Dataset Information

Bedside upper gastrointestinal series in the neonatal intensive care unit.

ABSTRACT:

Background

In neonatal intensive care unit (NICU) patients with intubation status, fluoroscopic evaluation for the bowel is limited. This study was to evaluate the utility of bedside upper gastrointestinal (UGI) series with delayed radiographs (DR) for assessing duodenojejunal junction (DJJ) and small bowel passage in NICU patients with nonspecific bowel ultrasonography and contrast enema findings.

Methods

We reviewed clinical and imaging data for bedside UGI with DR of NICU patients from 2014 to 2019. Five abdominal radiographs were obtained at fixed time intervals of immediately after, 1?min, 5?min, 1?h, and 2?h following the administration of 5?cc/kg isotonic water-soluble contrast agent via the nasogastric tube.

Results

Twenty bedside UGI with DR were performed in 17 patients (weight range: 520-3620?g, age range: 0-4?months). Confidence identifying the DJJ was either good (n?=?7) or equivocal (n?=?8) at immediate or 1?min radiographs. The DJJ could not be evaluated in five from four delayed passage (including two meconium plug syndrome and one gastric volvulus) and one inadequate timing. There was only one case of intestinal malrotation, which was not detected on ultrasonography, but detected at the first UGI examination with good DJJ confidence.

Conclusions

Bedside UGI with DR can evaluate intestinal malrotation using immediate and 1?min delay and small bowel passage using 1 and 2?h delay images in NICU patients with nonspecific ultrasonographic and contrast enema findings. The majority with delayed contrast passages can have bowel pathology. Because of a small number of patients in this study, further studies with more infants are needed.

SUBMITTER: Kang C

PROVIDER: S-EPMC7893964 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Bedside upper gastrointestinal series in the neonatal intensive care unit.

Kang Choeum C Yoon Haesung H Shin Hyun Joo HJ Eun Ho Sun HS In Park Kook K Lee Mi-Jung MJ

BMC pediatrics 20210219 1

<h4>Background</h4>In neonatal intensive care unit (NICU) patients with intubation status, fluoroscopic evaluation for the bowel is limited. This study was to evaluate the utility of bedside upper gastrointestinal (UGI) series with delayed radiographs (DR) for assessing duodenojejunal junction (DJJ) and small bowel passage in NICU patients with nonspecific bowel ultrasonography and contrast enema findings.<h4>Methods</h4>We reviewed clinical and imaging data for bedside UGI with DR of NICU patie ...[more]

PMID: 33607968

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Project description:BackgroundPoint of care (POC) glucose meters are routinely used as a screening tool for hypoglycemia in a neonatal setting. Glucose meters however, lack the same accuracy as laboratory instruments for glucose measurement. In this study we investigated potential reasons for this inaccuracy and established a cut off value for confirmatory testing.MethodsIn this prospective study, all patients in the neonatal intensive care unit who had a plasma glucose test ordered were eligible to participate. Demographic information, sample collection information (nine variables) and a recent hematocrit value were recorded for each sample. Glucose measurements were taken at the bedside on the glucose meter (RN PCx) as well as in the laboratory on both the glucose meter (LAB PCx) and the laboratory analyzer (PG). Data were analyzed by simple and mixed-effects regression analysis and by analysis of a receiver operator characteristics (ROC) curve.ResultsThere were 475 samples analyzed from 132 patients. RN PCx values were higher than PG values (mean = 4.9%), while LAB PCx results were lower (mean = -5.2%) than PG values. Only 31% of the difference between RN PCx--PG and 46% of the difference for LAB PCx--PG could be accounted for by the variables tested. The largest proportion of variance between PCx and PG measurements was explained by hematocrit (about 30%) with a greater effect seen at glucose concentrations < or =4.0 mmol/L (< or =72 mg/dL)(48% and 40% for RN PCx and LAB PCx, respectively). The ROC analysis showed that for detection of all cases of hypoglycemia (PG < 2.6 mmol/L)(PG < 47 mg/dL) the PCx screening cut off value would need to be set at 3.8 mmol/L (68 mg/dL) requiring 20% of all samples to have confirmatory analysis by the laboratory method.ConclusionThe large difference between glucose results obtained by PCx glucose meter compared to the laboratory analyzer can be explained in part by hematocrit and low glucose concentration. These results emphasize that the glucose meter is useful only as a screening device for neonatal hypoglycemia and that a screening cut off value must be established.

Project description:IntroductionThis study aims to construct a mortality prediction model for patients with non-variceal upper gastrointestinal bleeding (NVUGIB) in the intensive care unit (ICU), employing advanced machine learning algorithms. The goal is to identify high-risk populations early, contributing to a deeper understanding of patients with NVUGIB in the ICU.MethodsWe extracted NVUGIB data from the Medical Information Mart for Intensive Care IV (MIMIC-IV, v.2.2) database spanning from 2008 to 2019. Feature selection was conducted through LASSO regression, followed by training models using 11 machine learning methods. The best model was chosen based on the area under the curve (AUC). Subsequently, Shapley additive explanations (SHAP) was employed to elucidate how each factor influenced the model. Finally, a case was randomly selected, and the model was utilized to predict its mortality, demonstrating the practical application of the developed model.ResultsIn total, 2716 patients with NVUGIB were deemed eligible for participation. Following selection, 30 out of a total of 64 clinical parameters collected on day 1 after ICU admission remained associated with prognosis and were utilized for developing machine learning models. Among the 11 constructed models, the Gradient Boosting Decision Tree (GBDT) model demonstrated the best performance, achieving an AUC of 0.853 and an accuracy of 0.839 in the validation cohort. Feature importance analysis highlighted that shock, Glasgow Coma Scale (GCS), renal disease, age, albumin, and alanine aminotransferase (ALP) were the top six features of the GBDT model with the most significant impact. Furthermore, SHAP force analysis illustrated how the constructed model visualized the individualized prediction of death.ConclusionsPatient data from the MIMIC database were leveraged to develop a robust prognostic model for patients with NVUGIB in the ICU. The analysis using SHAP also assisted clinicians in gaining a deeper understanding of the disease.

Dataset Information

Bedside upper gastrointestinal series in the neonatal intensive care unit.

Background

Methods

Results

Conclusions

Publications

Bedside upper gastrointestinal series in the neonatal intensive care unit.

Similar Datasets

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