Tag Archives: critically ill

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

Rajesh Panda, Saurabh Saigal, Rajnish Joshi, Abhijit Pakhare, Ankur Joshi, Jai Prakash Sharma, Sahil Tandon

All India Institute of Medical Science – Bhopal, Madhya Pradesh, India

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

Alvin Saverymuthu, Rufinah Teo, Jaafar Md Zain, Saw Kian Cheah, Aliza Mohamad Yusof, Raha Abdul Rahman

Department of Anaesthesiology & Intensive Care, Hospital Canselor Tuanku Muhriz, University Kebangsaan Malaysia (UKM), Kuala Lumpur, Malaysia

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

Christophe de Terwangne1, Antonio Sorgente2, Redente Tortora3, Diana Cheung3, Frederic Duprez3, Sammy Place1, Jerome R. Lechien4, Lucio Capulzini2, Michael De Cubber2, Sven Saussez4, Fabio Silvio Taccone5, Shahram Mashayekhi3

1 Department of Internal Medicine, Centre Hospitalier EpiCURA Hornu, Hornu, Belgium
2 Department of Cardiology, Centre Hospitalier EpiCURA, Hornu, Belgium
3 Department of Intensive Care, Centre Hospitalier EpiCURA, Hornu, Belgium
4 Department of Human Anatomy and Experimental Oncology, University of Mons, Mons, Belgium
5 Department of Intensive Care, Hopital Erasme, Université Libre de Bruxelles, Brussels, Belgium

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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