Propensity‐Score Matched Comparative Study on Effects of Intravenous Human Serum Albumin Administration in Critically Ill Adult Patients Receiving Parenteral Nutrition

Antonio, Javier; Echeverría-Esnal, Daniel; Barceló-Vidal, Jaime; Fernández-Sala, X

doi:10.1002/jpen.1425

Cited by 2 publications

(2 citation statements)

References 29 publications

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“…HSA solutions have been used worldwide for treating critically ill patients since the 1940s. Intravenous administration of HSA solution increases circulating serum albumin levels in critically ill patients 17,110 . Treatment guidelines for management of critically ill patients recognise a role for HSA in the management of patients with sepsis, albeit mostly with weak recommendations based on moderate or low quality of evidence 42,[111][112][113] .…”

Section: Effects Of Human Albumin Solutions For Fluid Managementmentioning

confidence: 99%

Phases of fluid management and the roles of human albumin solution in perioperative and critically ill patients

Wiedermann¹

2020

Current Medical Research and Opinion

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Objective: Positive fluid balance is common among critically ill patients and leads to worse outcomes, particularly in sepsis, acute respiratory distress syndrome, and acute kidney injury. Restrictive fluid infusion and active removal of accumulated fluid are being studied as approaches to prevent and treat fluid overload. Use of human albumin solutions has been investigated in different phases of restrictive fluid resuscitation, and this narrative literature review was undertaken to evaluate hypoalbuminemia and the roles of human serum albumin with respect to hypovolemia and its management.

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Section: Effects Of Human Albumin Solutions For Fluid Managementmentioning

confidence: 99%

Phases of fluid management and the roles of human albumin solution in perioperative and critically ill patients

Wiedermann¹

2020

Current Medical Research and Opinion

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“…Finally, we picked the most common used laboratory tests performed on patients, HGB and PLR in blood routine, as well as the traditional nutritional marker albumin. 6 Although CRP was closely related to nutritional status, we did not include it in the modeling for two reasons: First, PLR can also reflect the inflammatory status and correlates well with CRP, which means it is a suitable substitute of CRP; 7 on the other hand, including CRP may result in a reduction in the number of included patients, which was not conducive to subsequent generalizability. We also included FFMI, which is an index obtained from bioelectrical impedance analysis (BIA) of body composition.…”

Section: Discussionmentioning

confidence: 99%

A Predictive Model for Qualitative Evaluation of PG-SGA in Tumor Patients Through Machine Learning

Liu¹,

Li²,

Ji³

et al. 2022

CMAR

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Objective Patient-Generated Subjective Global Assessment (PG-SGA) was a nutritional status assessment technique specifically tailored for patients with oncology. The goal of this study was to develop a machine learning (ML) prediction model for predicting PG-SGA categorization of patients with tumor. Methods From 2014 to 2020, patients at the First Hospital of Jilin University performed laboratory testing, bioelectrical impedance, physical measures, and the PG-SGA scale. A total of 8230 patients were involved in the study. Patients with missing or partial data were removed, leaving 7287 patients, of which 3743 were males and 3544 were females. ML was used to design a clinical prediction model for PG-SGA categories. Results Through the least absolute shrinkage and selection operator (LASSO) and the correlation matrix, 135 variables were screened and 6 variables were retained; ML was performed among the remaining variables. The accuracy of neural network prediction models was 70.3% and 70.4% for males and females in the training cohort, respectively, and 74.4% and 73.2% for males and females in the validation cohort, respectively. The area under curve (AUC) of males was 0.87 for PG-SGA scores “0–3”, 0.70 for PG-SGA scores “4–8” and 0.74 for PG-SGA scores “>8”. As for females, the AUC was 0.85 for PG-SGA scores “0–3”, 0.65 for PG-SGA scores “4–8” and 0.76 for PG-SGA scores “>8”. The results of confusion matrix showed that the models were of good predictive validity. The prediction model was nearly 90% accurate for predictions that do not require nutritional support. Conclusion We demonstrated that neural network learning is the best clinical prediction model using ML. The model can work as a prediction for the PG-SGA classification of patients with cancer and can be promoted further in the clinic.

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Propensity‐Score Matched Comparative Study on Effects of Intravenous Human Serum Albumin Administration in Critically Ill Adult Patients Receiving Parenteral Nutrition

Abstract: Patients receiving IV HSA and PN for several days increased serum albumin level, but decreased non-serum-albumin plasma protein levels. In addition, bilirubin clearance could be slightly impaired in these patients.

Cited by 2 publications

References 29 publications

Phases of fluid management and the roles of human albumin solution in perioperative and critically ill patients

Phases of fluid management and the roles of human albumin solution in perioperative and critically ill patients

A Predictive Model for Qualitative Evaluation of PG-SGA in Tumor Patients Through Machine Learning

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