One year after ICU admission for severe community-acquired pneumonia of bacterial, viral or unidentified etiology. What are the outcomes?

INTRODUCTION: Multiplex polymerase chain reaction (mPCR) for respiratory virus testing is increasingly used in community-acquired pneumonia (CAP), however data on one-year outcome in intensive care unit (ICU) patients with reference to the causative pathogen are scarce. MATERIALS AND METHODS: We performed a single-center retrospective study in 123 ICU patients who had undergone respiratory virus testing for CAP by mPCR and with known one-year survival status. Functional status including dyspnea (mMRC score), autonomy (ADL Katz score) and need for new home-care ventilatory support was assessed at a one-year post-ICU follow-up. Mortality rates and functional status were compared in patients with CAP of a bacterial, viral or unidentified etiology one year after ICU admission. RESULTS: The bacterial, viral and unidentified groups included 19 (15.4%), 37 (30.1%), and 67 (54.5%) patients, respectively. In multivariate analysis, one-year mortality in the bacterial group was higher compared to the viral group (HR 2.92, 95% CI 1.71-7.28, p = 0.02) and tended to be higher compared to the unidentified etiology group (p = 0.06); but no difference was found between the viral and the unidentified etiology group (p = 0.43). In 64/83 one-year survivors with a post-ICU follow-up consultation, there were no differences in mMRC score, ADL Katz score and new home-care ventilatory support between the groups (p = 0.52, p = 0.37, p = 0.24, respectively). Severe dyspnea (mMRC score = 4 or death), severe autonomy deficiencies (ADL Katz score ≤ 2 or death), and major adverse respiratory events (new home-care ventilatory support or death) were observed in 52/104 (50.0%), 47/104 (45.2%), and 65/104 (62.5%) patients, respectively; with no difference between the bacterial, viral and unidentified group: p = 0.58, p = 0.06, p = 0.61, respectively. CONCLUSIONS: CAP of bacterial origin had a poorer outcome than CAP of viral or unidentified origin. At one-year, impairment of functional status was frequently observed, with no difference according to the etiology.

Unsupervised clustering reveals phenotypes of AKI in ICU COVID-19 patients.

Background: Acute Kidney Injury (AKI) is a very frequent condition, occurring in about one in three patients admitted to an intensive care unit (ICU). AKI is a syndrome defined as a sudden decrease in glomerular filtration rate. However, this unified definition does not reflect the various mechanisms involved in AKI pathophysiology, each with its own characteristics and sensitivity to therapy. In this study, we aimed at developing an innovative machine learning based method able to subphenotype AKI according to its pattern of risk factors. Methods: We adopted a three-step pipeline of analyses. First, we looked for factors associated with AKI using a generalized additive model. Second, we calculated the importance of each identified AKI related factor in the estimated AKI risk to find the main risk factor for AKI, at the single patient level. Lastly, we clusterized AKI patients according to their profile of risk factors and compared the clinical characteristics and outcome of every cluster. We applied this method to a cohort of severe COVID-19 patients hospitalized in the ICU of the Geneva University Hospitals. Results: Among the 248 patients analyzed, we found 7 factors associated with AKI development. Using the individual expression of these factors, we identified three groups of AKI patients, based on the use of Lopinavir/Ritonavir, baseline eGFR, use of dexamethasone and AKI severity. The three clusters expressed distinct characteristics in terms of AKI severity and recovery, metabolic patterns and hospital mortality. Conclusion: We propose here a new method to phenotype AKI patients according to their most important individual risk factors for AKI development. When applied to an ICU cohort of COVID-19 patients, we were able to differentiate three groups of patients. Each expressed specific AKI characteristics and outcomes, which probably reflect a distinct pathophysiology.

Unsupervised clustering reveals phenotypes of AKI in ICU COVID-19 patients

Background Acute Kidney Injury (AKI) is a very frequent condition, occurring in about one in three patients admitted to an intensive care unit (ICU). AKI is a syndrome defined as a sudden decrease in glomerular filtration rate. However, this unified definition does not reflect the various mechanisms involved in AKI pathophysiology, each with its own characteristics and sensitivity to therapy. In this study, we aimed at developing an innovative machine learning based method able to subphenotype AKI according to its pattern of risk factors. Methods We adopted a three-step pipeline of analyses. First, we looked for factors associated with AKI using a generalized additive model. Second, we calculated the importance of each identified AKI related factor in the estimated AKI risk to find the main risk factor for AKI, at the single patient level. Lastly, we clusterized AKI patients according to their profile of risk factors and compared the clinical characteristics and outcome of every cluster. We applied this method to a cohort of severe COVID-19 patients hospitalized in the ICU of the Geneva University Hospitals. Results Among the 248 patients analyzed, we found 7 factors associated with AKI development. Using the individual expression of these factors, we identified three groups of AKI patients, based on the use of Lopinavir/Ritonavir, baseline eGFR, use of dexamethasone and AKI severity. The three clusters expressed distinct characteristics in terms of AKI severity and recovery, metabolic patterns and hospital mortality. Conclusion We propose here a new method to phenotype AKI patients according to their most important individual risk factors for AKI development. When applied to an ICU cohort of COVID-19 patients, we were able to differentiate three groups of patients. Each expressed specific AKI characteristics and outcomes, which probably reflect a distinct pathophysiology.

Delayed intubation is associated with mortality in patients with severe COVID-19: A single-centre observational study in Switzerland.

INTRODUCTION: Switzerland experienced two waves of COVID-19 in 2020, but with a different ICU admission and treatment management strategy. The timing of ICU admission and intubation remains a matter of debate in severe patients. The aim of our study was to describe the characteristics of ICU patients between two subsequent waves of COVID-19 who underwent a different management strategy and to assess whether the timing of intubation was associated with differences in mortality. PATIENTS AND METHODS: We conducted a prospective observational study of all adult patients with acute respiratory failure due to COVID-19 who required intubation between the 9th of March 2020 and the 9th of January 2021 in the intensive care unit (ICU) at Geneva University Hospitals, Switzerland. RESULTS: Two hundred twenty-three patients were intubated during the study period; 124 during the first wave, and 99 during the second wave. Patients admitted to the ICU during the second wave had a higher SAPS II severity score (52.5 vs. 60; p = 0.01). The time from hospital admission to intubation was significantly longer during the second compared to the first wave (4 days [IQR, 1-7] vs. 2 days [IQR, 0-4]; p < 0.01). All-cause ICU mortality was significantly higher during the second wave (42% vs. 23%; p < 0.01). In a multivariate analysis, the delay between hospital admission and intubation was significantly associated with ICU mortality (OR 3.25 [95% CI, 1.38-7.67]; p < 0.05). CONCLUSIONS: In this observational study, delayed intubation was associated with increased mortality in patients with severe COVID-19. Further randomised controlled trials are needed.

Decreased CRRT Filter Lifespan in COVID-19 ICU Patients.

(1) Background: Increased thromboembolic events and an increased need for continuous renal replacement therapy (CRRT) have been frequently reported in COVID-19 patients. Our aim was to investigate CRRT filter lifespan in intensive care unit (ICU) COVID-19 patients. (2) Methods: We compared CRRT adjusted circuit lifespan in COVID-19 patients admitted for SARS-CoV-2 infection to a control group of patients admitted for septic shock of pulmonary origin other than COVID-19. Both groups underwent at least one session of CRRT for AKI. (3) Results: Twenty-six patients (13 in each group) were included. We analysed 117 CRRT circuits (80 in the COVID-19 group and 37 in the control group). The adjusted filter lifespan was shorter in the COVID-19 group (17 vs. 39 h, p < 0.001). This trend persisted after adjustment for confounding factors (-14 h, p = 0.037). Before CRRT circuit clotting, the COVID-19 group had a more procoagulant profile despite higher heparin infusion rates. Furthermore, we reported a decreased relation between activated partial thromboplastin time (aPTT) and cumulative heparin dose in COVID-19 patients when compared to historical data of 23,058 patients, suggesting a heparin resistance. (4) Conclusion: COVID-19 patients displayed a shorter CRRT filter lifespan that could be related to a procoagulant profile and heparin resistance.

Inappropriate Heart Rate Response to Hypotension in Critically Ill COVID-19-Associated Acute Kidney Injury.

Angiotensin-converting enzyme 2 (ACE2) receptor of severe acute respiratory syndrome coronavirus 2 is involved in baroreflex control mechanisms. We hypothesize that severe coronavirus infectious disease 2019 (COVID-19) patients may show an alteration in baroreflex-mediated heart rate changes in response to arterial hypotension. A pilot study was conducted to assess the response to hypotension in relation to continuous venovenous hemodiafiltration (CVVHDF) in critically ill patients with PCR-confirmed COVID-19 (from February to April 2020) and in critically ill non-COVID-19 patients with sepsis (from February 2018 to February 2020). The endpoint was a change in the heart rate in response to CVVHDF-induced hypotension. The association between COVID-19 status and heart rate change was estimated using linear regression. The study population included 6 COVID-19 patients (67% men; age 58 (53-64) years) and 12 critically ill non-COVID-19 patients (58% men; age 67 (51-71) years). Baseline characteristics, laboratory findings, hemodynamic parameters, and management before CVVHDF-induced hypotension were similar between the two groups, with the exception of a higher positive end-expiratory pressure and doses of propofol and midazolam administered in COVID-19 patients. Changes in the heart rate were significantly lower in COVID-19 patients as compared to critically ill non-COVID-19 patients (-7 (-9; -2) vs. 2 (2;5) bpm, p = 0.003), while the decrease in mean arterial blood pressure was similar between groups. The COVID-19 status was independently associated with a lower change in the heart rate (-11 (-20; -2) bpm; p = 0.03). Our findings suggest an inappropriate heart rate response to hypotension in severe COVID-19 patients compared to critically ill non-COVID-19 patients.

Timing of VV-ECMO therapy implementation influences prognosis of COVID-19 patients.

INTRODUCTION: Current knowledge on the use of extracorporeal membrane oxygenation (ECMO) in COVID-19 remains limited to small series and registry data. In the present retrospective monocentric study, we report on our experience, our basic principles, and our results in establishing and managing ECMO in critically ill COVID-19 patients. METHODS: A cohort study was conducted in patients with severe acute respiratory distress syndrome (ARDS) related to COVID-19 pneumonia admitted to the ICU of the Geneva University Hospitals and supported by VV-ECMO from March 14 to May 31. The VV-ECMO implementation criteria were defined according to an institutional algorithm validated by the local crisis unit and the Swiss Society of Intensive Care Medicine. RESULTS: Out of 137 ARDS patients admitted to our ICU, 10 patients (age 57 ± 4 years, BMI 31.5 ± 5 kg/m2 , and SAPS II score 56 ± 3) were put on VV-ECMO. The mean duration of mechanical ventilation before ECMO and mean time under ECMO were 7 ± 3 days and 19 ± 11 days, respectively. The ICU and hospital length of stay were 26 ± 11 and 35 ± 10 days, respectively. The survival rate for patients on ECMO was 40%. The comparative analysis between survivors and non-survivors highlighted that survivors had a significantly shorter mechanical ventilation duration before ECMO (4 ± 2 days vs. 9 ± 2 days, p = 0.01). All the patients who had more than 150 h of mechanical ventilation before the application of ECMO ultimately died. CONCLUSION: The present results suggest that VV-ECMO can be safely utilized in appropriately selected COVID-19 patients with refractory hypoxemia. The main information for clinicians is that late VV-ECMO therapy (i.e., beyond the seventh day of mechanical ventilation) seems futile.