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1.
Anaesthesist ; 70(7): 573-581, 2021 07.
Article in German | MEDLINE | ID: covidwho-1453676

ABSTRACT

BACKGROUND: In a pandemic situation the overall mortality rate is of considerable interest; however, these data must always be seen in relation to the given healthcare system and the availability of local level of care. A recently published German data evaluation of more than 10,000 COVID-19 patients treated in 920 hospitals showed a high mortality rate of 22% in hospitalized patients and of more than 50% in patients requiring invasive ventilation. Because of the high infection rates in Bavaria, a large number of COVID-19 patients with considerable severity of disease were treated at the intensive care units of the LMU hospital. The LMU hospital is a university hospital and a specialized referral center for the treatment of patients with acute respiratory distress syndrome (ARDS). OBJECTIVE: Data of LMU intensive care unit (ICU) patients were systematically evaluated and compared with the recently published German data. METHODS: Data of all COVID-19 patients with invasive and noninvasive ventilation and with completed admission at the ICU of the LMU hospital until 31 July 2020 were collected. Data were processed using descriptive statistics. RESULTS: In total 70 critically ill patients were included in the data evaluation. The median SAPS II on admission to the ICU was 62 points. The median age was 66 years and 81% of the patients were male. More than 90% were diagnosed with ARDS and received invasive ventilation. Treatment with extracorporeal membrane oxygenation (ECMO) was necessary in 10% of the patients. The median duration of ventilation was 16 days, whereby 34.3% of patients required a tracheostomy. Of the patients 27.1% were transferred to the LMU hospital from external hospitals with reference to our ARDS/ECMO program. Patients from external hospitals had ARDS of higher severity than the total study population. In total, nine different substances were used for virus-specific treatment of COVID-19. The most frequently used substances were hydroxychloroquine and azithromycin. Immunomodulatory treatment, such as Cytosorb® (18.6%) and methylprednisolone (25.7%) were also frequently used. The overall in-hospital mortality rate of ICU patients requiring ventilation was 28.6%. The mortality rates of patients from external hospitals, patients with renal replacement therapy and patients with ECMO therapy were 47.4%, 56.7% and 85.7%, respectively. CONCLUSION: The mortality rate in the ventilated COVID-19 intensive care patients was considerably different from the general rate in Germany. The data showed that treatment in an ARDS referral center could result in a lower mortality rate. Low-dose administration of steroids may be another factor to improve patient outcome in a preselected patient population. In the authors' opinion, critically ill COVID-19 patients should be treated in an ARDS center provided that sufficient resources are available.


Subject(s)
COVID-19/therapy , Respiration, Artificial/statistics & numerical data , Aged , Aged, 80 and over , Antiviral Agents/therapeutic use , COVID-19/complications , COVID-19/mortality , Critical Illness/therapy , Extracorporeal Membrane Oxygenation , Female , Germany , Hospital Mortality , Hospitals, University , Humans , Immunologic Factors/therapeutic use , Intensive Care Units/statistics & numerical data , Male , Middle Aged , Patient Transfer , Renal Replacement Therapy/statistics & numerical data , Respiratory Distress Syndrome/etiology , Respiratory Distress Syndrome/therapy , Treatment Outcome
2.
Obes Med ; 25: 100358, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1294094

ABSTRACT

Aims: This study aimed to determine whether anthropometric markers of thoracic skeletal muscle and abdominal visceral fat tissue correlate with outcome parameters in critically ill COVID-19 patients. Methods: We retrospectively analysed thoracic CT-scans of 67 patients in four ICUs at a university hospital. Thoracic skeletal muscle (total cross-sectional area (CSA); pectoralis muscle area (PMA)) and abdominal visceral fat tissue (VAT) were quantified using a semi-automated method. Point-biserial-correlation-coefficient, Spearman-correlation-coefficient, Wilcoxon rank-sum test and logistic regression were used to assess the correlation and test for differences between anthropometric parameters and death, ventilator- and ICU-free days and initial inflammatory laboratory values. Results: Deceased patients had lower CSA and PMA values, but higher VAT values (p < 0.001). Male patients with higher CSA values had more ventilator-free days (p = 0.047) and ICU-free days (p = 0.017). Higher VAT/CSA and VAT/PMA values were associated with higher mortality (p < 0.001), but were negatively correlated with ICU length of stay in female patients only (p < 0.016). There was no association between anthropometric parameters and initial inflammatory biomarker levels. Logistic regression revealed no significant independent predictor for death. Conclusion: Our study suggests that pathologic body composition assessed by planimetric measurements using thoracic CT-scans is associated with worse outcome in critically ill COVID-19 patients.

3.
Diagnostics (Basel) ; 11(6)2021 Jun 03.
Article in English | MEDLINE | ID: covidwho-1259441

ABSTRACT

(1) Background: Extracorporeal membrane oxygenation (ECMO) therapy in intensive care units (ICUs) remains the last treatment option for Coronavirus disease 2019 (COVID-19) patients with severely affected lungs but is highly resource demanding. Early risk stratification for the need of ECMO therapy upon admission to the hospital using artificial intelligence (AI)-based computed tomography (CT) assessment and clinical scores is beneficial for patient assessment and resource management; (2) Methods: Retrospective single-center study with 95 confirmed COVID-19 patients admitted to the participating ICUs. Patients requiring ECMO therapy (n = 14) during ICU stay versus patients without ECMO treatment (n = 81) were evaluated for discriminative clinical prediction parameters and AI-based CT imaging features and their diagnostic potential to predict ECMO therapy. Reported patient data include clinical scores, AI-based CT findings and patient outcomes; (3) Results: Patients subsequently allocated to ECMO therapy had significantly higher sequential organ failure (SOFA) scores (p < 0.001) and significantly lower oxygenation indices on admission (p = 0.009) than patients with standard ICU therapy. The median time from hospital admission to ECMO placement was 1.4 days (IQR 0.2-4.0). The percentage of lung involvement on AI-based CT assessment on admission to the hospital was significantly higher in ECMO patients (p < 0.001). In binary logistic regression analyses for ECMO prediction including age, sex, body mass index (BMI), SOFA score on admission, lactate on admission and percentage of lung involvement on admission CTs, only SOFA score (OR 1.32, 95% CI 1.08-1.62) and lung involvement (OR 1.06, 95% CI 1.01-1.11) were significantly associated with subsequent ECMO allocation. Receiver operating characteristic (ROC) curves showed an area under the curve (AUC) of 0.83 (95% CI 0.73-0.94) for lung involvement on admission CT and 0.82 (95% CI 0.72-0.91) for SOFA scores on ICU admission. A combined parameter of SOFA on ICU admission and lung involvement on admission CT yielded an AUC of 0.91 (0.84-0.97) with a sensitivity of 0.93 and a specificity of 0.84 for ECMO prediction; (4) Conclusions: AI-based assessment of lung involvement on CT scans on admission to the hospital and SOFA scoring, especially if combined, can be used as risk stratification tools for subsequent requirement for ECMO therapy in patients with severe COVID-19 disease to improve resource management in ICU settings.

4.
Diagnostics ; 10(12):1108, 2020.
Article in English | ScienceDirect | ID: covidwho-984342

ABSTRACT

(1) Background: To assess the value of chest CT imaging features of COVID-19 disease upon hospital admission for risk stratification of invasive ventilation (IV) versus no or non-invasive ventilation (non-IV) during hospital stay. (2) Methods: A retrospective single-center study was conducted including all patients admitted during the first three months of the pandemic at our hospital with PCR-confirmed COVID-19 disease and admission chest CT scans (n = 69). Using clinical information and CT imaging features, a 10-point ordinal risk score was developed and its diagnostic potential to differentiate a severe (IV-group) from a more moderate course (non-IV-group) of the disease was tested. (3) Results: Frequent imaging findings of COVID-19 pneumonia in both groups were ground glass opacities (91.3%), consolidations (53.6%) and crazy paving patterns (31.9%). Characteristics of later stages such as subpleural bands were observed significantly more often in the IV-group (52.2% versus 26.1%, p = 0.032). Using information directly accessible during a radiologist’s reporting, a simple risk score proved to reliably differentiate between IV- and non-IV-groups (AUC: 0.89 (95% CI 0.81–0.96), p <0.001). (4) Conclusions: Information accessible from admission CT scans can effectively and reliably be used in a scoring model to support risk stratification of COVID-19 patients to improve resource and allocation management of hospitals.

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