Patients with coronavirus disease 2019 (COVID-19) can have neurologic manifestations, including acute cerebrovascular events and coma (1–6). In patients with severe COVID-19 requiring admission to the ICU, coma occurs in approximately 15% of patients and is typically diagnosed during the second week of hospital admission (2,5). Little is known about the etiology and the effect of coma in patients with COVID-19 presenting to an ICU for treatment of acute respiratory distress syndrome (ARDS).
During the COVID-19 pandemic, unprecedented numbers of patients have required sedation in the ICUs and other hospital locations due to prolonged ventilator dependence (7). Although sedation is typically required to facilitate mechanical ventilation, deeper sedation levels may be favored by ICU staff to reduce the possibility of a patient’s self-extubation, which carries an increased risk of exposing staff and other patients to COVID-19. Long-acting sedatives were also used more frequently due to impending national shortages of commonly used short-acting sedatives. Finally, clinicians might have favored deep sedation to allow tolerance of lung-protective ventilation strategies.
We tested the hypothesis that patients with COVID-19–associated ARDS compared with patients with ARDS due to other etiologies are at higher risk of increased in-hospital mortality. Contingent on this hypothesis, we also hypothesized that the association of COVID-19 and in-hospital mortality was mediated by a high percentage of comatose days as a consequence of deep sedation during mechanical ventilation.
MATERIALS AND METHODS
This retrospective hospital registry study was approved by the Committee on Clinical Investigations at Beth Israel Deaconess Medical Center (BIDMC) in Boston, MA (protocol number 2020P000694) and met criteria for exemption from review. BIDMC is an academic teaching hospital of Harvard Medical School and a tertiary referral center covering intensive care of eight hospitals in the Beth Israel Lahey Health system. During the surge of COVID-19, the medical center doubled its ICU capacity to a total of 140 beds.
We combined multiple electronic data sources to obtain comprehensive information for all included patients. Demographic data, as well as a patients’ past medical history, were collected from online medical records. Laboratory values and ICU data including level of consciousness, ventilator variables, and drug administration were extracted from Metavision, an electronic medical record interface routinely used in all ICUs. Encounter dates and discharge information were retrieved from Casemix and the Admission Discharge Transfer database. Radiographic imaging reports were obtained from the radiology database (supplementary document, section 1, https://links.lww.com/CCM/G322).
Adult patients (≥ 18 yr) admitted to the ICUs were included if they were mechanically ventilated and were diagnosed with COVID-19 between March 2020 and May 2020, based on World Health Organization interim guidelines (8), or were diagnosed with ARDS between January 2008 and June 2019. Patients with missing baseline characteristics for the propensity matching model were excluded.
Primary Outcomes and Analyses
We tested outcomes in an a priori defined, hierarchical order. The primary outcome was in-hospital mortality. The coprimary outcome was the percentage of comatose days.
The level of consciousness was routinely recorded at least every 4 hours using the Richmond Agitation Sedation Scale (RASS). Patients with a mean RASS score of –3 to –5 were classified as comatose based on previously published literature, irrespective of whether the state was induced by disease or sedation (9). The daily sedation variables during the first 10 days of mechanical ventilation are provided in eTable 2 (https://links.lww.com/CCM/G322). We defined the percentage of days spent in coma as the ratio of days with coma during the first 10 days of mechanical ventilation for each patient. The percentage of comatose days was dichotomized into low and high by using the median as the cut off value.
In the primary analysis, we tested the hypothesis that COVID-19 patients had a higher risk of in-hospital mortality compared with non–COVID-19 ARDS patients. Contingent on this assumption, we tested the coprimary hypothesis that the higher percentage of coma was a mediator of in-hospital mortality in COVID-19 patients.
Secondary Outcomes and Analyses
In secondary analyses, we investigated the causes that might affect coma. Sedative and analgesic medications used during mechanical ventilation, the Sedation Burden Index (SBI) during the first 10 days of mechanical ventilation, and structural brain lesions were compared between COVID-19 and non–COVID-19 patients. We tested the hypothesis that the hypnotic agent dose was associated with coma and mediated coma in COVID-19 patients. In addition, we tested the hypothesis that the association between sedation-related coma and mortality may be different than the association between neurologic injury-related coma and mortality.
We collected the daily cumulative doses of sedatives, analgesics, and neuromuscular blocking agents (NMBAs). Opioid doses were converted to oral morphine equivalents, and benzodiazepines were converted to midazolam equivalents for comparison (10–12). For simplification and better comparison between an individual’s exposure to sedative and analgesic medications, we calculated the SBI which was defined as the cumulative burden from every sedative or analgesic medication that patients received on each day during the 10-day mechanical ventilated period. The average SBI over 10 days was calculated for each patient. To calculate the hypnotic agent dose, we then identified the patient with the highest average SBI over 10 days and expressed individual values as the percent maximum value (supplementary document, section 2, https://links.lww.com/CCM/G322).
All CT scans of the brain and neurologic consultation results were reviewed and confirmed by an experienced intensivist.
Propensity Score Matching
One-to-two propensity score matching for patients with COVID-19 and without COVID-19 was performed as described detailed in the supplementary document, section 3 (https://links.lww.com/CCM/G322) (13,14). Propensity score estimates, calibrated for both the odd of the exposure (COVID-19–associated ARDS) and the outcome (in-hospital mortality) for each patient, were derived from clinical variables; demographic characteristics (age, sex, and body mass index), comorbidities (Charlson Comorbidity Index), disease severity (Acute Physiology and Chronic Health Evaluation II score), organ failure (renal impairment and severe liver injury), vasopressor support, and baseline ventilator variables at onset of mechanical ventilation (respiratory system compliance, Pao2:Fio2 [P/F] ratio, Paco2, and alveolar–arterial [A-a] gradient) (15–17). Covariates with residual imbalances following propensity score matching (standardized difference ≥ 0.1) were added as adjustment covariates to a model following matching.
Sensitivity and Exploratory Analyses
We conducted several sensitivity analyses to test the robustness of our findings. In the primary analysis, we matched for possible predictors of the exposure and outcome (18). In order to address a potential selection bias, we repeated the analysis using the same covariate model in the complete, unselected cohort of all ARDS patients, which are described in detail with other sensitivity analyses in the supplementary document, section 4 (https://links.lww.com/CCM/G322).
With an exploratory intent, the hypnotic agent doses were compared in subgroups of patients who received NMBAs and prone positioning. We examined the trend in ARDS treatment by means of NMBA infusion, prone positioning, and sedative medications used during mechanical ventilation, compared between the COVID-19 pandemic period and the period before the COVID-19 pandemic. Delirium-free days were compared between the two groups (9).
Continuous variables and counts are described using mean ± sd or median (interquartile range [IQR]); categorical variables are reported as percentages.
Analyses were performed using chi-square test, multivariable logistic regression, negative binomial regression, and mediation analysis. For mediation analysis, we tested whether COVID-19 patients had a higher percentage of coma during the first 10 days of mechanical ventilation and whether a higher percentage of coma was associated with in-hospital mortality, indicating a possible effect mediation. Conditional on both associations being significant, we used formal mediation analysis to estimate odds ratios of the indirect (mediated) effect of high percentage of comatose state and the total (unmediated) effect of COVID-19 on in-hospital mortality (19,20). A Cox proportional hazards regression analysis was used to compare the effects of coma on mortality of patients with sedation-related coma versus neurologic injury-related coma. We considered a two-tailed p value of below 0.05 as statistically significant. All analyses were performed using Stata, Version 15.1 (StataCorp LP, College Station, TX).
Based on previously published mortality in mechanically ventilated COVID-19 patients (21) and assuming a two-tailed alpha of 0.01 and a power greater than 95% to detect a significant effect, a total sample size of 190 patients was needed.
Study Cohort and Patients’ Cognitive Status Over Time
Among 2,301 patients with a diagnosis of COVID-19 between March 1, and May 12, 2020, 270 patients (11.7 %) were admitted to the ICU. Among those, 141 patients (61.3%) were intubated and mechanically ventilated and therefore included in this study. One-hundred fourteen mechanically ventilated COVID-19 patients (80.9%) were matched with 228 non–COVID-19 ARDS patients (eFig. 1, https://links.lww.com/CCM/G322). Table 1 shows baseline characteristics at the time of initiation of mechanical ventilation and standardized difference after matching. Figure 1 shows the cumulative frequency of death or extubation in each study group over 28 days, as well as the cognitive status during mechanical ventilation for patients in each study group.
TABLE 1. -
Baseline Characteristics at the Time of Starting Mechanical Ventilation by Coronavirus Disease Diagnosis; Propensity-Matched Cohort
||Non-COVID (n = 228)
||COVID (n = 114)
|Age (yr), mean ± sd
||62.3 ± 17.2
||60.6 ± 15.9
|Female sex, n (%)
|Body mass index (kg/m2), median (interquartile range)
|Acute Physiology and Chronic Health Evaluation II score, median (interquartile range)
|Charlson Comorbidity Index, median (interquartile range)
|Respiratory system compliance (mL/cm H2O), mean ± sd
||40.7 ± 18.6
||39.9 ± 21.8
2 ratio, median (interquartile range)
2 (mm Hg), mean ± sd
||48.6 ± 16.3
||47.8 ± 13.2
|Alveolar–arterial gradient, median (interquartile range)
|Creatinine (mg/dL), mean ± sd
||1.6 ± 1.3
||1.5 ± 1.3
|Total bilirubin (mg/dL), mean ± sd
||1.6 ± 1.4
||1.7 ± 1.5
|International normalized ratio, mean ± sd
||1.4 ± 3.3
||0.7 ± 1.0
|Vasopressors (µg of norepinephrine equivalents), mean ± sd
||0.052 ± 0.177
||0.043 ± 0.133
|pH, median (interquartile range)
|Minute ventilation (L/min), median (interquartile range)
|Glasgow Coma Scale, median (interquartile range)
||8.5 (8, 15)
|Renal impairment, n (%)
|Severe liver injury, n (%)
|ARDS severity, n (%)
|Cause of ARDS, n (%)
| Documented viral infection
| Documented bacterial infection
ARDS = acute respiratory distress syndrome, COVID = coronavirus disease.
Renal impairment defined as creatinine level ≥ 2.5 mg/dL. Severe liver injury defined as total bilirubin ≥ 5 mg/dL and INR ≥ 1.5. Pulmonary cause of ARDS as opposed to nonpulmonary causes.
Primary and Secondary Outcomes
COVID-19 patients experienced a higher percentage of coma during the first 10 days of mechanical ventilation (66.0% ± 31.3%) compared with non–COVID-19 patients (36.0% ± 36.9%). This result was confirmed in an adjusted analysis (adjusted coefficient [aCoef], 29.34; 95% CI, 21.45–37.24; p < 0.001). Mediation analysis revealed that COVID-19 patients experienced a significantly higher percentage of coma, which in turn was significantly associated with in-hospital mortality (adjusted odds ratio [aOR], 5.84; 95% CI, 3.56–9.58; p < 0.001). 58.6% of the effect of COVID-19 on in-hospital mortality was mediated through the indirect effect of coma (aOR, 1.57; 95% CI, 1.22–2.00; p < 0.001). The direct effect of COVID-19 diagnosis on mortality was insignificant (aOR, 1.37; 95% CI, 0.87–2.15; p = 0.17) (eFig. 2, https://links.lww.com/CCM/G322).
Hypnotic Agent Dose and Use of Sedative Medications
The hypnotic agent dose was higher in COVID-19 patients (51.3% ± 20.6% vs 17.1% ± 12.5%) (p < 0.001). The hypnotic agent dose was associated with the percentage of coma (aCoef, 0.61; 95% CI, 0.45–0.78; p < 0.001). Mediation analysis demonstrated that 52.0% of the effect of COVID-19 diagnosis on coma was mediated through the indirect effect of hypnotic agent dose (aOR, 3.08; 95% CI, 1.62–5.83; p = 0.001) (eFig. 3, https://links.lww.com/CCM/G322).
During mechanical ventilation, opioids were the most commonly used medications. There was no significant difference in the numbers of patients receiving opioids between COVID-19 and non–COVID-19 patients (112 [98.2%] vs 214 [93.9%]; p = 0.07). However, the duration of treatment was significantly longer in COVID-19 patients (10.1 ± 5.7 vs 5.6 ± 4.7 d; p < 0.001). COVID-19 patients received a higher proportion of sedative medications and higher doses for a longer time (Table 2) (eTable 3, https://links.lww.com/CCM/G322). The SBI was significantly higher during the first 10 days of mechanical ventilation in COVID-19 patients (p < 0.001) along with a higher percentage of patients who were comatose (Fig. 2).
TABLE 2. -
Administration of Sedatives, Analgesics, and Neuromuscular Blocking Agents During Mechanical Ventilation
||Non-COVID (n = 228)
||COVID (n = 114)
|No. of Prescriptions, n (%)
||Duration ofPrescription (d), Mean ± sd
||No. of Prescriptions, n (%)
||Duration of Prescription (d), Mean ± sd
|Opioid (oral morphine equivalents)
||5.6 ± 4.7
||25.1 (12.5–53.1) mg/d
||10.1 ± 5.7
||16.5 (8.1–31.8) mg/d
||3.9 ± 2.8
||1,773 (932–3,176) mg/d
||7.4 ± 5.0
||3,606 (2,188–4,914) mg/d
||2.8 ± 2.7
||16.1 (3.0–44.8) mg/d
||6.3 ± 4.4
||83.3 (45.5–116.4) mg/d
||1.5 ± 1.1
||1 (0–2) mg/d
||1.5 ± 1.1
||1.8 (0.5–2.3) mg/d
||3.9 ± 3.0
||14.2 (9.8–22.3) mg/d
||3.8 ± 2.9
||841 (359–1,411) µg/d
||5.1 ± 3.5
||1,157 (806–1,568) µg/d
||1.5 ± 0.7
||147 (39–254) mg/d
||7.4 ± 4.5
||919 (610–1,570) mg/d
|Neuromuscular blocking agent
||2.6 ± 2.4
||4.8 ± 3.9
||138 (89–221) mg/d
||182 (112–240) mg/d
||425 (270–579) mg/d
||683 (477–845) mg/d
ap compared between number of treatments.
Neurologic Consultation and Brain Imaging
Brain imaging was performed in 36 patients (31.6%) with COVID-19 and 100 patients (43.9%) without COVID-19. Results from neuroimaging reports revealed that patients with and without COVID-19 were not significantly different in terms of pathologic brain lesions (p = 0.76). Seven COVID-19 patients (6.1%) suffered a stroke (3 ischemic and 4 hemorrhagic), and 16 non–COVID-19 patients (7.0%) had pathologic brain lesions (8 ischemic stroke, 4 hemorrhagic stroke, 4 severe cerebral edema). The proportional hazards ratio was not significantly different between sedation-related coma versus coma that was accompanied by an additional neurologic injury (adjusted hazard ratio, 1.34; 95% CI, 0.69–2.59; p = 0.38) (eFig. 4, https://links.lww.com/CCM/G322).
Sensitivity and Exploratory Analyses
The primary results were confirmed throughout all sensitivity analyses. In the complete, unselected cohort of all ARDS patients (n = 3,201) (eTable 1, https://links.lww.com/CCM/G322), COVID-19 patients experienced a higher percentage of coma (aCoef, 35.00; 95% CI, 29.25–40.70; p < 0.001), which in turn was significantly associated with in-hospital mortality (aOR, 3.57; 95% CI, 2.97–4.30; p < 0.001). The effect of COVID-19 on in-hospital mortality was mediated through the indirect effect of coma (p < 0.001). Details of sensitivity analyses are provided in the supplementary document, section 4 (https://links.lww.com/CCM/G322).
Effect Modification and Subgroup Analysis in Patients Who Received NMBAs and Prone Positioning
When considering the effect of adjunctive treatments on the use of sedative medications, an effect modification by prone positioning was observed (p for interaction = 0.04) but not with NMBA use (p for interaction = 0.12). However, a diagnosis of COVID-19 was associated with an increase of hypnotic agent dose in all subgroups of patients (eTable 5, https://links.lww.com/CCM/G322).
Trend in ARDS Treatment
When comparing the common adjunctive therapies used in the management of ARDS prior to and during the COVID-19 pandemic, we found that prone positioning and NMBA use increased during the COVID-19 period (March to May 2020) (48.2% vs 3.5% and 56.1% vs 23.2%, respectively; p < 0.001). Doses and number of sedative and analgesic medications also increased (Fig. 3) (eTable 3, https://links.lww.com/CCM/G322).
Within 28 days, COVID-19 patients had a significantly lower median number of days alive without delirium or coma (delirium-free days) compared with non–COVID-19 patients (median [IQR] = 11 [1–19] vs 21 d [5–25 d]; absolute incidence rate ratio, 0.64; 95% CI, 0.49–0.83; adjusted difference, –6.5 d; p = 0.001).
Patients with COVID-19 had a higher risk of in-hospital mortality and experienced a higher percentage of coma during mechanical ventilation compared with patients with ARDS from other etiologies—even after controlling for markers of comorbidities (including markers of heart, renal and liver failure) and ARDS severity (P/F ratio, A-a gradient, Paco2, pH, and minute ventilation). Coma was identified as a mediator of in-hospital mortality in patients with COVID-19.
COVID-19 is associated with neurologic disturbances and complications including impaired consciousness and stroke (22,23). In our COVID-19 cohort, clinicians were concerned about a possible nonpharmacologic mechanism of coma in approximately one third of patients to the extent that they requested formal neurologic consultation and brain imaging. Neurologic workup revealed a frequency of stroke confirmed by neuroimaging of 6.1%, which was not different from the 7.0% observed in non–COVID-19 patients.
In our study, patients with COVID-19–associated ARDS received substantially higher doses of hypnotics than patients with ARDS of other etiology, which explained the higher occurrence rate of coma based on our association analysis. Higher utilization of analgesics and hypnotics in mechanically ventilated patients with ARDS due to COVID-19 compared with other etiologies has been reported previously (24,25). The reasons for the higher requirements are multifactorial: First, based on early treatment suggestions for COVID-19 patients, clinicians opted for prone position therapy more often compared with patients with ARDS of other etiology (48.2 vs 3.5%; p < 0.001). NMBAs were used in most proned patients, which was accompanied by deep sedation targets according to a recommendation (26). NMBA infusions and deep sedation may have been maintained unnecessarily during the periods when the patients were returned to the supine position. We have previously shown that a long duration of deep sedation after termination of neuromuscular blockade is associated with increased mortality (27).
Second, more long-acting sedatives, such as benzodiazepines, were used in COVID-19 patients, which was likely related to national drug shortage reports. On April 10, 2020, propofol and dexmedetomidine were included in the U.S. Food and Drug Administration list of drug shortages (28). In response, our institute issued a document to recommend alternative sedative agents, including benzodiazepines, to be considered during the pandemic drug shortage period. With differences in pharmacokinetic properties such as longer context-sensitive half-life than propofol, benzodiazepines and their metabolites can persist long after infusions are stopped and therefore may cause oversedation (29).
Third, previous publications suggested that patients with COVID-19 can present with different phenotypes, one of which is high ventilatory drive (high dead space and shunt) despite good compliance (25,30,31). It is possible that clinicians used higher doses of hypnotic agents to protect their patients with COVID-19 from self-inflicted lung injury. This hypothesis is supported by our finding that patients with COVID-19 received higher hypnotic agent doses and paralytics more frequently, resulting in lower minute ventilation compared with patients with ARDS of other etiology. Finally, in order to mitigate the risk of viral spreading across healthcare providers and patients, strict infection control protocols, including isolation of patients, personal protective equipment, and respiratory protection, were recommended (32). Deep and prolonged sedation may have been unintended consequences. Maintaining deep sedation may also be anxiety driven; ICU staff may have been focused on the prevention of patients’ self-extubation more for patients who tested positive for COVID-19.
Mediation analysis demonstrated a strong relationship between coma and increased in-hospital mortality. Expectedly, we found that a longer period of sedation was associated with a higher occurrence rate of delirium, which could have contributed to the effects of sedation on mortality. Our findings are supported by previous studies demonstrating that deep sedation or coma lead to immobilization, delirium, delays in extubation, and delays in ICU discharge (33–35). Such delays increase the risk of nosocomial infections and other complications that can contribute to mortality (36). Current sedation guidelines and sedation bundles should be considered and applied when possible (37,38).
Our study is the largest cohort study investigating sedative drug usage and cognitive function in mechanically ventilated COVID-19 patients. We also have a highly detailed and granular database of non-COVID ARDS patients, with which we were able to compare characteristics, clinical practice, and outcomes.
However, several limitations arise from the retrospective design of our study. First, although we matched patients based on most relevant factors such as heart, liver, and renal failure at admission, as well as severity of ARDS, we cannot exclude the relevance of unmeasured confounders. Second, to the best of our knowledge, there is no robust way to combine the effects of different drug compounds. We adapted the drug burden index as a SBI to compare the effect of summative analgesic and sedative doses in critically ill patients (39–41). We cannot identify the cause of high sedative medication needs, even though we controlled for all available variables that affect respiratory drive (P/F ratio, A-a gradient, Paco2, pH, and minute ventilation). Finally, it is possible that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may have had direct effects on the brain which could not be identified by CT imaging. Leukoencephalopathy is a rare CNS complication in SARS-CoV-2 which cannot be diagnosed with a CT (42), and it is possible that patients who were identified as not having a structural neurologic disease had an unidentified leukoencephalopathy.
Patients with COVID-19 received higher doses of hypnotics during mechanical ventilation, which was associated with prolonged coma and increased in-hospital mortality. Clinical practices focusing on safely minimizing analgesic and sedative doses and duration of administration should be applied.
We are grateful to Dr. Timothy T. Houle for providing us with an independent statistical advice during the per-review process.
1. Frontera J, Mainali S, Fink EL, et al.: Global consortium study of neurological dysfunction in COVID-19 (GCS-NeuroCOVID): Study design and rationale. Neurocrit Care 2020; 33:25–34
2. Mao L, Jin H, Wang M, et al.: Neurologic manifestations of hospitalized patients with coronavirus disease 2019 in Wuhan, China. JAMA Neurol 2020; 77:683–690
3. Asadi-Pooya AA, Simani L: Central nervous system manifestations of COVID-19: A systematic review. J Neurol Sci 2020; 413:116832
4. Li Y, Li M, Wang M, et al.: Acute cerebrovascular disease following COVID-19: A single center, retrospective, observational study. Stroke Vasc Neurol 2020; 5:1–6
5. Xiong W, Mu J, Guo J, et al.: New onset neurologic events in people with COVID-19 infection in three regions in China. Neurology 2020; 95:e1479–e1487
6. Slooter AJC, Otte WM, Devlin JW, et al.: Updated nomenclature of delirium and acute encephalopathy: Statement of ten Societies. Intensive Care Med 2020; 46:1020–1022
7. Hanidziar D, Bittner E: Sedation of mechanically ventilated COVID-19 patients. Anesth Analg 2020; 131:e40–e41
8. World Health Organization: Clinical Management of Severe Acute Respiratory Infection When Novel Coronavirus (nCoV) Infection is Suspected, Interim Guidance2020
9. Page VJ, Ely EW, Gates S, et al.: Effect of intravenous haloperidol on the duration of delirium and coma in critically ill patients (Hope-ICU): A randomised, double-blind, placebo-controlled trial. Lancet Respir Med 2013; 1:515–523
10. Wilson WC, Smedira NG, Fink C, et al.: Ordering and administration of sedatives and analgesics during the withholding and withdrawal of life support from critically ill patients. JAMA 1992; 267:949–953
11. Aragón RE, Proaño A, Mongilardi N, et al.: Sedation practices and clinical outcomes in mechanically ventilated patients in a prospective multicenter cohort. Crit Care 2019; 23:130
12. Long DR, Lihn AL, Friedrich S, et al.: Association between intraoperative opioid administration and 30-day readmission: A pre-specified analysis of registry data from a healthcare network in New England. Br J Anaesth 2018; 120:1090–1102
13. Austin PC: An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res 2011; 46:399–424
14. Gayat E, Pirracchio R, Resche-Rigon M, et al.: Propensity scores in intensive care and anaesthesiology literature: A systematic review. Intensive Care Med 2010; 36:1993–2003
15. Wu T, Li J, Shao L, et al.: Development of diagnostic criteria and a prognostic score for hepatitis B virus-related acute-on-chronic liver failure. Gut 2018; 67:1–11
16. Gong J, Ou J, Qiu X, et al.: A tool for early prediction of severe coronavirus disease 2019 (COVID-19): A multicenter study using the risk nomogram in Wuhan and Guangdong, China. Clin Infect Dis 2020; 71:833–840
17. Wu C, Chen X, Cai Y, et al.: Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med 2020; 180:934–943
18. Austin PC, Grootendorst P, Anderson GM: A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: A Monte Carlo study. Stat Med 2007; 26:734–753
19. Shrout PE, Bolger N: Mediation in experimental and nonexperimental studies: New procedures and recommendations. Psychol Methods 2002; 7:422–445
20. Imai K, Keele L, Tingley D, et al.: Unpacking the black box of causality: Learning about causal mechanisms from experimental and observational studies. Am Polit Sci Rev 2011; 105:765–789
21. Zhou F, Yu T, Du R, et al.: Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet 2020; 395:1054–1062
22. Hess DC, Eldahshan W, Rutkowski E: COVID-19-related stroke. Transl Stroke Res 2020; 11:322–325
23. Rogers JP, Chesney E, Oliver D, et al.: Psychiatric and neuropsychiatric presentations associated with severe coronavirus infections: A systematic review and meta-analysis with comparison to the COVID-19 pandemic. Lancet Psychiatry 2020; 7:611–627
24. Hanidziar D, Bittner EA: In response: The use of analgesia and sedation in mechanically ventilated patients with COVID-19 ARDS. Anesth Analg 2020; 131:e200–e202
25. Christopher K, Sandra Z, Shannon N, et al.: The use of analgesia and sedation in mechanically ventilated patients with COVID-19 ARDS. Anesth Analg 2020; 131:e198–e200
26. Murray MJ, DeBlock H, Erstad B, et al.: Clinical practice guidelines for sustained neuromuscular blockade in the adult critically ill patient. Crit Care Med 2016; 44:2079–2103
27. Wongtangman K, Grabitz SD, Hammer M, et al. Optimal sedation in patients who receive neuromuscular blocking agent infusions for treatment of acute respiratory distress syndrome - a retrospective cohort study from a Health Care Network on New England. Crit Care Med 2021 Mar 12. [online ahead of print]
28. U.S. Food & Drug AdministrationFDA Drug Shortages. Available at: https://www.accessdata.fda.gov/scripts/drugshortages/default.cfm
. Accessed March 22, 2021.
29. Hughes MA, Glass PS, Jacobs JR: Context-sensitive half-time in multicompartment pharmacokinetic models for intravenous anesthetic drugs. Anesthesiology 1992; 76:334–341
30. Marini JJ, Gattinoni L: Management of COVID-19 respiratory distress. JAMA 2020; 323:2329–2330
31. Esnault P, Cardinale M, Hraiech S, et al.: High respiratory drive and excessive respiratory efforts predict relapse of respiratory failure in critically ill patients with COVID-19. Am J Respir Crit Care Med 2020; 202:1173–1178
32. COVID-19 - Control and Prevention: Healthcare Workers and Employers | Occupational Safety and Health Administration.Available at: https://www.osha.gov/SLTC/covid-19/healthcare-workers.html
33. Girard TD, Kress JP, Fuchs BD, et al.: Efficacy and safety of a paired sedation and ventilator weaning protocol for mechanically ventilated patients in intensive care (awakening and breathing controlled trial): A randomised controlled trial. Lancet 2008; 371:126–134
34. Shehabi Y, Chan L, Kadiman S, et al.; Sedation Practice in Intensive Care Evaluation (SPICE) Study Group investigators: Sedation depth and long-term mortality in mechanically ventilated critically ill adults: A prospective longitudinal multicentre cohort study. Intensive Care Med 2013; 39:910–918
35. Schaller SJ, Anstey M, Blobner M, et al.; International Early SOMS-guided Mobilization Research Initiative: Early, goal-directed mobilisation in the surgical intensive care unit: A randomised controlled trial. Lancet 2016; 388:1377–1388
36. Ferrell BA, Girard TD: Sedative choice: A critical decision. Am J Respir Crit Care Med 2014; 189:1295–1297
37. Devlin JW, Skrobik Y, Gélinas C, et al.: Clinical practice guidelines for the prevention and management of pain, agitation/sedation, delirium, immobility, and sleep disruption in adult patients in the ICU. Crit Care Med 2018; 46:e825–e873
38. Chanques G, Constantin JM, Devlin JW, et al.: Analgesia and sedation in patients with ARDS. Intensive Care Med 2020; 46:2342–2356
39. Hilmer SN: Calculating and using the drug burden index score in research and practice. Expert Rev Clin Pharmacol 2018; 11:1053–1055
40. O’Connell J, Burke É, Mulryan N, et al.: Drug burden index to define the burden of medicines in older adults with intellectual disabilities: An observational cross-sectional study. Br J Clin Pharmacol 2018; 84:553–567
41. Barr J, Fraser GL, Puntillo K, et al.; American College of Critical Care Medicine: Clinical practice guidelines for the management of pain, agitation, and delirium in adult patients in the intensive care unit. Crit Care Med 2013; 41:263–306
42. Radmanesh A, Derman A, Lui YW, et al.: COVID-19-associated diffuse leukoencephalopathy and microhemorrhages. Radiology 2020; 297:E223–E227