Nomogram for the Prediction of In-Hospital Incidence of Acute Respiratory Distress Syndrome in Patients with Acute Pancreatitis

Ding, Ning; Guo, Cuirong; Song, Kun; Li, Changluo; Zhou, Yang; Yang, Guifang; Chai, Xiangping

doi:10.1016/j.amjms.2021.08.009

Cited by 12 publications

(32 citation statements)

References 43 publications

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“…Several predictors and prediction models for predicting the incidence of ARDS in patients with specific diseases or injuries have been reported ( 18 , 25 , 26 ). For instance, Majid et al constructed a 3-variable model comprising total body surface area percent, inhalation injury, and von Willebrand factor-A2 to predict ARDS in patients with burn injuries, with an AUC of 0.90.…”

Section: Discussionmentioning

confidence: 99%

“…For instance, Majid et al constructed a 3-variable model comprising total body surface area percent, inhalation injury, and von Willebrand factor-A2 to predict ARDS in patients with burn injuries, with an AUC of 0.90. In addition, Ning et al developed a logistic model to predict the in-hospital incidence of ARDS in patients with acute pancreatitis ( 26 ). In addition, other studies reported the risk factors of ARDS in patients undergoing major surgery or extracorporeal membrane oxygenation ( 16 , 18 , 27 – 29 ).…”

Section: Discussionmentioning

confidence: 99%

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Novel models for early prediction and prevention of acute respiratory distress syndrome in patients following hepatectomy: A clinical translational study based on 1,032 patients

Wang

Zhang²,

Zong³

et al. 2023

Front. Med.

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BackgroundAcute respiratory distress syndrome (ARDS) is a serious organ failure and postoperative complication. However, the incidence rate, early prediction and prevention of postoperative ARDS in patients undergoing hepatectomy remain unidentified.MethodsA total of 1,032 patients undergoing hepatectomy between 2019 and 2020, at the Eastern Hepatobiliary Surgery Hospital were included. Patients in 2019 and 2020 were used as the development and validation cohorts, respectively. The incidence rate of ARDS was assessed. A logistic regression model and a least absolute shrinkage and selection operator (LASSO) regression model were used for constructing ARDS prediction models.ResultsThe incidence of ARDS was 8.8% (43/490) in the development cohort and 5.7% (31/542) in the validation cohort. Operation time, postoperative aspartate aminotransferase (AST), and postoperative hemoglobin (Hb) were all critical predictors identified by the logistic regression model, with an area under the curve (AUC) of 0.804 in the development cohort and 0.752 in the validation cohort. Additionally, nine predictors were identified by the LASSO regression model, with an AUC of 0.848 in the development cohort and 0.786 in the validation cohort.ConclusionWe reported the incidence of ARDS in patients undergoing hepatectomy and developed two simple and practical prediction models for early predicting postoperative ARDS in patients undergoing hepatectomy. These tools may improve clinicians’ ability to early estimate the risk of postoperative ARDS and timely prevent its emergence.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Novel models for early prediction and prevention of acute respiratory distress syndrome in patients following hepatectomy: A clinical translational study based on 1,032 patients

Wang

Zhang²,

Zong³

et al. 2023

Front. Med.

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“…Most AP patients have a mild course of disease, but nearly 20% of patients can experience complications, and those with complications have a mortality rate as high as 60%. 7 , 16 , 17 Most complications cannot be treated by specific drugs; some require surgical intervention, such as endoscopic surgery, and are prone to recurrence after surgery, which adversely affects the quality of life of patients, increasing the economic and psychological burden. Therefore, early prediction of the possible complications in AP patients and early intervention can improve their condition and prognosis.…”

Section: Discussionmentioning

confidence: 99%

Prediction of acute pancreatitis complications using routine blood parameters during early admission

Chen

Ning

et al. 2022

Immunity Inflam & Disease

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Background: There have been many reports on biomarkers for predicting the severity of acute pancreatitis (AP), but few studies on biomarkers for predicting complications; some simple and inexpensive indicators, in particular, are worth exploring. Methods:We retrospectively collected clinical data of 809 AP patients, including medical history and results of routine blood tests, and grouped them according to the occurrence of complications. Differences in clinical characteristics between groups with and without complications were compared using t-test or χ 2 test. Receiver operating curve (ROC) and area under the curve were calculated to evaluate the ability of predicting the occurrence of complications for the routine blood parameters with statistical differences. Then, through univariate and multivariate analyses, independent risk factors closely associated with complications were identified. Finally, we built a three-parameter prediction system and evaluated its ability to predict AP complications.Results: Compared with the group without complications, the patients in the complication group had higher white blood cells, neutrophils, C-reactive protein, and erythrocyte sedimentation rate (ESR), and lower red blood cells and hemoglobin (Hb) (all p < .05), and most of them had severe pancreatitis. In addition, pseudocysts were more common in patients with alcoholic etiology, recurrence, low BMI, and high platelet (PLT) and plateletocrit. Acute respiratory failure was more common in patients with first onset and high mean PLT volume (MPV). Sepsis was more common in patients with lipogenic etiology, high MPV, and low lymphocytes. Infectious pancreatic necrosis was more common in patients with alcoholic etiology. Acute renal failure was more common in patients with monocytes and high MPV and low PLT. Multivariate analysis showed that PLT and ESR were risk factors for

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“… 1 Albumin not only regulates the acid–base balance and fluid distribution in the body, but also serves as a transporter of many substances including drugs and hormones. 2 , 3 Previous studies have explored the relationships between albumin level and clinical outcomes in many disorders including malignant tumor, 4 hepatic disease, 5 pancreatitis, 6 infectious disease 7 and even in COVID-19. 8 One study with 100,529 participants and a median follow-up of 8.5 years revealed that with each 1g/dl decrease in plasma albumin, the hazard ratios (HR) for ischemic heart disease, myocardial infarction and stroke were 1.17, 1.25 and 1.46, respectively.…”

Section: Introductionmentioning

confidence: 99%

Albumin Level is Associated with Short-Term and Long-Term Outcomes in Sepsis Patients Admitted in the ICU: A Large Public Database Retrospective Research

Cao¹,

Su²,

Guo³

et al. 2023

CLEP

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Objective This study aimed to explore the relationship between albumin level with short- and long-term outcomes in sepsis patients admitted in the intensive care unit (ICU) based on a large public database to provide clinical evidence for physicians to make individualized plans of albumin supplementation. Methods Sepsis patients admitted in the ICU in MIMIC-IV were included. Different models were performed to investigate the relationships between albumin and mortalities of 28-day, 60-day, 180-day and 1-year. Smooth fitting curves were performed. Results A total of 5357 sepsis patients were included. Mortalities of 28-day, 60-day, 180-day and 1-year were 29.29% (n = 1569), 33.92% (n = 1817), 36.70% (n = 1966) and 37.71% (n = 2020). In the fully adjusted model (adjusted for all potential confounders), with each 1g/dL increment in albumin level, the risk of mortality in 28-day, 60-day, 180-day and 1-year decreased by 39% (OR = 0.61, 95% CI: 0.54–0.69), 34% (OR = 0.66, 95% CI: 0.59–0.73), 33% (OR = 0.67, 95% CI: 0.60–0.75), and 32% (OR = 0.68, 95% CI: 0.61–0.76), respectively. The non-linear negative relationships between albumin and clinical outcomes were confirmed by smooth fitting curves. The turning point of albumin level was 2.6g/dL for short- and long-term clinical outcomes. When albumin level ≤2.6g/dL, with each 1g/dL increment in albumin level, the risk of mortality in 28-day, 60-day, 180-day and 1-year decreased by 59% (OR = 0.41, 95% CI: 0.32–0.52), 62% (OR = 0.38, 95% CI: 0.30–0.48), 65% (OR = 0.35, 95% CI: 0.28–0.45), and 62% (OR = 0.38, 95% CI: 0.29–0.48), respectively. Conclusion Albumin level was associated with short- and long-term outcomes in sepsis. Albumin supplementation might be beneficial for septic patients with serum albumin<2.6g/dL.

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Nomogram for the Prediction of In-Hospital Incidence of Acute Respiratory Distress Syndrome in Patients with Acute Pancreatitis

Cited by 12 publications

References 43 publications

Novel models for early prediction and prevention of acute respiratory distress syndrome in patients following hepatectomy: A clinical translational study based on 1,032 patients

Novel models for early prediction and prevention of acute respiratory distress syndrome in patients following hepatectomy: A clinical translational study based on 1,032 patients

Prediction of acute pancreatitis complications using routine blood parameters during early admission

Albumin Level is Associated with Short-Term and Long-Term Outcomes in Sepsis Patients Admitted in the ICU: A Large Public Database Retrospective Research

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