Tag Archives: critically ill

Optimizing Nutrient Uptake in the Critically Ill: Insights into Malabsorption Management

DOI: 10.2478jccm-2024-0012

It has already been stated that nutritional support represents a crucial component in the care of critically ill patients [1]. Prolonged negative energy balance during intensive care stay was confirmed as an independent risk factor for mortality. High metabolic demand encountered for critically ill patients may cause significant energy deficits responsible for increased risk of infection, prolonged mechanical ventilation and ICU stay [2-4].
Aditionally, providing nutritional support in ICU patients is often deemd challenging, as enteral feeding intolerance devolps secondary to gastrointestinal dysfunction [5]. Exccesive antimicrobial usage along with associated risk of nosocomial diarrhea may further exacerbate feeding intolerance. [More]

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Feeding Intolerance in Critically Ill Patients with Enteral Nutrition: A Meta-Analysis and Systematic Review

DOI: 10.2478/jccm-2024-0007

Background: Feeding intolerance is a common yet serious complication in critically ill patients undergoing enteral nutrition. We aimed to conduct a meta-analysis to evaluate the risk factors of feeding intolerance in critically ill patients undergoing enteral nutrition, to provide insights to the clinical enteral nutrition treatment and care.
Methods: Two researchers systematically searched PubMed, Medline, Web of Science, Cochrane Library, Chinanews.com, Wanfang and Weipu databases about the studies on the risk factors of feeding intolerance in severe patients with enteral nutrition up to August 15, 2023. Literature screening, data extraction and quality evaluation were carried out independently by two researchers, and Meta analysis was carried out with RevMan 5.3 software and Stata 15.0 software.
Results: 18 studies involving 5564 enteral nutrition patients were included. The results of meta-analyses showed that age < 2 years old, age > 60 years old, APACHE II score ≥ 20, Hypokalemia, starting time of enteral nutrition > 72 hours, no dietary fiber, intra-abdominal pressure > 15mmHg, central venous pressure > 10cmH2O and mechanical ventilation were the risk factors of feeding intolerance in critically ill patients undergoing EN (all P<0.05). No publication biases were found amongst the included studies.
Conclusion: The incidence of feeding intolerance in critically ill patients undergoing enteral nutrition is high, and there are many influencing factors. Clinical medical workers should take effective preventive measures according to the risk and protective factors of patients to reduce the incidence of feeding intolerance and improve the prognosis of patients.

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Total Psoas Area and Psoas Density Assessment in COVID-19 Patients Using CT Imaging – Could Muscle Mass Alteration During Intensive Care Hospitalization be Determined?

DOI: 10.2478/jccm-2023-0026

Background: Since its debut, as reported by the first published studies, COVID-19 has been linked to life-threatening conditions that needed vital assistance and admission to the intensive care unit. Skeletal muscle is a core element in an organism’s health due to its ability to keep energy balance and homeostasis. Many patients with prolonged hospitalization are characterized by a greater probability prone to critical illness myopathy or intensive care unit-acquired weakness.
Objective: The main aim of this study was to assess the skeletal muscle in a COVID-19 cohort of critically ill patients by measuring the psoas area and density.
Material and methods: This is a retrospective study that included critically ill adult patients, COVID-19 positive, mechanically ventilated, with an ICU stay of over 24 hours, and who had 2 CT scans eligible for psoas muscle evaluation. In these patients, correlations between different severity scores and psoas CT scans were sought, along with correlations with the outcome of the patients.
Results: Twenty-two patients met the inclusion criteria. No statistically significant differences were noticed regarding the psoas analysis by two blinded radiologists. Significant correlations were found between LOS in the hospital and in ICU with psoas area and Hounsfield Units for the first CT scan performed. With reference to AUC-ROC and outcome, it is underlined that AUC-ROC is close to 0.5 values, for both the psoas area and HU, indicating that the model had no class separation capacity.
Conclusion: The study suggested that over a short period, the psoas muscle area, and the psoas HU decline, for both the left and the right sight, in adult COVID-19 patients in ICU conditions, yet not statistically significant. Although more than two-thirds of the patients had a negative outcome, it was not possible to demonstrate an association between the SARS-COV2 infection and psoas muscle impairment. These findings highlight the need for further larger investigations.

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Accuracy of Critical Care Ultrasonography Plus Arterial Blood Gas Analysis Based Algorithm in Diagnosing Aetiology of Acute Respiratory Failure

DOI: 10.2478/jccm-2023-0006

Introduction: Lung ultrasound when used in isolation, usually misses out metabolic causes of dyspnoea and differentiating acute exacerbation of COPD from pneumonia and pulmonary embolism is difficult, hence we thought of combining critical care ultrasonography (CCUS) with arterial blood gas analysis (ABG).
Aim of the study: The objective of this study was to estimate accuracy of Critical Care Ultrasonography (CCUS) plus Arterial blood gas (ABG) based algorithm in diagnosing aetiology of dyspnoea. Accuracy of traditional Chest X-ray (CxR) based algorithm was also validated in the following setting.
Methods : It was a facility based comparative study, where 174 dyspneic patients were subjected to CCUS plus ABG and CxR based algorithms on admission to ICU. The patients were classified into one of five pathophysiological diagnosis 1) Alveolar( Lung-pneumonia)disorder ; 2) Alveolar (Cardiac-pulmonary edema) disorder; 3) Ventilation with Alveolar defect (COPD) disorder ;4) Perfusion disorder; and 5) Metabolic disorder. We calculated diagnostic test properties of CCUS plus ABG and CXR based algorithm in relation to composite diagnosis and correlated these algorithms for each of the defined pathophysiological diagnosis.
Results: The sensitivity of CCUS and ABG based algorithm was 0.85 (95% CI-75.03-92.03) for alveolar (lung) ; 0.94 (95% CI-85.15-98.13) for alveolar (cardiac); 0.83 (95% CI-60.78-94.16) for ventilation with alveolar defect; 0.66 (95% CI-30-90.32) for perfusion defect; 0.63 (95% CI-45.25-77.07) for metabolic disorders.Cohn’s kappa correlation coefficient of CCUS plus ABG based algorithm in relation to composite diagnosis was 0.7 for alveolar (lung), 0.85 for alveolar (cardiac), 0.78 for ventilation with alveolar defect, 0.79 for perfusion defect and 0.69 for metabolic disorders.
Conclusion: CCUS plus ABG algorithm is highly sensitive and it’s agreement with composite diagnosis is far superior. It is a first of it’s kind study, where authors have attempted combining two point of care tests and creating an algorithmic approach for timely diagnosis and intervention.

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Acute Kidney Injury Following Rhabdomyolysis in Critically Ill Patients

DOI: 10.2478/jccm-2021-0025

Introduction: Rhabdomyolysis, which resulted from the rapid breakdown of damaged skeletal muscle, potentially leads to acute kidney injury.
Aim: To determine the incidence and associated risk of kidney injury following rhabdomyolysis in critically ill patients.
Methods: All critically ill patients admitted from January 2016 to December 2017 were screened. A creatinine kinase level of > 5 times the upper limit of normal (> 1000 U/L) was defined as rhabdomyolysis, and kidney injury was determined based on the Kidney Disease Improving Global Outcome (KDIGO) score. In addition, trauma, prolonged surgery, sepsis, antipsychotic drugs, hyperthermia were included as risk factors for kidney injury.
Results: Out of 1620 admissions, 149 (9.2%) were identified as having rhabdomyolysis and 54 (36.2%) developed kidney injury. Acute kidney injury, by and large, was related to rhabdomyolysis followed a prolonged surgery (18.7%), sepsis (50.0%) or trauma (31.5%). The reduction in the creatinine kinase levels following hydration treatment was statistically significant in the non- kidney injury group (Z= -3.948, p<0.05) compared to the kidney injury group (Z= -0.623, p=0.534). Significantly, odds of developing acute kidney injury were 1.040 (p<0.001) for mean BW >50kg, 1.372(p<0.001) for SOFA Score >2, 5.333 (p<0.001) for sepsis and the multivariate regression analysis showed that SOFA scores >2 (p<0.001), BW >50kg (p=0.016) and sepsis (p<0.05) were independent risk factors. The overall mortality due to rhabdomyolysis was 15.4% (23/149), with significantly higher incidences of mortality in the kidney injury group (35.2%) vs the non- kidney injury (3.5%) [ p<0.001].
Conclusions: One-third of rhabdomyolysis patients developed acute kidney injury with a significantly high mortality rate. Sepsis was a prominent cause of acute kidney injury. Both sepsis and a SOFA score >2 were significant independent risk factors.

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Mortality Rate and Predictors among Patients with COVID-19 Related Acute Respiratory Failure Requiring Mechanical Ventilation: A Retrospective Single Centre Study

DOI: 10.2478/jccm-2020-0043

Aim: The objective of the study was to assess mortality rates in COVID-19 patients suffering from acute respiratory distress syndrome (ARDS) who also requiring mechanical ventilation. The predictors of mortality in this cohort were analysed, and the clinical characteristics recorded.
Material and method: A single centre retrospective study was conducted on all COVID-19 patients admitted to the intensive care unit of the Epicura Hospital Center, Province of Hainaut, Belgium, between March 1st and April 30th 2020.
Results: Forty-nine patients were included in the study of which thirty-four were male, and fifteen were female. The mean (SD) age was 68.8 (10.6) and 69.5 (12.6) for males and females, respectively. The median time to death after the onset of symptoms was eighteen days. The median time to death, after hospital admission was nine days. By the end of the thirty days follow-up, twenty-seven patients (55%) had died, and twenty–two (45%) had survived. Non-survivors, as compared to those who survived, were similar in gender, prescribed medications, COVID-19 symptoms, with similar laboratory test results. They were significantly older (p = 0.007), with a higher co-morbidity burden (p = 0.026) and underwent significantly less tracheostomy (p < 0.001). In multivariable logistic regression analysis, no parameter significantly predicted mortality.
Conclusions: This study reported a mortality rate of 55% in critically ill COVID-19 patients with ARDS who also required mechanical ventilation. The results corroborate previous findings that older and more comorbid patients represent the population at most risk of a poor outcome in this setting.

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