Prognostic Performance of NUTRIC Score in Quantifying Malnutrition Risk in the Critically Ill in Congruence With the Bioelectrical Impedance Analysis

Experiences, barriers and expectations regarding current patient monitoring systems among ICU nurses in a University Hospital in Lebanon: a qualitative study

Purpose

The aim of the study is to assess the experiences, barriers, and expectations regarding current patient monitoring systems among intensive care unit nurses at one university hospital.

Methods

A qualitative exploratory study approach was adopted to test the research questions.

Results

Intensive care unit personnel placed a high value on practical criteria such as user friendliness and visualization while assessing the present monitoring system. Poor alarm handling was recognized as possible patient safety hazards. The necessity of high accessibility was highlighted once again for a prospective system; wireless, noninvasive, and interoperability of monitoring devices were requested; and smart phones for distant patient monitoring and alert management improvement were required.

Conclusion

Core comments from ICU personnel are included in this qualitative research on patient monitoring. All national healthcare involved parties must focus more on user-derived insights to ensure a speedy and effective introduction of digital health technologies in the ICU. The findings from the alarm control or mobile device studies might be utilized to train ICU personnel to use new technology, minimize alarm fatigue, increase medical device accessibility, and develop interoperability standards in critical care practice.

Clinical applications of body composition and functional status tools for nutrition assessment of hospitalized adults: A systematic review

BACKGROUND

No global consensus exists on diagnostic criteria for malnutrition. Muscular deficits and functional impairments are major components of available malnutrition diagnostic frameworks because these facets of nutrition status significantly impact outcomes. The purpose of this review is to explore which body composition assessment (BCA) and functional status assessment (FSA) tools are being used for nutrition assessment (NA) and monitoring the response to nutrition interventions (RNIs) in adult inpatients.

METHODS

A literature search of Embase, Medline (Ovid), Web of Science, and Cochrane Central was performed to identify studies that used BCA and/or FSA tools for NA (along with an accepted NA diagnostic framework) and/or for monitoring RNI in adult inpatients.

RESULTS

The search yielded 3667 articles; 94 were included in the review. The number of studies using BCA and/or FSA tools for NA was 47 and also 47 for monitoring RNI. Seventy-nine percent of studies used bioimpedance for BCA, and 97% that included FSA utilized handgrip strength. When compared against sets of diagnostic criteria, many of the BCA and FSA tools showed promising associations with nutrition status.

CONCLUSION

Bioimpedance methods are the most widely used bedside BCA tools, and handgrip strength is the most widely used FSA tool; however, these methods are being used with a variety of protocols, algorithms, and interpretation practices in heterogeneous populations. To create a standardized nutrition status assessment process there is a need for validation studies on bedside methods and the development of globally standardized assessment protocols in clinical inpatient settings.

Implementation of Hospital-to-Home Model for Nutritional Nursing Management of Patients with Chronic Kidney Disease Using Artificial Intelligence Algorithm Combined with CT Internet

The objective of this study was to evaluate the application value of “Internet + hospital-to-home (H2H)” nutritional care model using the improved wavelet transform algorithm based on computed tomography (CT) images in the nutritional care management of chronic kidney disease (CKD) stages 3-5. A total of 120 patients with CKD were the research objects and they were randomly divided into two groups. The normal nutritional nursing model was used for nursing of patients in the control group, and the “Internet + H2H″ model was used for the observation group (H2H group), with 60 cases in each group. The nursing effect was evaluated using 320-slice volume CT low-dose perfusion imaging images, anthropometry, laboratory biochemical tests, and other survey scores. The results showed that compared with the mean filter denoising (MFD) algorithm and the orthogonal wavelet denoising (OWD) algorithm, the mean square error (MSE) and signal noise ratio (SNR) values of the IWT algorithm were better (40.0781 vs 45.2891, 59.2123)/(20.0122 vs 18.2311, 15.7812) (P < 0.05). The arm muscle circumference (MAC) (239.77 ± 18.24 vs 243.94 ± 18.72 mm) and triceps skindold (TSF) value (8.87 ± 2.74 vs 10.04 ± 2.90 mm) of the patients in the H2H group were greatly improved after the nursing (P < 0.05). For biochemical indicators, serum albumin (ALB) (35.22 ± 4.98 vs 45.32 ± 4.21) g/L, prealbumin (PAB) (289.94 ± 72.99 vs 341.79 ± 74.45) mg/L, hemoglobin (Hb) (97.62 ± 24.87 vs 110.65 ± 28.83) g/L, and blood urea nitrogen (BUN) (15.74 ± 9.87 vs 11.06 ± 5.69) mmol/L of patients in H2H group were improved (P < 0.05). After nursing, the nutritional screening score of the H2H group was obviously improved (83.33% (before) vs 50% (after)), the total score of health quality assessment (114.89 ± 5.23) in the H2H group was much higher than that of the control group (87.22 ± 14.89), and the satisfaction on the nursing model was higher in the H2H group (100% vs 71.67%) (P < 0.05). The renal cortex BF before and after nursing was significantly different between the two groups of patients (P < 0.05), and the BE of the H2H group was significantly higher than that of the control group after treatment ((335.12 ± 52.74) mL·100 g⁻¹·min⁻¹ vs (289.90 ± 53.91) mL·100 g⁻¹·min⁻¹) (P < 0.05). In summary, the “Internet + H2H″ nutritional nursing model was more individualized, which can better improve the physical quality of patients with stages 3-5 of CKD, improve the psychological state of patients, and further enhance the prognosis of the disease. In addition, the IWT algorithm showed better effects in the processing of the image of 320-slice volume CT low-dose perfusion imaging, and it was worthy of clinical application.

The comparison of GNRI and other nutritional indexes on short-term survival in geriatric patients treated for respiratory failure

BACKGROUND

There are several screening tools used in the detection of malnutrition to facilitate nutritional support and predict prognosis in the elderly.

AIMS

We aimed to compare the prognostic predictive value of geriatric nutritional risk index (GNRI) with other nutritional indices on 1 month survival in geriatric patients hospitalized for respiratory failure in intensive care unit (ICU).

METHODS

A total of 191 geriatric patients (> 65 years) admitted to a specialized chest hospital with respiratory failure between January 2018 and January 2019 were analyzed. Patients were classified into two category according to 30-day survival: Survivors and Non-survivors. Nutritional assesment was done via GNRI, OPNI, NRS 2002, Nutric Scores in ICU.

RESULTS

Using GNRI, 146 (76.3%) geriatric patients found to be at risk of malnutrition (GNRI score: ≤ 92). GNRI < 86.9 showed significantly higher 30-day mortality rate and patients with malnutrition risk were older, had significantly lower BMI, OPNI, and higher SOFA score. The Age, NRS 2002, Nutric and SOFA score had negative correlation with GNRI. Nutric score, prealbumin and GNRI were detected as significant independent risk factors of 30-day mortality. GNRI had higher sensitivity (76.7%) but lower specificity (57.1%) compared to Nutric score and OPNI for the prediction of 30-day hospital mortality.

CONCLUSIONS

Compared to others, Geriatric Nutritional Risk Index (GNRI) seems to be a good predictor of 30-day mortality and having a score of less than 86.9 increase the malnutrition risk in geriatric patients hospitalized for respiratory failure in ICU.