Extracorporeal membrane oxygenation support for SARS-CoV-2: a multi-centered, prospective, observational study in critically ill 92 patients in Saudi Arabia.
Extracorporeal membrane oxygenation (ECMO) has been used as a rescue strategy in patients with severe with acute respiratory distress syndrome (ARDS) due to SARS-CoV-2 infection, but there has been little evidence of its efficacy.
To describe the effect of ECMO rescue therapy on patient-important outcomes in patients with severe SARS-CoV-2.
A case series study was conducted for the laboratory-confirmed SARS-CoV-2 patients who were admitted to the ICUs of 22 Saudi hospitals, between March 1, 2020, and October 30, 2020, by reviewing patient's medical records prospectively.
ECMO use was associated with higher in-hospital mortality (40.2% vs. 48.9%; p = 0.000); lower COVID-19 virological cure (41.3% vs 14.1%, p = 0.000); and longer hospitalization (20.2 days vs 29.1 days; p = 0.000), ICU stay (12.6 vs 26 days; p = 0.000) and mechanical ventilation use (14.2 days vs 22.4 days; p = 0.000) compared to non-ECMO group. Also, there was a high number of patients with septic shock (19.6%) and multiple organ failure (10.9%); and more complications occurred at any time during hospitalization [pneumothorax (5% vs 29.3%, p = 0.000), bleeding requiring blood transfusion (7.1% vs 38%, p = 0.000), pulmonary embolism (6.4% vs 15.2%, p = 0.016), and gastrointestinal bleeding (3.3% vs 8.7%, p = 0.017)] in the ECMO group. However, PaO2 was significantly higher in the 72-h post-ECMO initiation group and PCO2 was significantly lower in the 72-h post-ECMO start group than those in the 12-h pre-ECMO group (62.9 vs. 70 mmHg, p = 0.002 and 61.8 vs. 51 mmHg, p = 0.042, respectively).
Following the use of ECMO, the mortality rate of patients and length of ICU and hospital stay were not improved. However, these findings need to be carefully interpreted, as most of our cohort patients were relatively old and had multiple severe comorbidities. Future randomized trials, although challenging to conduct, are highly needed to confirm or dispute reported observations.
Alhumaid S
,Al Mutair A
,Alghazal HA
,Alhaddad AJ
,Al-Helal H
,Al Salman SA
,Alali J
,Almahmoud S
,Alhejy ZM
,Albagshi AA
,Muhammad J
,Khan A
,Sulaiman T
,Al-Mozaini M
,Dhama K
,Al-Tawfiq JA
,Rabaan AA
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Outcomes of Adult Patients With COVID-19 Transitioning From Venovenous to Venoarterial or Hybrid Extracorporeal Membrane Oxygenation in the Extracorporeal Life Support Organization Registry.
This retrospective analysis of the Extracorporeal Life Support Organization (ELSO) registry evaluates the outcomes and identifies risk factors associated with conversion from initial venovenous extracorporeal membrane oxygenation (ECMO) support to venoarterial or hybrid ECMO in patients with coronavirus disease 2019 (COVID-19). We collected deidentified data on all adult patients (≥18 years old) diagnosed with COVID who received venovenous extracorporeal membrane oxygenation between March 2020 and November 2022. Patients initially placed on an ECMO configuration other than venovenous (VV) ECMO were excluded from the analysis. Our analysis included data from 12,850 patients, of which 393 (3.1%) transitioned from VV ECMO to an alternative mode. The primary outcome measure was in-hospital mortality, and the conversion group exhibited a higher in-hospital mortality rate. We also examined baseline variables, including demographic information, biochemical labs, and inotrope requirements. Univariate analysis revealed that pre-ECMO arrest, the need for renal replacement therapy, and the use of inotropic agents, particularly milrinone, were strongly associated with the risk of conversion. Notably, even after implementing a 3:1 propensity score matching, the impact of conversion on both mortality and complications remained substantial. Our study underscores an elevated risk of mortality for COVID-19 patients initially treated with VV ECMO who subsequently require conversion to VA-ECMO or hybrid ECMO.
Nguyen K
,Altibi A
,Prasad P
,Mukundan S
,Shekar K
,Ramanathan K
,Zakhary B
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Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.
Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided.
(1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS?
Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses.
Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS.
Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments.
Level III, diagnostic study.
Lee CC
,Chen CW
,Yen HK
,Lin YP
,Lai CY
,Wang JL
,Groot OQ
,Janssen SJ
,Schwab JH
,Hsu FM
,Lin WH
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Extracorporeal Membrane Oxygenation with Right Ventricular Assist Device for COVID-19 ARDS.
Right ventricular failure is an underrecognized consequence of COVID-19 pneumonia. Those with severe disease are treated with extracorporeal membrane oxygenation (ECMO) but with poor outcomes. Concomitant right ventricular assist device (RVAD) may be beneficial.
A retrospective analysis of intensive care unit patients admitted with COVID-19 ARDS (Acute Respiratory Distress Syndrome) was performed. Nonintubated patients, those with acute kidney injury, and age > 75 were excluded. Patients who underwent RVAD/ECMO support were compared with those managed via invasive mechanical ventilation (IMV) alone. The primary outcome was in-hospital mortality. Secondary outcomes included 30-d mortality, acute kidney injury, length of ICU stay, and duration of mechanical ventilation.
A total of 145 patients were admitted to the ICU with COVID-19. Thirty-nine patients met inclusion criteria. Of these, 21 received IMV, and 18 received RVAD/ECMO. In-hospital (52.4 versus 11.1%, P = 0.008) and 30-d mortality (42.9 versus 5.6%, P= 0.011) were significantly lower in patients treated with RVAD/ECMO. Acute kidney injury occurred in 15 (71.4%) patients in the IMV group and zero RVAD/ECMO patients (P< 0.001). ICU (11.5 versus 21 d, P= 0.067) and hospital (14 versus 25.5 d, P = 0.054) length of stay were not significantly different. There were no RVAD/ECMO device complications. The duration of mechanical ventilation was not significantly different (10 versus 5 d, P = 0.44).
RVAD support at the time of ECMO initiation resulted in the no secondary end-organ damage and higher in-hospital and 30-d survival versus IMV in specially selected patients with severe COVID-19 ARDS. Management of severe COVID-19 ARDS should prioritize right ventricular support.
Cain MT
,Smith NJ
,Barash M
,Simpson P
,Durham LA 3rd
,Makker H
,Roberts C
,Falcucci O
,Wang D
,Walker R
,Ahmed G
,Brown SA
,Nanchal RS
,Joyce DL
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