Preexisting diabetes, serum calcium and D-dimer levels as predictable risk factors for pancreatic necrosis of patients with acute pancreatitis: a retrospective study

Xue, Enfu; Shi, Qiao; Guo, Shouliang; Zhang, Xiaoyi; Liu, Chengsi; Qian, Bin; Guo, Xin; Hu, Ning; Jiang, Fang; Ji, Tao; Wang, Weixing

doi:10.1080/17474124.2022.2116314

Cited by 8 publications

(3 citation statements)

References 29 publications

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“…Another study indicated that serum calcium levels elevate the risk of necrosis development by 0.021-fold at values above 2.04 mmol/L. 26 Our research suggests that hypocalcemia at the 48-hour mark of admission is an independent risk factor for the development of NP.…”

Section: Discussionsupporting

confidence: 48%

Development of a Nomogram to Predict the Risk for Acute Necrotizing Pancreatitis

Zhang,

Weng

2024

Gut and Liver

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Background/Aims: Necrotizing pancreatitis (NP) presents a more severe clinical trajectory and increased mortality compared to edematous pancreatitis. Prompt identification of NP is vital for patient prognosis. A risk prediction model for NP among Chinese patients has been developed and validated to aid in early detection.Methods: A retrospective analysis was performed on 218 patients with acute pancreatitis (AP) to examine the association of various clinical variables with NP. The least absolute shrinkage and selection operator (LASSO) regression was utilized to refine variables and select predictors. Subsequently, a multivariate logistic regression was employed to construct a predictive nomogram. The model's accuracy was validated using bootstrap resampling (n=500) and its calibration assessed via a calibration curve. The model's clinical utility was evaluated through decision curve analysis.Results: Of the 28 potential predictors analyzed in 218 AP patients, the incidence of NP was 25.2%. LASSO regression identified 14 variables, with procalcitonin, triglyceride, white blood cell count at 48 hours post-admission, calcium at 48 hours post-admission, and hematocrit at 48 hours post-admission emerging as independent risk factors for NP. The resulting nomogram accurately predicted NP risk with an area under the curve of 0.822, sensitivity of 82.8%, and specificity of 76.4%. The bootstrap-validated area under the curve remained at 0.822 (95% confidence interval, 0.737 to 0.892). This model exhibited excellent calibration and demonstrated greater predictive efficacy and clinical utility for NP than APACHE II, Ranson, and BISAP. Conclusions:We have developed a prediction nomogram of NP that is of great value in guiding clinical decision.

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Section: Discussionsupporting

confidence: 48%

Development of a Nomogram to Predict the Risk for Acute Necrotizing Pancreatitis

Zhang,

Weng

2024

Gut and Liver

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“…[21] Serum calcium, LDH and CRP levels, which were included factors in the final model, have been reported as risk factors for SAP in a number of previous studies. [22][23][24][25] It is worth noting that although several factors were not included in the model that was ultimately constructed, they were also valuable in assessing the severity of AP. The results demonstrated that the D-dimer levels correlated with the severity of HTG-AP (Spearman's correlation, r = 0.403).…”

Section: Discussionmentioning

confidence: 99%

Prediction of severe hypertriglyceridemia-associated acute pancreatitis using a nomogram based on CT findings and blood biomarkers

Dong,

Shen,

Wang

et al. 2024

Medicine

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Hypertriglyceridemia is a common cause of acute pancreatitis (AP). Fatty liver, a manifestation of metabolic syndrome, is related to the severity of AP. The present study aimed to construct an accurate predictive model for severe AP (SAP) by combining the fatty liver infiltration on a computerized tomography (CT) scan with a series of blood biomarkers in patients with hypertriglyceridemia-associated AP (HTG-AP). A total of 213 patients diagnosed with HTG-AP were included in the present retrospective study. Clinical information and imageological findings were retrospectively analyzed. The model was constructed from independent risk factors using univariate analysis, the least absolute shrinkage and selection operator method. Subsequently, the data from the training group of 111 patients with HTG-AP was analyzed using logistic regression analysis. The efficacy of the model was verified using an external validation group of 102 patients through the receiver operating characteristic curve (ROC). Independent predictors, including serum calcium, C-reactive protein, lactate dehydrogenase and liver-to-spleen CT attenuation ratio (L/S ratio), were incorporated into the nomogram model for SAP in HTG-AP. The model achieved a sensitivity of 91.3% and a specificity of 88.6% in the training group. Compared with the Ranson model, the established nomogram model exhibited a better discriminative ability in the training group [area under the curve (AUC): 0.957] and external validation group (AUC: 0.930), as well as better calibration and clinical benefits. The present study demonstrates that the constructed nomogram based on CT findings and blood biomarkers is useful for the accurate prediction of SAP in HTG-AP.

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“…Li Mengke et al [8] found that the AUC of D-dimer was 0.72, the optimal cut-off value was 1.43 μg/L, the sensitivity was 0.58, and the specificity was 0.79, indicating that D-dimer can be used as a predictor of the severity of AP and has good diagnostic efficacy. Xue et al [9] showed that D-dimer was an independent predictor of pancreatic necrosis. The ROC curve was constructed with D-dimer, which predicted the occurrence of pancreatic necrosis in patients with acute pancreatitis, with an AUC of 0.786, an optimal cut-off value of 2.08, and a sensitivity and specificity of 75.86% and 70.8%, respectively.…”

Section: D-dimer (D-d)mentioning

confidence: 99%

Progress in the Study of Laboratory Indicators Related to Acute Pancreatitis

Song,

Tan

2024

JBM

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Acute pancreatitis (AP) is one of the more common gastrointestinal diseases in clinics and is characterized by rapid progression, many complications, and high mortality. When it develops into severe pancreatitis, its prognosis is poor. Therefore, early assessment of the degree of inflammatory response plays a crucial role in the treatment plan and prognosis of patients. More and more studies have shown that the levels of D-dimer (D-D), angiotensin-2 (Ang-2), phosphate, heparin-binding protein (HBP), retinol-binding protein-4 (RBP4), and osteoblastic protein (OPN) are closely related to the severity of acute pancreatitis and can be used as effective indicators for early assessment of AP. In this paper, the research progress of the above indicators in assessing the severity of AP is summarized.

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Preexisting diabetes, serum calcium and D-dimer levels as predictable risk factors for pancreatic necrosis of patients with acute pancreatitis: a retrospective study

Cited by 8 publications

References 29 publications

Development of a Nomogram to Predict the Risk for Acute Necrotizing Pancreatitis

Development of a Nomogram to Predict the Risk for Acute Necrotizing Pancreatitis

Prediction of severe hypertriglyceridemia-associated acute pancreatitis using a nomogram based on CT findings and blood biomarkers

Progress in the Study of Laboratory Indicators Related to Acute Pancreatitis

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