Tag Archives: ICU

Tracheoesophageal Iatrogenic Fistulas in ICU: Still a Pandora’s Box?

Radu Stoica

Clinical Hospital Sanador Bucharest, Romania

DOI: 10.2478/jccm-2024-0044

Tracheoesophageal fistulas (TEF) in the ICU are still considered a relatively rare, but life-threatening complication of prolonged intubation, with an incidence of approximately 0.5% of cases [1]. Classically, their occurrence was considered the result of the direct interaction between two mechanical factors: the endotracheal tube (ETT) or the tracheostomy tube placement on the membranous wall of the trachea, and the esophageal feeding tube that affects esophageal mucosa, leading to ischemic lesions and decubitus injury. The question that arises is why, despite this simple explanation, the incidence of TEF remains low? In reality, the occurrence of TEF in ICU is related to the complex interactions between patients’ comorbidities and the particularities of pathophysiology and management in critically ill patients, leading to local tissue metabolic disorders and favoring fistulas’ occurrence. Malnutrition, diabetes, chronic anemia, reflux esophagitis, prolonged inflammation, sepsis, hemodynamic instability, prolonged hypoxemia, vasoactive drugs or corticosteroids are the mainly factors favoring fistulas’ development. [More]

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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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Burnout Syndrome During COVID-19 Second Wave on ICU Caregivers

Anaëlle Caillet¹, Marina Fillon¹, Margaux Plou¹, Emmanuel Tisson¹, Charles-Hervé Vacheron1,2,3, Bernard Allaouchiche1,4,5

1 Hospices Civils de Lyon, Hospital center Lyon-Sud, ICU, F-69310, Pierre-Bénite, France
2 Biostatistics-Bioinformatics Department, Public Health Unit, Hospices Civils de Lyon, Lyon, France
3 CIRI, International Center for Research in Infectiology (Emerging Pathogens Laboratory Team), Inserm, U1111, Claude Bernard Lyon 1 University, CNRS, UMR5308, Lyon, France
4 University Claude Bernard, Lyon1, Lyon, France
5 Lyon university, VetAgro Sup, Lyon veterinary campus, UPSP 2016.A101, Pulmonary and Cardiovascular Agression in Sepsis, F-69280, Marcy l’Étoile, France

DOI: 10.2478/jccm-2022-0026

Objective: The main objective of this article is to evaluate the prevalence of burnout syndrome (BOS) among the Intensive Care Unit (ICU) healthcare workers.
Methods: The COVID-impact study is a study conducted in 6 French intensive care units. Five units admitting COVID patient and one that doesn’t admit COVID patients. The survey was conducted between October 20th and November 20th, 2020, during the second wave in France. A total of 208 professionals responded (90% response rate). The Maslach Burnout Inventory scale, the Hospital Anxiety and Depression Scale and the Impact of Event Revisited Scale were used to study the psychological impact of the COVID-19 Every intensive care unit worker.
Results: The cohort includes 208 professionals, 52.4% are caregivers. Almost 20% of the respondents suffered from severe BOS. The professionals who are particularly affected by BOS are women, engaged people, nurses or reinforcement, not coming willingly to the intensive care unit and professionals with psychological disorders since COVID-19, those who are afraid of being infected, and people with anxiety, depression or post-traumatic stress disorder. Independent risk factors isolated were being engaged and being a reinforcement. Being a volunteer to come to work in ICU is protective. 19.7% of the team suffered from severe BOS during the COVID-19 pandemic in our ICU. The independent risk factors for BOS are: being engaged (OR = 3.61 (95% CI, 1.44; 9.09), don’t working in ICU when it’s not COVID-19 pandemic (reinforcement) (OR = 37.71 (95% CI, 3.13; 454.35), being a volunteer (OR = 0.10 (95% CI, 0.02; 0.46).
Conclusion: Our study demonstrates the value of assessing burnout in health care teams. Prevention could be achieved by training personnel to form a health reserve in the event of a pandemic.

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