Outcomes of Patients With Active Cancer and COVID-19 in the Intensive-Care Unit: A Multicenter Ambispective Study

Background

Several studies report an increased susceptibility to SARS-CoV-2 infection in cancer patients. However, data in the intensive care unit (ICU) are scarce.

Research Question

We aimed to investigate the association between active cancer and mortality among patients requiring organ support in the ICU.

Study Design and Methods

In this ambispective study encompassing 17 hospitals in France, we included all adult active cancer patients with SARS-CoV-2 infection requiring organ support and admitted in ICU. For each cancer patient, we included 3 non cancer patients as controls. Patients were matched at the same ratio using the inverse probability weighting approach based on a propensity score assessing the probability of cancer at admission. Mortality at day 60 after ICU admission was compared between cancer patients and non-cancer patients using primary logistic regression analysis and secondary multivariable analyses.

Results

Between March 12, 2020 and March 8, 2021, 2608 patients were admitted with SARS-CoV-2 infection in our study, accounting for 2.8% of the total population of patients with SARS-CoV-2 admitted in all French ICUs within the same period. Among them, 105 (n=4%) presented with cancer (51 patients had hematological malignancy and 54 patients had solid tumors). 409 of 420 patients were included in the propensity score matching process, of whom 307 patients in the non-cancer group and 102 patients in the cancer group. 145 patients (35%) died in the ICU at day 60, 59 (56%) with cancer and 86 (27%) without cancer. In the primary logistic regression analysis, the odds ratio for death associated to cancer was 2.3 (95%CI 1.24 - 4.28, p=0.0082) higher for cancer patients than for a non-cancer patient at ICU admission. Exploratory multivariable analyses showed that solid tumor (OR: 2.344 (0.87-6.31), p=0.062) and hematological malignancies (OR: 4.144 (1.24-13.83), p=0.062) were independently associated with mortality.

Interpretation

Patients with cancer and requiring ICU admission for SARS-CoV-2 infection had an increased mortality, hematological malignancy harboring the higher risk in comparison to solid tumors.

Geoeconomic variations in epidemiology, ventilation management, and outcomes in invasively ventilated intensive care unit patients without acute respiratory distress syndrome: a pooled analysis of four observational studies

Background

Geoeconomic variations in epidemiology, the practice of ventilation, and outcome in invasively ventilated intensive care unit (ICU) patients without acute respiratory distress syndrome (ARDS) remain unexplored. In this analysis we aim to address these gaps using individual patient data of four large observational studies.

Methods

In this pooled analysis we harmonised individual patient data from the ERICC, LUNG SAFE, PRoVENT, and PRoVENT-iMiC prospective observational studies, which were conducted from June, 2011, to December, 2018, in 534 ICUs in 54 countries. We used the 2016 World Bank classification to define two geoeconomic regions: middle-income countries (MICs) and high-income countries (HICs). ARDS was defined according to the Berlin criteria. Descriptive statistics were used to compare patients in MICs versus HICs. The primary outcome was the use of low tidal volume ventilation (LTVV) for the first 3 days of mechanical ventilation. Secondary outcomes were key ventilation parameters (tidal volume size, positive end-expiratory pressure, fraction of inspired oxygen, peak pressure, plateau pressure, driving pressure, and respiratory rate), patient characteristics, the risk for and actual development of acute respiratory distress syndrome after the first day of ventilation, duration of ventilation, ICU length of stay, and ICU mortality.

Findings

Of the 7608 patients included in the original studies, this analysis included 3852 patients without ARDS, of whom 2345 were from MICs and 1507 were from HICs. Patients in MICs were younger, shorter and with a slightly lower body-mass index, more often had diabetes and active cancer, but less often chronic obstructive pulmonary disease and heart failure than patients from HICs. Sequential organ failure assessment scores were similar in MICs and HICs. Use of LTVV in MICs and HICs was comparable (42·4% vs 44·2%; absolute difference –1·69 [–9·58 to 6·11] p=0·67; data available in 3174 [82%] of 3852 patients). The median applied positive end expiratory pressure was lower in MICs than in HICs (5 [IQR 5–8] vs 6 [5–8] cm H₂O; p=0·0011). ICU mortality was higher in MICs than in HICs (30·5% vs 19·9%; p=0·0004; adjusted effect 16·41% [95% CI 9·52–23·52]; p<0·0001) and was inversely associated with gross domestic product (adjusted odds ratio for a US$10 000 increase per capita 0·80 [95% CI 0·75–0·86]; p<0·0001).

Interpretation

Despite similar disease severity and ventilation management, ICU mortality in patients without ARDS is higher in MICs than in HICs, with a strong association with country-level economic status.

Funding

No funding.

Effects of positive end-expiratory pressure strategy in supine and prone position on lung and chest wall mechanics in acute respiratory distress syndrome

Background

In acute respiratory distress syndrome (ARDS) patients, it has recently been proposed to set positive end-expiratory pressure (PEEP) by targeting end-expiratory transpulmonary pressure. This approach, which relies on the measurement of absolute esophageal pressure (Pes), has been used in supine position (SP) and has not been investigated in prone position (PP). Our purposes were to assess Pes-guided strategy to set PEEP in SP and in PP as compared with a PEEP/FIO₂ table and to explore the early (1 h) and late (16 h) effects of PP on lung and chest wall mechanics.

Results

We performed a prospective, physiologic study in two ICUs in university hospitals on ARDS patients with PaO₂/FIO₂ < 150 mmHg. End-expiratory Pes (Pes,ee) was measured in static (zero flow) condition. Patients received PEEP set according to a PEEP/F_IO₂ table then according to the Pes-guided strategy targeting a positive (3 ± 2 cmH₂O) static end-expiratory transpulmonary pressure in SP. Then, patients were turned to PP and received same amount of PEEP from PEEP/F_IO₂ table then Pes-guided strategy. Respiratory mechanics, oxygenation and end-expiratory lung volume (EELV) were measured after 1 h of each PEEP in each position. For the rest of the 16-h PP session, patients were randomly allocated to either PEEP strategy with measurements done at the end. Thirty-eight ARDS patients (27 male), mean ± SD age 63 ± 13 years, were included. There were 33 primary ARDS and 26 moderate ARDS. PaO₂/FIO₂ ratio was 120 ± 23 mmHg. At same PEEP/FIO₂ table-related PEEP, Pes,ee averaged 9 ± 4 cmH₂O in both SP and PP (P = 0.88). With PEEP/F_IO₂ table and Pes-guided strategy, PEEP was 10 ± 2 versus 12 ± 4 cmH₂O in SP and 10 ± 2 versus 12 ± 5 cmH₂O in PP (PEEP strategy effect P = 0.05, position effect P = 0.96, interaction P = 0.96). With the Pes-guided strategy, chest wall elastance increased regardless of position. Lung elastance and transpulmonary driving pressure decreased in PP, with no effect of PEEP strategy. Both PP and Pes-guided strategy improved oxygenation without interaction. EELV did not change with PEEP strategy. At the end of PP session, respiratory mechanics did not vary but EELV and PaO₂/F_IO₂ increased while PaCO₂ decreased.

Conclusions

There was no impact of PP on Pes measurements. PP had an immediate improvement effect on lung mechanics and a late lung recruitment effect independent of PEEP strategy.

Electronic supplementary material

The online version of this article (10.1186/s13613-018-0434-2) contains supplementary material, which is available to authorized users.

Change in cardiac output during Trendelenburg maneuver is a reliable predictor of fluid responsiveness in patients with acute respiratory distress syndrome in the prone position under protective ventilation

Background

Predicting fluid responsiveness may help to avoid unnecessary fluid administration during acute respiratory distress syndrome (ARDS). The aim of this study was to evaluate the diagnostic performance of the following methods to predict fluid responsiveness in ARDS patients under protective ventilation in the prone position: cardiac index variation during a Trendelenburg maneuver, cardiac index variation during an end-expiratory occlusion test, and both pulse pressure variation and change in pulse pressure variation from baseline during a tidal volume challenge by increasing tidal volume (VT) to 8 ml.kg^-1.

Methods

This study is a prospective single-center study, performed in a medical intensive care unit, on ARDS patients with acute circulatory failure in the prone position. Patients were studied at baseline, during a 1-min shift to the Trendelenburg position, during a 15-s end-expiratory occlusion, during a 1-min increase in VT to 8 ml.kg^-1, and after fluid administration. Fluid responsiveness was deemed present if cardiac index assessed by transpulmonary thermodilution increased by at least 15% after fluid administration.

Results

There were 33 patients included, among whom 14 (42%) exhibited cardiac arrhythmia at baseline and 15 (45%) were deemed fluid-responsive. The area under the receiver operating characteristic (ROC) curve of the pulse contour-derived cardiac index change during the Trendelenburg maneuver and the end-expiratory occlusion test were 0.90 (95% CI, 0.80–1.00) and 0.65 (95% CI, 0.46–0.84), respectively. An increase in cardiac index ≥ 8% during the Trendelenburg maneuver enabled diagnosis of fluid responsiveness with sensitivity of 87% (95% CI, 67–100), and specificity of 89% (95% CI, 72–100). The area under the ROC curve of pulse pressure variation and change in pulse pressure variation during the tidal volume challenge were 0.52 (95% CI, 0.24–0.80) and 0.59 (95% CI, 0.31–0.88), respectively.

Conclusions

Change in cardiac index during a Trendelenburg maneuver is a reliable test to predict fluid responsiveness in ARDS patients in the prone position, while neither change in cardiac index during end-expiratory occlusion, nor pulse pressure variation during a VT challenge reached acceptable predictive performance to predict fluid responsiveness in this setting.

Trial registration

ClinicalTrials.gov, NCT01965574. Registered on 16 October 2013. The trial was registered 6 days after inclusion of the first patient.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-017-1881-0) contains supplementary material, which is available to authorized users.

Predicting Extubation Outcome by Cough Peak Flow Measured Using a Built-in Ventilator Flow Meter

BACKGROUND

Successful weaning from mechanical ventilation depends on the patient's ability to cough efficiently. Cough peak flow (CPF) could predict extubation success using a dedicated flow meter but required patient disconnection. We aimed to predict extubation outcome using an overall model, including cough performance assessed by a ventilator flow meter.

METHODS

This was a prospective observational study conducted from November 2014 to October 2015. Before and after a spontaneous breathing trial, subjects were encouraged to cough as strongly as possible before freezing the ventilator screen to assess CPF and tidal volume (V_T) in the preceding inspiration. Early extubation success rate was defined as the proportion of subjects not re-intubated 48 h after extubation. Diagnostic performance of CPF and V_T was assessed by using the area under the curve of the receiver operating characteristic curve. Cut-off values for CPF and V_T were defined according to median values and used to describe the performance of a predictive test combining them with risk factors of early extubation failure.

RESULTS

Among 673 subjects admitted, 92 had a cough assessment before extubation. For the 81 subjects with early extubation success, the median CPF was -67.7 L/min, and median V_T was 0.646 L. For the 11 subjects with early extubation failure, the median CPF was -57.3 L/min, and median V_T was 0.448 L. Area under the curve was 0.61 (95% CI 0.37-0.83) for CPF and 0.64 (95% CI 0.42-0.84) for CPF/V_T combined. After dichotomization (CPF < -60 L/min or V_T > 0.55 L), there was a synergistic effect to predict early extubation success (P < .001). The predictive value of success reached 94.2% for CPF/V_T combined. The overall model including pH before extubation < 7.45 reached a 66.7% predictive value of failure.

CONCLUSIONS

CPF measured using the flow meter of an ICU ventilator was able to predict extubation success and to build a composite score to predict extubation failure. The results were close to that found in previous studies that used a dedicated flow meter. This could help to identify high-risk subjects to prevent extubation failure. (ClinicalTrials.gov registration NCT02847221.).

Pulse Wave Transit Time Measurements of Cardiac Output in Septic Shock Patients: A Comparison of the Estimated Continuous Cardiac Output System with Transthoracic Echocardiography

Background

We determined reliability of cardiac output (CO) measured by pulse wave transit time cardiac output system (esCCO system; CO_esCCO) vs transthoracic echocardiography (CO_TTE) in mechanically ventilated patients in the early phase of septic shock. A secondary objective was to assess ability of esCCO to detect change in CO after fluid infusion.

Methods

Mechanically ventilated patients admitted to the ICU, aged >18 years, in sinus rhythm, in the early phase of septic shock were prospectively included. We performed fluid infusion of 500ml of crystalloid solution over 20 minutes and recorded CO by EsCCO and TTE immediately before (T0) and 5 minutes after (T1) fluid administration. Patients were divided into 2 groups (responders and non-responders) according to a threshold of 15% increase in CO_TTE in response to volume expansion.

Results

In total, 25 patients were included, average 64±15 years, 15 (60%) were men. Average SAPSII and SOFA scores were 55±21.3 and 13±2, respectively. ICU mortality was 36%. Mean cardiac output at T0 was 5.8±1.35 L/min by esCCO and 5.27±1.17 L/min by CO_TTE. At T1, respective values were 6.63 ± 1.57 L/min for esCCO and 6.10±1.29 L/min for CO_TTE. Overall, 12 patients were classified as responders, 13 as non-responders by the reference method. A threshold of 11% increase in CO_esCCO was found to discriminate responders from non-responders with a sensitivity of 83% (95% CI, 0.52-0.98) and a specificity of 77% (95% CI, 0.46-0.95).

Conclusion

We show strong correlation esCCO and echocardiography for measuring CO, and change in CO after fluid infusion in ICU patients.