknowledgements
  15. References

Acute pancreatitis is a serious condition1. Although it often has a mild and self-limiting course, it may be severe, resulting in local and systemic complications carrying a significant risk of death2–7. Over the past two decades, advances in intensive care and surgical management have resulted in a reduction in mortality and morbidity. Many patients with severe acute pancreatitis now survive the early systemic inflammatory response and enter a second phase of illness dominated by sepsis and the consequences of organ failure8–10. Many authors and several guidelines11–16 have attempted to standardize the management of acute pancreatitis in terms of indications for computed tomography (CT), endoscopic retrograde cholangiopancreatography17–19 and surgical intervention20–22. The success of these efforts depends on the correct prediction of the severity of disease and the identification of patients who are at risk from local and systemic complications23.

Severity scoring systems have been used since the 1970s, the first being the widely used Ranson's criteria24. Others have subsequently been described, many of which are variants of the Ranson system, including the Imrie or Glasgow severity scoring system25–29. More recently, early markers of activation of the systemic inflammatory response30–33, measurement of pancreatic enzymes, and trypsinogen activation have been investigated as putative predictors of severity, with some encouraging results30, 34. In addition, novel predictive models such as artificial neural networks (ANNs) and genetic algorithms have been shown to improve severity stratification in patients with acute pancreatitis35–39. This review assesses the evolution of severity prediction in patients with acute pancreatitis and considers possible future developments in this field.

Definition of severe acute pancreatitis

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Definition of severe acute pancreatitis
  6. Severity scoring criteria for acute pancreatitis
  7. Markers of severity of the inflammatory process
  8. Markers of leakage of pancreatic enzymes
  9. Markers of trypsinogen activation
  10. Haemoconcentration
  11. Imaging and the diagnosis of severe acute pancreatitis
  12. Artificial neural networks and other novel predictive models
  13. Overview
  14. Acknowledgements
  15. References

The Atlanta classification system, proposed following an international symposium in 1992, is based on clinical, radiological and pathological findings40. It has become the standard tool for defining a severe attack of acute pancreatitis. The Atlanta classification defines severe pancreatitis as a score of 3 or more on Ranson's criteria, a score of 8 or more on the Acute Physiology And Chronic Health Evaluation (APACHE) II scoring system, or evidence of organ failure and intrapancreatic pathology. The Atlanta classification also defines the local and systemic complications of acute pancreatitis (Table1)40.

Table 1. Definition of severe acute pancreatitis based on the Atlanta criteria
Severity criteriaDefinitions

  1. The presence of each item by itself constitutes severe acute pancreatitis. APACHE, Acute Physiology And Chronic Health Evaluation; Pa O2, arterial partial pressure of oxygen.

Severity scoring systems
 Ranson score> 3
 APACHE II score> 8
Systemic complications or organ dysfunction
 RespiratoryPa O2 < 60 mmHg (8 kPa)
 RenalSerum creatinine > 177 µmol/l (2 mg/dl) after resuscitation
 CardiovascularSystolic blood pressure < 90 mmHg (after resuscitation)
 Coagulation systemPlatelet count < 100 × 109/l or fibrinogen level < 1 g/l
 Gastrointestinal haemorrhage> 500 ml per 24 h
 Metabolic disturbanceCorrected serum calcium < 1·85 mmol/l (7·5 mg/dl)
 Serum lactate levels > 5 mmol/l
Local complications
 Acute fluid collectionsOccur early in the natural history of acute pancreatitis and lack a fibrous capsule
 PseudocystOccurs at least 4 weeks after the onset of symptoms and has a fibrous capsule
 Pancreatic abscessA localized collection of pus containing little or no necrotic pancreatic material
 Pancreatic necrosisPathological features: diffuse or focal area of non-viable pancreas that may be associated with peripancreatic fat necrosis
 CT features: an area of non-enhancing pancreas measuring > 3 cm in diameter or 30% of pancreatic tissue

Early prediction of severe disease should identify patients who are at risk of subsequent morbidity and death. However, despite their value in standardizing the definitions and terminology associated with acute pancreatitis, the Atlanta criteria have several drawbacks that limit their usefulness41. The main drawback is the lack of clear distinction between predicted and actual severity of severe acute pancreatitis. This lack of distinction is important, as a significant proportion of patients who present with predicted severe acute pancreatitis do not go on to develop severe disease. This may account for the marked variation in the incidence and outcome of severe acute pancreatitis reported from different institutions41, 42. In addition, although the Atlanta criteria incorporate clinical and morphological definitions of local complications of acute pancreatitis, they do not provide exact radiological (CT) definitions of these complications41, 43. This leaves room for individual interpretation, which may be responsible for the relatively poor interobserver agreement in the identification of these complications44. In view of these deficiencies, there is now a large body of opinion that believes the Atlanta classification to be outdated, requiring revision41. International efforts to develop a new classification system are ongoing but should bear fruit in the near future.

Mortality from acute pancreatitis has a bimodal distribution. Early death is related to the development of severe and irreversible multiorgan dysfunction, whereas late death occurs in the second phase of illness that is dominated by sepsis and the consequences of organ failure. Regardless of the timing, death is closely associated with the number of failing organs, plus the severity and reversibility of organ failure8–10. In addition to multiorgan dysfunction, the extent of pancreatic necrosis and septic complications are the major determinants of mortality in acute pancreatitis8–10. Clear definitions of organ dysfunction are of prognostic value and can be a useful tool in the assessment of patient progress. Several organ dysfunction scores have been developed for use in critically ill patients45–47. The most commonly used in the setting of acute pancreatitis are the Multiple Organ Dysfunction Score (MODS) (Table2)45, 46 and the Sequential Organ Failure Assessment (SOFA) (Table3)47.

Table 2. Modified Multiple Organ Dysfunction Score
Organ system involvedScore
12345

  1. Organ dysfunction is quoted as both a score for the individual organ and as the sum of the scores for the individual organ systems; the latter is called the cumulative Multiple Organ Dysfunction Score. PAHR, pressure-adjusted heart rate (heart rate × (right atrial pressure/mean arterial pressure)); Pa O2, arterial partial pressure of oxygen; Fi O2, fraction of inspired oxygen.

Cardiovascular     
 PAHR (beats/min)≤ 1010–1530–1520–30> 30
Respiratory     
 Pa O2/Fi O2 (mmHg)> 300300–225150–22575–150< 75
Renal     
 Creatinine (µmol/l)< 100100–200200–350350–500> 500
Neurological     
 Glasgow Coma Score1514–1312–109–7≤ 6
Haematological     
 Platelet count (×109/l)> 12080–12050–8020–50≤ 20
Hepatic     
 Bilirubin (µmol/l)< 2020–6060–120120–240> 240
Table 3. Sequential Organ Failure Assessment score
Organ system involvedScore
12345

  • The Sequential Organ Failure Assessment score is calculated as the sum of the scores for the individual organs.

  • *

    These values are calculated with ventilatory support. MAP, mean arterial pressure; Pa O2, arterial partial pressure of oxygen; Fi O2, fraction of inspired oxygen.

CardiovascularNo hypotensionMAP < 70 mmHgDopamine or dobutamine (any dose)Dopamine > 5 µg per kg per min or adrenaline (epinephrine) < 0·1 µg per kg per min or noradrenaline (norepinephrine) < 0·1 µg per kg per minDopamine > 15 µg per kg per min or adrenaline > 0·1 µg per kg per min or noradrenaline > 0·1 µg per kg per min
Respiratory     
 Pa O2/Fi O2 (mmHg)> 400400–300300–200200–100*≤ 100*
Renal     
 Creatinine (µmol/l)< 100100–200200–350350–500> 500
Neurological     
 Glasgow Coma Score15 14–13 12–10 9–7≤ 6
Haematological     
 Platelet count (×109/l)> 150150–100100–50 20–50≤ 20
Hepatic     
 Bilirubin (µmol/l)< 20 20–60 60–120120–240> 240

The main difference between MODS and SOFA lies in the evaluation of cardiovascular function. MODS is based on the so-called ‘pressure-adjusted heart rate’, which is the product of heart rate multiplied by the ratio of right atrial pressure to mean arterial pressure48. SOFA uses the absolute mean arterial pressure and therapeutic interventions with vasopressors to quantify cardiovascular function. Being therapy dependent, SOFA is associated with a degree of variability depending on the timing and nature of therapeutic intervention48. On the other hand, the modified MODS evaluates cardiovascular function from the postresuscitation heart rate, the need for inotropic support and the presence of lactic acidosis49.

In addition to the severity of organ dysfunction and the number of organs involved, the dynamic nature of organ dysfunction has been increasingly recognized as an important variable in predicting mortality from acute pancreatitis. Several authors have described the prognostic significance of the distinction between transient and persistent or deteriorating organ dysfunction on mortality from severe acute pancreatitis. Persistent or deteriorating multiorgan dysfunction in the first 7 days after presentation is the most significant predictor of death7–10. In addition, multiorgan dysfunction during the first week of admission is closely related to the development of local complications of severe acute pancreatitis, such as infected pancreatic necrosis; this contributes to the bimodal distribution in mortality7.

Organ dysfunction has been embedded in the definition of severe acute pancreatitis since the advent of the Atlanta criteria. What is new is the classification and scoring of multiorgan dysfunction, and the realization that the cumulative score (sum of the scores of different organ systems) has a strong prognostic value7–10.

Severity scoring criteria for acute pancreatitis

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Definition of severe acute pancreatitis
  6. Severity scoring criteria for acute pancreatitis
  7. Markers of severity of the inflammatory process
  8. Markers of leakage of pancreatic enzymes
  9. Markers of trypsinogen activation
  10. Haemoconcentration
  11. Imaging and the diagnosis of severe acute pancreatitis
  12. Artificial neural networks and other novel predictive models
  13. Overview
  14. Acknowledgements
  15. References

Before severity criteria were introduced, patients with acute pancreatitis were assessed purely on the clinical progression of the illness. Clinical assessment, however, was found to be inadequate in identifying those who would develop severe disease50. Severity scoring systems were developed in an attempt to streamline management by correctly identifying a severe attack early, and anticipating the development of local and systemic complications. Two general types of scoring system have been applied to pancreatitis. The first type comprises systems that are specific to pancreatitis, such as the Ranson and Imrie (Glasgow) severity scoring systems. The second type correlates non-specific physiological variables with outcome; examples are the APACHE II and III systems51, 52.

Ranson and colleagues24 initially evaluated the relationship of 43 clinical and laboratory variables with morbidity and mortality in patients with acute pancreatitis. Eleven of these variables were found to be prognostically significant (Table4) and there was a close correlation between mortality and the number of positive variables. The main problem with Ranson's criteria was that they did not allow prediction until 48 h after admission. Furthermore, these criteria were developed and validated in patients with alcoholic pancreatitis and, although they were accurate at the extremes of scores (less than 3 predicts survival and greater than 6 predicts death), they fared less well at intermediate scores51. Imrie and co-workers25, 53 in Glasgow proposed a similar scoring system, which was validated on patients with gallstone and alcoholic pancreatitis. During the 1980s, the Glasgow severity scoring system was simplified down to nine variables (Table5)54–56 and this version has been shown to be as accurate as Ranson's criteria at predicting death from acute pancreatitis regardless of aetiology25, 55, 56.

Table 4. Ranson's criteria for prediction of severity of acute pancreatitis
On admissionDuring initial 48 h

  1. Each variable carries a score of 1 and an overall score of more than 3 defines severe acute pancreatitis. Pa O2, arterial partial pressure of oxygen.

Age > 55 yearsHaemoglobin falls below 10 mg/dl
White cell count < 16 × 109/lBlood urea nitrogen increases by > 5 mg/dl
Lactate dehydrogenase > 350 units/lCalcium < 8 mg/dl
Aspartate aminotransferase > 250 units/lPa O2 < 60 mmHg (8 kPa)
Glucose > 200 mg/dlBase deficit > 4 mEq/l
 Fluid sequestration > 6 litres
Table 5. Glasgow (Imrie) severity scoring system for acute pancreatitis

  • Each variable has a binary score of 0 or 1. The Glagow (Imrie) outcome score is derived from the sum of scores for all variables at 48 h after presentation.

  • *

    Removed from the revised Glasgow outcome score. Pa O2, arterial partial pressure of oxygen.

Age > 55 years
White cell count > 15 × 109/l
Pa O2 < 60 mmHg (8 kPa)
Serum lactate dehydrogenase > 600 units/l
Serum aspartate aminotransferase > 200 units/l*
Serum albumin < 32 g/l
Serum calcium < 2 mmol/l
Serum glucose > 10 mmol/l
Serum urea > 16 mmol/l

Fan and colleagues57 in Hong Kong have described a scoring system based on the presence of raised serum glucose and urea levels on admission. This system has been claimed to predict the severity of acute pancreatitis as accurately as the Glasgow system. The Hong Kong criteria have the appeal of being extremely simple and able to be used at the time of admission57. The major drawback is that some authors have found them to be inaccurate58, 59.

Prediction of severe acute pancreatitis in Japan is performed using the Japanese Severity Score (JSS) (Table6)60. This uses similar variables to the Ranson system, although the score is calculated differently. The overall accuracy of the JSS for prediction of severity and mortality from acute pancreatitis is similar to that of the Ranson score60, 61.

Table 6. Japanese Severity Score for acute pancreatitis
 Clinical findingsLaboratory measurements

  1. The Japanese Severity Score is calculated as the sum of all points for prognostic factors I, II and III. Severe pancreatitis is defined as having at least one item in group I or more than two in group II. Moderate pancreatitis is defined as no item in group I and only one item in group II. Mild pancreatitis is defined as having none of the items in groups I and II. BUN, blood urea nitrogen; Pa O2, arterial partial pressure of oxygen; SIRS, systemic inflammatory response syndrome.

Prognostic factor IShockBase excess < − 3 mEq/l
 2 points per positive itemImpaired level of consciousnessHaematocrit < 30% after hydration
 Respiratory failureSerum urea > 14 mmol/l (BUN > 40 mg/dl)
 Severe sepsisSerum creatinine > 176 mmol/l (2 mg/dl)
 Disseminated intravascular coagulation 
Prognostic factor II Calcium level < 1·75 mmol/l
 1 point per positive item Serum glucose < 16 mmol/l
 Lactate dehydrogenase > 700 units/l
 Pa O2 < 60 mmHg (on room air)
 Prothrombin time > 15 s
 Platelet count < 100 × 109/l
 Balthazar score D or E
Prognostic factor IIISIRS score > 3 (2 points) 
 Age > 70 years (1 point) 

Ueda and colleagues62 developed a simpler composite scoring system based on three different variables: serum lactate dehydrogenase, blood urea nitrogen and the findings of contrast-enhanced abdominal CT performed in the first 2 days of admission. This scoring system appears to be accurate for identifying patients who are at risk of death from severe acute pancreatitis62.

The APACHE system was developed as a physiologically based classification model for the prediction of mortality in patients with a broad range of disorders in the intensive care setting63. The APACHE score is based on the most abnormal values of 34 variables measured 24–48 h after admission, with weighting based on the degree of deviation from the normal value; points are added for the severity of the patient's baseline health status. This system was validated for perioperative mortality and length of stay in the intensive care unit in a wide range of patients, and was subsequently simplified to form the APACHE II scoring system. This is based on 12 physiological variables, the age of the patient and five organ system-based chronic health points64. The APACHE II scoring system is useful as it offers a calculation of disease severity on admission and on each day thereafter, allowing an assessment of progression of disease. Larvin and McMahon65 and Wilson and co-workers66 have observed that a reducing APACHE II score is associated with mild disease, whereas a rising score within the first 48 h is associated with severe pancreatitis. In addition, by setting different threshold values for the APACHE II score it is possible to predict differing outcomes, such as the development of severe acute pancreatitis and death from severe acute pancreatitis37, 65–67. Despite its promise, the APACHE II scoring system has a major shortcoming—it is designed as a group classification system, not to predict outcome in an individual patient. The APACHE investigators have developed the APACHE III classification system but this seems to be less accurate than APACHE II in assessing a range of outcomes in patients with acute pancreatitis68, 69.

Obesity has been shown to be an independent predictor of death and the development of severe acute pancreatitis. A body mass index (BMI) greater than 30 kg/m2 is associated with an increased risk of developing acute pancreatitis as well as being an independent predictor of mortality from that disease70. A modification to the APACHE II scoring system has been proposed that includes a factor for obesity. The ‘APACHE-O’ scale adds 1 point for a BMI of 26–30 kg/m2 (defined as overweight) and 2 points for a BMI over 30 kg/m2 (defined as obese)71, 72. Johnson and colleagues72 have reported that this system improves severity prediction. APACHE-O has been validated by several other authors and has been recognized as better in terms of severity prediction than conventional APACHE II.

All of the conventional severity scoring systems for acute pancreatitis depend on a combination of measures of the severity of the systemic inflammatory response and organ dysfunction. To this is added a few pancreatitis-related variables, such as serum calcium and lactate dehydrogenase, at specific times following admission, in order to predict mortality from acute pancreatitis. The presence of a persistent systemic inflammatory response syndrome or multiorgan dysfunction is associated with a higher risk of death8–10, 73, 74.

Markers of severity of the inflammatory process

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Definition of severe acute pancreatitis
  6. Severity scoring criteria for acute pancreatitis
  7. Markers of severity of the inflammatory process
  8. Markers of leakage of pancreatic enzymes
  9. Markers of trypsinogen activation
  10. Haemoconcentration
  11. Imaging and the diagnosis of severe acute pancreatitis
  12. Artificial neural networks and other novel predictive models
  13. Overview
  14. Acknowledgements
  15. References

C-reactive protein (CRP) is an acute-phase reactant that is synthesized by hepatocytes in response to circulating interleukin (IL) 1 and IL-6. CRP is the most popular and widely available marker of severity of acute pancreatitis in use today30, 34, 66, 75. It appears to be a useful discriminator of disease severity at 48 h after onset of symptoms, with an accuracy similar to that of the APACHE II score66. Cut-off levels reported to distinguish between mild and severe disease vary between 120 and 210 mg/l30, 34, 75–77. However, levels on admission are a poor predictor of severity of disease as raised CRP levels are dependent on hepatic synthesis secondary to circulating cytokines9.

IL-6 is the principal cytokine mediator of the synthesis of acute-phase proteins such as fibrinogen, serum amyloid A and CRP. It can be measured in serum and urine using a commercially available radioimmunoassay30. IL-6 levels in serum are reported to discriminate between mild and severe attacks of acute pancreatitis within 24 h of admission. Serum (and urine) levels peak in the first 48 h and tend to decline rapidly unless pancreatic necrosis, a pancreatic abscess or infected necrosis develops. Patients with mild disease have undetectable serum levels of IL-6 and serum levels have been shown to reflect the severity of an attack of acute pancreatitis with a relatively high degree of accuracy30, 78–80. Assays suitable for routine clinical use or near patient assessment are not yet available.

Tumour necrosis factor (TNF) α, a predominantly macrophage-derived cytokine, is believed to play a major role in mediating many of the pathophysiological responses to injury and sepsis30, 81. There are reports suggesting some correlation between serum TNF-α levels and the severity of acute pancreatitis81–84. However, the value of TNF-α in predicting severity of acute pancreatitis has not been assessed in any large-scale comparative studies. To date, it remains only of research interest.

IL-8 is the principal secondary mediator of TNF-α-induced neutrophil activation80. It has been shown in several studies to be raised in the course of acute pancreatitis79, 82 and to correlate with clinical outcome85.

Mentula and colleagues31 assessed the value of 19 prognostic variables in predicting the development of organ failure in patients with acute pancreatitis. The resulting prognostic model, which was based on serum calcium and IL-10 levels, was reported to be comparable to any of the more complex predictive models and was more accurate than APACHE II scores in predicting the development of organ failure.

Raised levels of procalcitonin (PCT), the inactive propeptide of the active hormone calcitonin, have been found in the sera of patients with severe bacterial and fungal infections, and in patients with multiple organ dysfunction syndrome86–88. PCT has been assessed as a potential marker for predicting severity, and hence outcome, in patients with acute pancreatitis of all aetiologies, with varying degrees of success89, 90. Several studies suggest that the serum PCT level on admission is a more accurate indicator of probable severity in acute pancreatitis than other predictive markers, such as CRP and APACHE II scores32, 91–93. This, however, has not been a universal observation93, 94.

There is some evidence to suggest that PCT may be of more value as a predictor of outcome in specific subgroups of patients with acute pancreatitis. Rau and co-workers32, 95 have reported in patients with severe acute pancreatitis that serum PCT levels are able to distinguish between those who will develop infected pancreatic necrosis and those with sterile pancreatic necrosis, although this is not a universally held view96. Potential reasons for the discrepancy between studies may relate to variation in the definition of severe acute pancreatitis, as well as variation in treatment. Different aetiologies of acute pancreatitis may affect serum levels of PCT differently97; ongoing biliary sepsis, for instance, has a marked influence on PCT levels96, 97.

Before PCT enters mainstream usage, further large trials are required to elucidate the optimum time point of measurement, whether it needs to be monitored over a short period of time, and the ideal cut-off values that best predict progression to severe acute pancreatitis.

Markers of leakage of pancreatic enzymes

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Definition of severe acute pancreatitis
  6. Severity scoring criteria for acute pancreatitis
  7. Markers of severity of the inflammatory process
  8. Markers of leakage of pancreatic enzymes
  9. Markers of trypsinogen activation
  10. Haemoconcentration
  11. Imaging and the diagnosis of severe acute pancreatitis
  12. Artificial neural networks and other novel predictive models
  13. Overview
  14. Acknowledgements
  15. References

Although serum amylase and lipase levels have been used for years to diagnose acute pancreatitis, serum levels of either enzyme have never been associated with severity of the disease process98. Trypsin is a proteolytic enzyme that is secreted as the proenzyme trypsinogen. Its premature activation is thought to be a key event in the pathogenesis of acute pancreatitis30, 98. The isosyme trypsinogen 2 (anionic trypsinogen) is known to be raised in the serum and urine of patients with acute pancreatitis compared with trypsinogen 1 (cationic trypsinogen). Furthermore, urinary trypsinogen 2 levels appear to be significantly higher in patients who are destined to progress to a severe course99–102. However, there is a significant degree of overlap in serum trypsinogen 2 levels between mild and severe disease. As a result, serum trypsinogen 2 levels are more valuable as a diagnostic tool for acute pancreatitis than for prediction of disease severity2.

Markers of trypsinogen activation

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Definition of severe acute pancreatitis
  6. Severity scoring criteria for acute pancreatitis
  7. Markers of severity of the inflammatory process
  8. Markers of leakage of pancreatic enzymes
  9. Markers of trypsinogen activation
  10. Haemoconcentration
  11. Imaging and the diagnosis of severe acute pancreatitis
  12. Artificial neural networks and other novel predictive models
  13. Overview
  14. Acknowledgements
  15. References

Markers of trypsinogen activation appear very early after the onset of acute pancreatitis. Their levels are maximal 1–2 days after the onset of pain and then decrease very quickly, irrespective of the course of the disease30. This rapid decrease gives them a limited ‘diagnostic window’. However, given that the first 24–48 h is when the assessment of severity of acute pancreatitis is of crucial clinical importance, markers of trypsinogen activation have the potential to become important diagnostic and prognostic tools30. Trypsinogen activation peptide (TAP) is a small peptide that is cleaved from trypsinogen during its activation72, 103, 104. In a large multicentre observational study, Neoptolemos and co-workers34 found raised urinary TAP 24 h after symptom onset to be an accurate predictor of severity in acute pancreatitis. Several authors have reported a significant degree of correlation between the levels of serum trypsin–α1-protease inhibitor complexes and severity of acute pancreatitis105. Levels of this complex are usually raised at a very early stage, but high levels have also been noted in patients with perforated ulcers and, to a lesser extent, in patients with biliary tract disease. This reduces its clinical usefulness105.

Carboxypeptidase B activation peptide is the largest activation peptide released from any pancreatic proenzyme30. It is very stable in serum and urine. Three recent retrospective studies have suggested its usefulness as a prognostic tool in acute pancreatitis106–108.

Haemoconcentration

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Definition of severe acute pancreatitis
  6. Severity scoring criteria for acute pancreatitis
  7. Markers of severity of the inflammatory process
  8. Markers of leakage of pancreatic enzymes
  9. Markers of trypsinogen activation
  10. Haemoconcentration
  11. Imaging and the diagnosis of severe acute pancreatitis
  12. Artificial neural networks and other novel predictive models
  13. Overview
  14. Acknowledgements
  15. References

The importance of a raised admission haematocrit as a marker of severity of acute pancreatitis has been known for over 50 years109, 110. Animal models have shown that a rise in the haematocrit occurs within the first 2 h of pancreatic injury, significantly earlier than systemic inflammatory or haemodynamic manifestations of acute pancreatitis111–113. An admission haematocrit of over 47 per cent is a reliable predictor of the development of severe acute pancreatitis, and failure of the admission haematocrit to reduce after resuscitation or within the first 24 h predicts the development of local and systemic complications. Organ failure is rare in those who do not experience haemoconcentration within the first 24 h of admission114.

It has subsequently been recognized that a raised haematocrit on admission, or within the first 24 h, as a single binary value compares well with APACHE II and Ranson's criteria in predicting the severity of acute pancreatitis114–117. It also correlates well with the subsequent development of pancreatic necrosis114, 118, although this has not been a universal finding119. Brown and colleagues120 have used admission haematocrit together with the presence of obesity (BMI over 30 kg/m2) and pleural effusions to develop the PANC 3 score. They claim that this is an accurate early predictor of severe acute pancreatitis120. The attractiveness of using the haematocrit as a predictor of severity is that it is readily obtainable in all patients who present with acute pancreatitis and it appears to be highly specific.

Imaging and the diagnosis of severe acute pancreatitis

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Definition of severe acute pancreatitis
  6. Severity scoring criteria for acute pancreatitis
  7. Markers of severity of the inflammatory process
  8. Markers of leakage of pancreatic enzymes
  9. Markers of trypsinogen activation
  10. Haemoconcentration
  11. Imaging and the diagnosis of severe acute pancreatitis
  12. Artificial neural networks and other novel predictive models
  13. Overview
  14. Acknowledgements
  15. References

Failure of enhancement of the pancreatic parenchyma during the arterial phase of intravenous contrast-enhanced CT indicates pancreatic necrosis. This predicts a severe clinical course, especially when over half of the gland is involved121. Contrast-enhanced CT has been considered the ‘gold standard’ for diagnosing pancreatic necrosis and identifying peripancreatic collections122 (Fig.1). It has a near 100 per cent sensitivity and positive predictive value for the diagnosis of necrosis. Other radiological features observed in severe acute pancreatitis include diffuse enlargement of the pancreas, irregularity of the pancreatic contour and loss of peripancreatic fat planes, heterogeneous areas of decreased density within the pancreas and variable, ill defined collections122. CT assessment correlates with the clinical course of the disease and recognized variables of disease severity. Disease severity can be graded according to the Balthazar122 (Table7) and Helsinki123 systems, which are based on CT findings.

thumbnail image

Figure 1. Contrast-enhanced computed tomogram of upper abdomen revealing necrotic non-enhancing pancreatic tissue surrounded by a rim of enhancement (arrowhead). In addition, gas bubbles visible in pancreatic tissue are suggestive of infected pancreatic necrosis (arrows)

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Table 7. Balthazar computed tomography grading system for severity of acute pancreatitis
GradeAppearance on computed tomography
ANormal
BGland enlargement, small intrapancreatic fluid collections
CPeripancreatic inflammation, > 30% pancreatic necrosis
DSingle extrahepatic fluid collection, 30–50% pancreatic necrosis
EExtensive extrapancreatic fluid collections, > 50% pancreatic necrosis

Contrast-enhanced CT for predicting acute severe pancreatitis is subject to certain time constraints. CT-based classification systems have the highest diagnostic and predictive accuracy when the scan is performed 6–10 days after the onset of disease. Early scanning for prediction of severity is limited because the full extent of pancreatic necrosis may not develop within the first 48 h of presentation. Despite this, a number of authors have reported that early scanning, even when performed without the use of contrast enhancement, can predict mortality in severe acute pancreatitis123–125. A number of scoring systems incorporate the findings of early abdominal CT62, 119, 124, 125. It should be recognized that a relatively small proportion of patients with acute pancreatitis develop necrosis. Universal CT would result in a significant number of negative investigations. Furthermore, the extent of devitalized gland does not necessarily correlate with the development of multiple organ dysfunction syndrome or risk of early death from acute panceatitis126. Magnetic resonance imaging may predict severity and outcome of acute pancreatitis127 with the additional advantage of identifying choledocholithiasis (Fig.2)128 and pancreatic haemorrhage127.

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Figure 2. Magnetic resonance cholangiopancreatogram in a patient with acute pancreatitis, revealing a common bile duct calculus (arrow)

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Artificial neural networks and other novel predictive models

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Definition of severe acute pancreatitis
  6. Severity scoring criteria for acute pancreatitis
  7. Markers of severity of the inflammatory process
  8. Markers of leakage of pancreatic enzymes
  9. Markers of trypsinogen activation
  10. Haemoconcentration
  11. Imaging and the diagnosis of severe acute pancreatitis
  12. Artificial neural networks and other novel predictive models
  13. Overview
  14. Acknowledgements
  15. References

ANNs are a family of data analysis algorithms. They are designed to resemble biological nervous systems129–131. They differ in structure and function from conventional data analysis models, as ANNs are able to learn from the data presented to them, thereby improving their predictive ability. ANNs have been used in medicine in a wide variety of clinical situations as decision support aids to analyse complex clinical problems132–137.

Several authors have used ANNs to develop predictive models for the assessment of patients with acute pancreatitis, with varying degrees of success35–39. Pofahl and colleagues138 used a simple ANN model and found it reasonably accurate in predicting the duration of inpatient stay, which was used as a surrogate marker of disease severity. They reported that the accuracy of an ANN model was similar to that of the APACHE II and Ranson scores. Similarly, Keogan and co-workers35 used an ANN to identify patients with acute pancreatitis whose hospital stay exceeded the mean of 8·4 days. They did not find any difference between the predictive ability of the ANN and a stepwise linear discriminate analysis. Both of these studies were limited by their small size and the retrospective nature of the study design35.

ANNs can predict mortality in the early phase of predicted severe acute pancreatitis; they appear to be more accurate than the APACHE II and Ranson systems36. One recent study suggests that ANNs are significantly more accurate than conventional scoring systems (APACHE II and Glasgow outcome scores) at predicting the development of severe acute pancreatitis, multiorgan dysfunction and death37. More complex predictive models, such as genetic algorithms, are also accurate predictors of outcome39. Pearce and co-workers139 used a kernel logistic regression model, which combined admission values of selected components of APACHE II and CRP, to predict severe acute pancreatitis; their model was significantly more accurate than APACHE II scores in predicting severe acute pancreatitis. The most likely future role for ANNs is as decision support aids to identify patients with severe disease.

Overview

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Definition of severe acute pancreatitis
  6. Severity scoring criteria for acute pancreatitis
  7. Markers of severity of the inflammatory process
  8. Markers of leakage of pancreatic enzymes
  9. Markers of trypsinogen activation
  10. Haemoconcentration
  11. Imaging and the diagnosis of severe acute pancreatitis
  12. Artificial neural networks and other novel predictive models
  13. Overview
  14. Acknowledgements
  15. References

When Ranson developed his prognostic scoring system over 30 years ago for the early identification of patients with severe pancreatitis, his aim was to evaluate the role of early operative intervention140. Although early surgery is no longer practised, scoring systems are still being used in clinical practice. The interest in new biological markers and predictive models for identifying severe acute pancreatitis testifies to the continued clinical importance of early severity prediction. Early identification facilitates protocol-guided care and streamlined resource utilization by targeting the 20 per cent of patients who will develop severe disease141–143.

Early recognition and accurate grading of organ dysfunction should play a central role in identifying patients with severe acute pancreatitis and charting their progress in the critical care setting. Among the biochemical markers of significance, IL-6, IL-10, PCT and TAP are most likely to be used in clinical practice as predictors of severity. They have already reached clinical use. In addition, newer investigative modalities, such as microarray analysis in transcriptional profiling of genes related to molecular and pancreatic function, may act as surrogate markers of severity in acute pancreatitis. The clinical application of such modalities is, however, some years away144–147.

It is likely that novel predictive models such as ANNs will play a role in the management of acute pancreatitis. They may permit the identification of patients who require transfer to a specialist unit or need critical care support. They may identify those suitable for novel therapies and clinical trials. Each of these roles is likely to require a different prognostic model with different topographies, input values and predictive power. Some of the new biochemical markers of severity for acute pancreatitis may be included as input variables in these ANNs.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Definition of severe acute pancreatitis
  6. Severity scoring criteria for acute pancreatitis
  7. Markers of severity of the inflammatory process
  8. Markers of leakage of pancreatic enzymes
  9. Markers of trypsinogen activation
  10. Haemoconcentration
  11. Imaging and the diagnosis of severe acute pancreatitis
  12. Artificial neural networks and other novel predictive models
  13. Overview
  14. Acknowledgements
  15. References
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