A historical cohort study on predictors for successful weaning from prolonged mechanical ventilation and up to 3-year survival follow-up in a rehabilitation center.

BACKGROUND: We followed prolonged mechanically ventilated (PMV) patients for weaning attempts and explored factors associated with successful weaning and long-term survival. METHODS: This historical cohort study included all adult PMV patients admitted to a single rehabilitation hospital during 2015-2018 and followed for survival according to weaning success up to 3 years or the end of 2021. RESULTS: The study included 223 PMV patients. Of them, 124 (55.6 %) underwent weaning attempts, with 69 (55.6 %) successfully weaned, 55 (44.4 %) unsuccessfully weaned, and 99 patients with no weaning attempts. The mean age was 67 ± 20 years, with 39 % female patients. Age, sex distributions and albumin levels at admission were not significantly different among the groups. The successful weaning group had a 6 % higher proportion of conscious patients than the failed weaning group (55 % vs. 49 %, respectively, p = 0.45). Patients successfully weaned were less frequently treated with antibiotics for 5 days or more than those unsuccessfully weaned (74 % vs 80 %, respectively, p = 0.07). They also had a lower proportion of time from intubation to tracheostomy greater than 14 days (45 % vs 66 %, p = 0.02). The age, sex, antibiotic treatment, time to tracheostomy exceeding 14 days and time from admission to first weaning attempt adjusted one-year mortality risk of successful vs. failed weaning was somewhat lower, HR = 0.75, 95%CI: 0.33-1.60, p = 0.45, with the same trend by the end of 3 years, HR = 0.77, 95%CI: 0.42-1.39, p = 0.38. CONCLUSION: Successful weaning from PMV may be associated with better survival and allows chronically ventilated patients to become independent on a ventilator. A larger study is needed to further validate our findings.

Global availability of parenteral nutrition: Pre- and post-COVID-19 pandemic surveys.

OBJECTIVE: Parenteral nutrition represents a therapeutic option for patients with type 3 intestinal failure. If used exclusively, parenteral nutrition has to be complete to provide all essential nutrients. The aim was to assess the availability of parenteral nutrition in all parts of the world, to better comprehend the global situation, and to prepare an action plan to increase access to parenteral nutrition. METHODS: An international survey using an electronic questionnaire was conducted in August 2019 and repeated in May 2022. An electronic questionnaire was sent to 52 members or affiliates of the International Clinical Nutrition Section of the American Society for Parenteral and Enteral Nutrition. Questions addressed the availability of parenteral nutrition admixtures and their components, reimbursement, and prescribing pre- and post-COVID-19 pandemic. All participating countries were categorized by their economic status. RESULTS: Thirty-six country representatives responded, answering all questions. Parenteral nutrition was available in all countries (100%), but in four countries (11.1%) three-chamber bags were the only option, and in six countries a multibottle system was still used. Liver-sparing amino acids were available in 18 (50%), kidney-sparing in eight (22.2%), and electrolyte-free in 11 (30.5%) countries (30.5%). In most countries (n = 28; 79.4%), fat-soluble and water-soluble vitamins were available. Trace elements solutions were unavailable in four (11.1%) countries. Parenteral nutrition was reimbursed in most countries (n = 33; 91.6%). No significant problems due to the coronavirus pandemic were reported. CONCLUSIONS: Despite the apparent high availability of parenteral nutrition worldwide, there are some factors that may have a substantial effect on the quality of parenteral nutrition admixtures. These shortages create an environment of inequality.

Insights from home parenteral nutrition infusion data.

OBJECTIVE: Patients with chronic intestinal failure use home parenteral nutrition infusion support. Non-compliance of home parenteral nutrition treatment is well documented, especially if clinical resources are remote. Objective delivery data from Infusion Pump reports have the potential to support treatment progress and planning. The aim of this study was to report the efficacy and accuracy of the Eitan Insights digital health platform for home parenteral nutrition use (a platform providing data-driven insights from the pump-recorded data). METHODS: A prospective, single-center observational study of 20 patients treated with home parenteral nutrition ≥3 d/wk was conducted over 2022. The patients recorded the pre- and postinfusion home parenteral nutrition bag weight, duration of infusion, and alarms. We compared manual records to the pump data. Repeated measures analysis of variance was used for statistical analysis. RESULTS: A total of 45 data sets were collected, with no adverse events noted. In multiple comparisons between patient factors and descriptive statistics, there was no significant difference between manually recorded and pump-recorded data for volume infused (mean values of manual versus pump were 1707 ± 362 mL and 1708 ± 405 mL; P = 0.939) and infusion duration (mean values of manual versus pump iwere 9h 43 min ± 2.48 SD versus 9h 45 min ± 2.41 SD; P = 0.858). CONCLUSION: The data collected by the digital platform accurately reflect patients' infusion data. This connected device has the potential to allow clinicians to be more informed and assess treatment trends and proactive resource planning through the Infusion Pump data insights.

Predicting invasive mechanical ventilation in COVID 19 patients: A validation study.

INTRODUCTION: The decision to intubate and ventilate a patient is mainly clinical. Both delaying intubation (when needed) and unnecessarily invasively ventilating (when it can be avoided) are harmful. We recently developed an algorithm predicting respiratory failure and invasive mechanical ventilation in COVID-19 patients. This is an internal validation study of this model, which also suggests a categorized "time-weighted" model. METHODS: We used a dataset of COVID-19 patients who were admitted to Rabin Medical Center after the algorithm was developed. We evaluated model performance in predicting ventilation, regarding the actual endpoint of each patient. We further categorized each patient into one of four categories, based on the strength of the prediction of ventilation over time. We evaluated this categorized model performance regarding the actual endpoint of each patient. RESULTS: 881 patients were included in the study; 96 of them were ventilated. AUC of the original algorithm is 0.87-0.94. The AUC of the categorized model is 0.95. CONCLUSIONS: A minor degradation in the algorithm accuracy was noted in the internal validation, however, its accuracy remained high. The categorized model allows accurate prediction over time, with very high negative predictive value.

The future of artificial intelligence in clinical nutrition.

PURPOSE OF REVIEW: Artificial intelligence has reached the clinical nutrition field. To perform personalized medicine, numerous tools can be used. In this review, we describe how the physician can utilize the growing healthcare databases to develop deep learning and machine learning algorithms, thus helping to improve screening, assessment, prediction of clinical events and outcomes related to clinical nutrition. RECENT FINDINGS: Artificial intelligence can be applied to all the fields of clinical nutrition. Improving screening tools, identifying malnourished cancer patients or obesity using large databases has been achieved. In intensive care, machine learning has been able to predict enteral feeding intolerance, diarrhea, or refeeding hypophosphatemia. The outcome of patients with cancer can also be improved. Microbiota and metabolomics profiles are better integrated with the clinical condition using machine learning. However, ethical considerations and limitations of the use of artificial intelligence should be considered. SUMMARY: Artificial intelligence is here to support the decision-making process of health professionals. Knowing not only its limitations but also its power will allow precision medicine in clinical nutrition as well as in the rest of the medical practice.

Implementation of the ESPEN guideline on clinical nutrition in the intensive care unit (ICU): It is time to move forward!: A position paper from the 'nutrition in the ICU' ESPEN special interest group.

Nutritional assessment and provision of nutritional therapy are a core part of intensive care unit (ICU) patient treatment. The ESPEN guideline on clinical nutrition in the ICU was published in 2019. However, uncertainty and difficulties remain regarding its full implementation in daily practice. This position paper is intended to help ICU healthcare professionals facilitate the implementation of ESPEN nutrition guidelines to ensure the best care for their patients. We have aimed to emphasize the guideline recommendations that need to be implemented in the ICU, are advised, or are optional, and to give practical directives to improve the guideline recommendations in daily practice. These statements were written by the members of the ICU nutrition ESPEN special interest group (SIG), based on a survey aimed at identifying current practices relating to key issues in ICU nutrition. The ultimate goal is to improve the ICU patients quality of care.

Metabolic and nutritional aspects in continuous renal replacement therapy.

Nutrition is one of the foundations for supporting and treating critically ill patients. Nutritional support provides calories, protein, electrolytes, vitamins, and trace elements via the enteral or parenteral route. Acute kidney injury (AKI) is a common and devastating problem in critically ill patients and has significant metabolic and nutritional consequences. Moreover, renal replacement therapy (RRT), whatever the modality used, also profoundly impacts metabolism. RRT and of the extracorporeal circuit impede 'effect the evaluation of a patient's energy requirements by clinicians. Substrates added and removed within the extracorporeal treatment are not always taken into consideration, making treatment even more challenging. Furthermore, evidence on nutritional support during continuous renal replacement therapy (CRRT) is scarce, and there are no clinical guidelines for nutrition adaptations during CRRT in critically ill patients. Most recommendations are based on expert opinions. This review discusses the complex interaction between nutritional support and CRRT and presents some milestones for nutritional support in critically ill patients on CRRT.

Two-hour indirect calorimetry measurement as a predictor of 24-hour energy expenditure in critically ill surgical patients: A longitudinal study.

BACKGROUND: Measuring energy expenditure (EE) by indirect calorimetry (IC) has become the gold standard tool for critically ill patients to define energy targets and tailor nutrition. Debate remains as to the optimal duration of measurements or the optimal time of day in which to perform IC. METHODS: In this retrospective longitudinal study, we analyzed results of daily continuous IC in 270 mechanically ventilated, critically ill patients admitted to the surgical intensive care unit in a tertiary medical center and compared measurements performed at different hours of the day. RESULTS: A total of 51,448 IC hours was recorded, with an average 24-h EE of 1523 ± 443 kcal/day. Night shift (00:00-8:00) was found to have significantly lower EE measurements (mean, 1499 ± 439 kcal/day) than afternoon (16:00-00:00; mean, 1526 ± 435 kcal/day) and morning (8:00-16:00; mean, 1539 ± 462 kcal/day) measurements (P < 0.001 for all). The bi-hourly time frame that most closely resembled the daily mean was 18:00-19:59, with a mean of 1521 ± 433 kcal/day. Daily EE measurements of the continuous IC at days 3-7 of admission showed a trend toward a daily increase in 24-h EE, but the difference was not statistically significant (P = 0.081). CONCLUSIONS: Periodic measurements of EE can differ slightly when performed at various hours of the day, but the error range is small and may not necessarily have a clinical impact. When continuous IC is not available, a 2-h EE measurement between 18:00 and 19:59 can serve as a reasonable alternative.

ESPEN practical and partially revised guideline: Clinical nutrition in the intensive care unit.

Following the new ESPEN Standard Operating Procedures, the previous 2019 guideline to provide best medical nutritional therapy to critically ill patients has been shortened and partially revised. Following this update, we propose this publication as a practical guideline based on the published scientific guideline, but shortened and illustrated by flow charts. The main goal of this practical guideline is to increase understanding and allow the practitioner to implement the Nutrition in the ICU guidelines. All the items discussed in the previous guidelines are included as well as special conditions.

Controlled enteral nutrition in critical care patients - A randomized clinical trial of a novel management system.

PURPOSE: Nutritional therapy is essential to ICU care. Successful early enteral feeding is hindered by lack of protocols, gastrointestinal intolerance and feeding interruptions, leading to impaired nutritional intake. smART+ was developed as a nutrition management feeding platform controlling tube positioning, reflux, gastric pressure, and malnutrition. This study evaluated the potential of this new ICU care platform to deliver targeted nutrition and improve ICU outcomes. METHODS: Critically ill patients ≥18 years-old, mechanically ventilated and enterally fed, were randomized to receive ESPEN-guideline-based nutrition or smART+ -guided nutrition for 2-14 days. Primary endpoint was average deviation from daily targeted nutrition determined via calculation of energy targets per calorimetry. Secondary endpoints included gastric residual volumes, length of stay (LOS) and length of ventilation (LOV). RESULTS: smART+ achieved a mean deviation from daily targeted nutrition of 10.5% (n = 48) versus 34.3% for control (n = 50), p < 0.0001. LOS and LOV were decreased in the smART+ group versus control (mean LOS: 10.4 days versus 13.7; reduction 3.3 days, adjusted HR 1.71, 95% CI:1.13,2.60, p = 0.012; mean LOV: 9.5 days versus 12.8 days reduction of 3.3 days, adjusted HR 1.64, 95% CI:1.08-2.51, p = 0.021). Feeding goals were met (within ±10%) on 75.7% of days for smART+ versus 23.3% for control (p < 0.001). No treatment-related adverse events occurred in either group. The study was stopped due to success in a planned interim analysis of the first 100 patients. CONCLUSION: The smART+ Platform improved adherence to feeding goals and reduced LOS and LOV versus standard of care in critically ill patients. TRIAL REGISTRATION: NCT04098224; registered September 23, 2019.

An immune-protein score combining TRAIL, IP-10 and CRP for predicting severe COVID-19 disease.

COVID-19 patients are oftentimes over- or under-treated due to a deficit in predictive management tools. This study reports derivation of an algorithm that integrates the host levels of TRAIL, IP-10, and CRP into a single numeric score that is an early indicator of severe outcome for COVID-19 patients and can identify patients at-risk to deteriorate. 394 COVID-19 patients were eligible; 29% meeting a severe outcome (intensive care unit admission/non-invasive or invasive ventilation/death). The score's area under the receiver operating characteristic curve (AUC) was 0.86, superior to IL-6 (AUC 0.77; p = 0.033) and CRP (AUC 0.78; p < 0.001). Likelihood of severe outcome increased significantly (p < 0.001) with higher scores. The score differentiated severe patients who further deteriorated from those who improved (p = 0.004) and projected 14-day survival probabilities (p < 0.001). The score accurately predicted COVID-19 patients at-risk for severe outcome, and therefore has potential to facilitate timely care escalation and de-escalation and appropriate resource allocation.

Gastrointestinal failure, big data and intensive care.

PURPOSE OF REVIEW: Enteral feeding is the main route of administration of medical nutritional therapy in the critically ill. However, its failure is associated with increased complications. Machine learning and artificial intelligence have been used in intensive care to predict complications. The aim of this review is to explore the ability of machine learning to support decision making to ensure successful nutritional therapy. RECENT FINDINGS: Numerous conditions such as sepsis, acute kidney injury or indication for mechanical ventilation can be predicted using machine learning. Recently, machine learning has been applied to explore how gastrointestinal symptoms in addition to demographic parameters and severity scores, can accurately predict outcomes and successful administration of medical nutritional therapy. SUMMARY: With the rise of precision and personalized medicine for support of medical decisions, machine learning is gaining popularity in the field of intensive care, first not only to predict acute renal failure or indication for intubation but also to define the best parameters for recognizing gastrointestinal intolerance and to recognize patients intolerant to enteral feeding. Large data availability and improvement in data science will make machine learning an important tool to improve medical nutritional therapy.

Using Machine-Learning to Assess the Prognostic Value of Early Enteral Feeding Intolerance in Critically Ill Patients: A Retrospective Study.

BACKGROUND: The association between gastrointestinal intolerance during early enteral nutrition (EN) and adverse clinical outcomes in critically ill patients is controversial. We aimed to assess the prognostic value of enteral feeding intolerance (EFI) markers during early ICU stays and to predict early EN failure using a machine learning (ML) approach. METHODS: We performed a retrospective analysis of data from adult patients admitted to Beilinson Hospital ICU between January 2011 and December 2018 for more than 48 h and received EN. Clinical data, including demographics, severity scores, EFI markers, and medications, along with 72 h after admission, were analyzed by ML algorithms. Prediction performance was assessed by the area under the receiver operating characteristics (AUCROC) of a ten-fold cross-validation set. RESULTS: The datasets comprised 1584 patients. The means of the cross-validation AUCROCs for 90-day mortality and early EN failure were 0.73 (95% CI 0.71-0.75) and 0.71 (95% CI 0.67-0.74), respectively. Gastric residual volume above 250 mL on the second day was an important component of both prediction models. CONCLUSIONS: ML underlined the EFI markers that predict poor 90-day outcomes and early EN failure and supports early recognition of at-risk patients. Results have to be confirmed in further prospective and external validation studies.

The EyeControl-Med device, an alternative tool for communication in ventilated critically ill patients: A pilot study examining communication capabilities and delirium.

INTRODUCTION: Communication with ventilated patients in the Intensive care unit (ICU) is challenging. This may lead to anxiety and frustration, potentially contributing to the development of delirium. Various technologies, such as eye-tracking devices, have been employed to facilitate communication with varying grades of success. The EyeControl-Med device is a novel technology that delivers audio content and allows patients to interact by eye movements and could potentially allow for better communication in this setting. The aim of this exploratory concept study was to assess communication capabilities and delirium incidence using the EyeControl-Med device in critically ill patients unable to generate speech. MATERIAL AND METHODS: A single-arm pilot study of patients in a mixed ICU. Patients were approached for consent if they were invasively ventilated and/or tracheotomized, hence unable to generate speech, but had no severe cognitive or sensory impairment that could prevent proper usage. Patients underwent at least 3 sessions with the EyeControl-Med device administered by a speech-language pathologist. Communication and consciousness were assessed using the Loewenstein Communication Scale (LCS) tool during the first and last sessions. Delirium was assessed using a computerized CAM-ICU questionnaire. RESULTS: 15 patients were included, 40% of whom were diagnosed with COVID-19. All patients completed three to seven usage sessions. The mean LCS score improved by 19.3 points (p < 0.0001), with each of its five components showing significant improvements as well. The mean number of errors on the CAM-ICU questionnaire decreased from 6.5 to 2.5 (p = 0.0006), indicating a lower incidence of delirium. No adverse effects were observed. CONCLUSION: The EyeControl-Med device may facilitate communication and reduce the manifestations and duration of delirium in ventilated critically ill patients. Controlled studies are required to establish this effect.

Early detection of oliguric events in critically ill patients in the ICU with a novel continuous urine flow measurement device: results of an initial validation study.

OBJECTIVES: Urine output is used to evaluate fluid status and is an important marker for acute kidney injury (AKI). Our primary aim was to validate a new automatic urine output monitoring device by comparison to the current practice - the standard urometer. METHODS: We conducted a prospective observational study in three ICUs. Urine flow measurements by Serenno Medical Automatic urine output measuring device (Serenno Medical, Yokneam, Israel) were compared to standard urometer readings taken automatically at 5-minutes intervals by a camera, and to hourly urometer readings by the nurses, both over 1 to 7 days. Our primary outcome was the difference between urine flow assessed by the Serenno device and reference camera-derived measurements (Camera). Our secondary outcome was the difference between urine flow assessed by the Serenno device and hourly nursing assessments (Nurse), and detection of oliguria. RESULTS: Thirty-seven patients completed the study, with 1,306 h of recording and a median of 25 measurement hours per patient. Bland and Altman analysis comparing the study device to camera measurements demonstrated good agreement, with a bias of -0.4 ml/h and 95% confidence intervals ranging from - 28 to 27ml/h. Concordance was 92%. The correlation between Camera and hourly nursing assessment of urine output was distinctly worse with a bias of 7.2 ml and limits of agreement extending from - 75 to + 107 ml. Severe oliguria (urine output < 0.3 ml/kg/h) lasting 2 h or more was common and observed in 8 (21%) of patients. Among the severe oliguric events lasting more than 3 consecutive hours, 6 (41%) were not detected or documented by the nursing staff. There were no device-related complications. CONCLUSION: The Serenno Medical Automatic urine output measuring device required minimal supervision, little ICU nursing staff attention, and is sufficiently accurate and precise. In addition to providing continuous assessments of urine output, it was considerably more accurate than hourly nursing assessments.

The efficacy of calorimetry-based nutritional support versus recommended dietary intake-based nutritional support in the successful weaning of chronically ventilated patients: A study protocol for a double blind randomized controlled trial.

BACKGROUND & AIMS: Mechanically ventilated patients are weaned during acute care hospitalization when it is determined that they are ready for withdrawal. If weaning fails, patients are admitted to a rehabilitation medical center for continued supportive care and additional weaning attempts. This study's objective is to increase the success rate of weaning from prolonged mechanical ventilation (PMV), and to shorten the overall weaning period by tailoring the patient's caloric intake according to their individually measured energy needs. METHODS: We designed a randomized, controlled, double-blinded trial to be conducted among PMV patients undergoing routine ventilation-weaning attempts. Patients in the intervention arm will be fed according to energy needs determined by calorimetry. Patients in the control arm will be fed according to the standard of care, namely the Recommended Dietary Allowance (RDA) guidelines. Each patient will undergo up to five weaning attempts. Study outcomes will include successful weaning rate, time to successful weaning, and 3-12 months survival rate. DISCUSSION: This trial aims to examine the safety and efficacy of a nutritional diet based on an individual's measured caloric needs in terms of weaning rates and weaning time. We hypothesize that calorimetry-based nutrition plan will prove to be superior in both success rate and time to successful weaning compared to the standard nutrition plan based on the resting energy expenditure (REE) formula during the weaning process. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04825717.