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One-year recurrence rate of acute pancreatitis at about 20%. 36% of the patients with recurrent acute pancreatitis will develop into chronic pancreatitis. In addition to negative impact on patient's quality of life, chronic pancreatitis is also associated with the occurrence of pancreatic cancer. The etiology of recurrent acute pancreatitis (RAP) can be divided into mechanical obstructive factors (e.g. cholelithiasis, cholestasis), metabolic abnormality and toxic substance factors (e.g. hyperlipidemia and alcoholism), and other or idiopathic factors. At present, the diagnosis and treatment of RAP remains highly challenging. Early identification and intervention on risk factors of recurrence will be effective in reducing incidence and improving prognosis.
Contrast-enhanced Computed Tomography (CT) can not only provide more imaging information and further assess the severity of acute pancreatitis, but also aid in the differentiation of other diseases associated with acute abdominal pain. In addition, radiomics based on raw radiographic data has become a research hotspot in recent years. The purpose of this study is to establish and validate a deep learning model based on high concentration iopromide-enhanced abdominal CT images which is designed to predict the recurrence of pancreatitis in patients with first episode of pancreatitis within the 1-year follow-up period.
Full description
Primary objective(s) To evaluate the sensitivity and specificity of the deep-learning integrated model established with relevant clinical factors and radiomic features based on the high concentration (370 mgI/ml) Iopromide-enhanced pancreatic CT obtained within 14 days after the first onset of symptoms for quantitative prediction of (the first) recurrence of acute pancreatitis in 12 months follow-up period.
Sample Size:
According to previously published data, the average time of occurrence of RAP is 12.5 ± 3.6 months and one-year recurrence rate of acute pancreatitis is about 20%. In addition, the recurrence rate is estimated to be about 17% within the 12-month follow-up window in this study, when taking into account the clinical experience of our hospital.
The calculation parameters for sample size of the training set in the study are as follows:
The training set, test set and validation set are estimated in a ratio of 5:2:3. The total sample size for this prospective study is 694. According to the order of patient enrollment, the last 200 patients recruited will form the validation set.
Statistical Analyses:
At baseline and follow-up, descriptive statistics will be used to describe the entire population and subgroups of interest. Summary statistics such as mean, median, standard deviation and range will be used to describe continuous variables. Categorical variables will be presented in a frequency table.
The sensitivity, specificity and corresponding 95% CI for prediction of recurrence within 1, 3, 6 and 12 months are calculated based on the model that used both clinical features and/or radiomics features. Only the first recurrence is calculated.
Brief statistics of the quality of CT images will be provided.
• Baseline demographic characteristics Demographic and baseline characteristics will be summarized descriptively. Sensitivity= TP/(TP+FN) Specificity=TN/(TN+FP) Accuracy = (TP+TN)/(TP+FN+TN+FP) TP=True positive TP=True negative FN=False negative FP=False positive TP+FN+TN+FP=Total number of patients Statistical analyses are performed using R software (R Core Team, Vienna, Austria) version 3.4.3 All tests are two-sided. A P value < 0.05 is considered statistically significant.
All therapies will be coded using the World Health Organization - Drug Dictionary (WHO-DD). Medical history and any disease will be coded using the most current version of ICH Medical Dictionary for Regulatory Activities (MedDRA).
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Inclusion criteria
18 -70 years old
The subject met the following three criteria and diagnosed with acute pancreatitis according to the Atlanta Classification of Acute Pancreatitis.
2.1 Abdominal pain indicative of pancreatitis 2.2 Serum levels of amylase or lipase >3 times the upper limit of normal 2.3 Characteristic findings from abdominal imaging (unenhanced CT\MR\ultrasonography)
Referred for an enhanced CT examination with Iopromide 370 in 14 days after symptom onset by clinicians
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Exclusion criteria
694 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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