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. 2022 Dec 15;17(12):e0277503. doi: 10.1371/journal.pone.0277503

Neuromuscular blockade in mechanically ventilated pneumonia patients with moderate to severe hypoxemia: A multicenter retrospective study

Moon Seong Baek 1,#, Jong Ho Kim 2,3,#, Yaeji Lim 4, Young Suk Kwon 2,3,*
Editor: Steven Eric Wolf5
PMCID: PMC9754162  PMID: 36520923

Abstract

Background/Purpose

The benefit of neuromuscular blockades (NMBs) in critically ill patients receiving mechanical ventilation remains uncertain. Therefore, we aimed to investigate whether NMB use is associated with improved survival of mechanically ventilated pneumonia patients with moderate to severe hypoxemia.

Methods

This retrospective multicenter study was conducted at five university-affiliated hospitals. Data of pneumonia patients aged 18 years and older who received mechanical ventilation between January 1, 2011, and December 31, 2020, were analyzed.

Results

In a total of 1,130 patients, the mean patient age was 73.1 years (SD±12.6), and the overall mortality rate at 30 d was 29.5% (n = 333). NMB users had a higher 30 d mortality rate than NMB nonusers (33.9% vs. 26.8%, P = 0.014). After PS matching, the 30 d mortality rate was not significantly different between NMB users and nonusers (33.4% vs. 27.8%, p = 0.089). However, 90 d mortality rate was significantly increased in NMB users (39.7% vs. 31.9%, p = 0.021). Univariable Cox proportional hazard regression analyses showed that NMB use ≥ 3 d was significant risk factor for the 90 d mortality than those with < 3 d use (90 d mortality HR 1.39 [95% CI: 1.01–1.91], P = 0.045).

Conclusions

NMB use was not associated with lower 30 d mortality among mechanically ventilated pneumonia patients with moderate to severe hypoxemia. Rather, NMB users had higher 90 d mortality, furthermore, and NMB use ≥ 3 d was associated with a higher risk of long-term mortality compared to NMB use < 3 d. Therefore, care should be taken to avoid extended use of NMB in critically ill pneumonia patients during mechanical ventilation.

Introduction

During mechanical ventilation, neuromuscular blockades (NMBs) have been used in various critical care settings such as acute respiratory distress syndrome (ARDS) [1–5], severe sepsis [6,7], bronchospasm with profound hypoxemia [8], and therapeutic hypothermia [9,10]. The expected advantages of NMBs are a reduction of oxygen consumption, improvement of oxygenation, and optimization of mechanical ventilation through reducing patient–ventilator asynchrony [11]. However, it has been reported that the use of NMBs does not affect oxygen consumption in adequately sedated patients [12,13]. In addition, the use of NMBs may be associated with increased atelectasis, prolonged paralysis following NMB, and intensive care unit (ICU)-acquired weakness [11,14]. Therefore, NMBs should be used with caution in critically ill patients receiving mechanical ventilation.

It is well established that by reducing the risk of ventilator-induced lung injury, lung-protective mechanical ventilation can improve survival among patients with ARDS [15]. To facilitate lung-protective mechanical ventilation, a short course of NMB has been recommended in the early phase of moderate-to-severe ARDS [5,16,17]. In the ARDS et Curarisation Systematique (ACURASYS) trial, the early administration of a 48 h infusion of NMB in ARDS improved the adjusted 90 d survival for patients with a PaO2/FiO2 ratio < 150. Furthermore, a systematic review and meta-analysis using three randomized trials revealed that a short-term course of NMB was associated with reduced mortality and did not increase ICU-acquired weakness for patients with ARDS [4]. However, a recently reported trial, the Reevaluation of Systemic Early Neuromuscular Blockade (ROSE) trial, showed that there was no significant difference in 90 d mortality between patients who received an early cisatracurium infusion and those who were treated with a lighter sedation strategy [18]. With this finding contradicting the supposed efficacy of NMBs in ARDS, the benefit of NMBs remains uncertain in critically ill patients receiving mechanical ventilation. Therefore, we aimed to investigate whether NMB use is associated with improved survival among mechanically ventilated pneumonia patients with moderate to severe hypoxemia.

Materials and methods

Study design and patients

This retrospective multicenter study was conducted at five university-affiliated hospitals of Hallym University Medical Center in the Republic of Korea. The overall bed capacity and annual inpatients were approximately 3,000 beds (231 ICU beds) and 100,000 patients. We collected the electronic medical records of patients aged 18 years and older who received mechanical ventilation in the ICU between January 1, 2011, and December 31, 2020. During the study period, severe COVID-19 patients did not hospitalize at our ICUs. Among the mechanically ventilated patients identified, we enrolled patients with pneumonia. According to the clinical practice guideline of ARDS [19], NMBs have been used in moderate to severe hypoxemia to facilitate mechanical ventilation. Patients were excluded if they received surgery, underwent extracorporeal membrane oxygenation (ECMO) therapy, or had a duration of mechanical ventilation < 3 d. We further excluded patients with PaO2 (partial pressure of oxygen)/FiO2 (fraction of inspired oxygen) ≥ 150 mmHg based on the initial arterial blood gas analysis. Patients received a bolus injection of NMB were excluded.

This study was approved by the Institutional Review Board of Chuncheon Sacred Heart Hospital (2021-03-011). The requirement for informed consent was waived owing to the retrospective nature of the analysis.

Data collection and definitions

We obtained the following data on the day of initiation of mechanical ventilation through clinical big data analytic solution Smart CDW, which can analyze the electronic medical record text and integrated fixed data at five hospitals: patient age, sex, body mass index, diagnosis, time from hospitalization to ICU admission, time from hospitalization to mechanical ventilation initiation, Acute Physiology and Chronic Health Evaluation (APACHE) II score, modified early warning score, CURB-65, transfer from a skilled nursing facility, Charlson Comorbidity Index (CCI) and its variables, continuous renal replacement therapy, transfusion, vasopressors or inotropes, corticosteroids, opioids (morphine, fentanyl, or remifentanil), sedatives (propofol, midazolam, or dexmedetomidine), type and infused duration of NMBs (cisatracurium and vecuronium), and laboratory results with arterial blood gases.

In the assigned diagnoses for each patient, we retrieved pneumonia using the KCD-7 codes (Korean version of the International Classification of Diseases-10, ICD-10). Comorbidities were categorized by CCI variables according to the ICD-10 codes. The CURB-65 score is comprised of five separate elements, including confusion, urea (> 19 mg/dL), respiratory rate (≥ 30/min), blood pressure (systolic blood pressure < 90 mmHg or diastolic blood pressure ≤ 60 mmHg diastolic), and age (≥ 65 years) [20]. ARDS was identified as ICD-10 code of J80. To avoid inclusion of NMB users with bolus injection for endotracheal intubation purpose, we defined NMB users as patients who received continuous infusion of NMBs. The primary outcome was 30 d mortality from the initiation of mechanical ventilation. The secondary outcomes were 90 d mortality, length of stay, ICU stay, duration of mechanical ventilation, and the use of quetiapine and amiodarone.

Statistical analysis

To construct a control group (NMB nonusers), propensity score (PS) matching was performed by the nearest-neighbor method with the following variables: age, sex, body mass index, time from hospitalization to ICU admission, time from hospitalization to mechanical ventilation initiation, APACHE II score, modified early warning score, CURB-65, transferred from skilled nursing facility, CCI, aspiration pneumonia, diabetes, congestive heart failure, myocardial infarction, chronic pulmonary disease, liver disease, moderate to severe chronic kidney disease, any malignancy, rheumatic disease, dementia, cerebrovascular disease, continuous renal replacement therapy, transfusion, vasopressors and inotropes, corticosteroids, opioids, sedatives, and PaO2/FiO2. In the matching process, 37 patients in the study groups were excluded due to null values of the matching variables.

Differences in continuous and categorical baseline characteristics between the groups were analyzed with Student’s t-test and the chi-square test, respectively. Moreover, differences in baseline characteristics in the 1:1 matched group were analyzed with the paired t-test and McNemar’s test. Univariable and multivariable stratified Cox proportional hazard regression models were used to calculate the hazard ratio (HR) and 95% confidence interval (CI) for the risk of mortality. Multivariate regression analysis was used to adjust the effect of imbalance in the baseline. Age, modified early warning score, Charlson comorbidity index, and positive end expiratory pressure (PEEP) were selected as the adjust variables, because there were significant differences between two groups even after matching. Statistical analyses were performed using R 4.0.4 (The R Foundation for Statistical Computing).

Results

Patient characteristics

During the study period, 1,146,506 patients admitted to our hospitals, and 112,322 patients admitted to the ICU. Mechanically ventilated patients were 29,554, and patients with pneumonia aged over 18 years were 3,357 (Fig 1). We excluded 2,227 patients who received surgery (n = 404), had a mechanical ventilation duration < 3 d (n = 502), received ECMO (n = 58), had PaO2/FiO2 ≥ 150 mmHg (n = 1,194), and received NMB as a bolus injection (n = 69). In a total of 1,130 patients, the mean patient age was 73.1 years (SD±12.6), and 67.2% were male. NMB users were 422 (37.3%), and the mean duration of NMB use was 4.6 d (SD±5.8). A comparison of the patients’ baseline characteristics is presented in Table 1. Age, CCI, and PaO2/FiO2 ratio were higher in NMB nonusers than NMB users. On the other hand, modified early warning score, PEEP and the use corticosteroids, opioids, and sedatives were higher in NMB users. There were no significant differences in the APACHE II score and continuous renal replacement therapy.

Fig 1. Patient flowchart.

Fig 1

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NMB, neuromuscular blockade; MV, mechanical ventilation; ECMO, extracorporeal membrane oxygenation; PaO2, partial pressure of oxygen; and FiO2, fraction of inspired oxygen.

Table 1. Comparison of baseline characteristics of patients.

Before matching After matching
Variables NMB nonuser (n = 708) NMB user (n = 422) P value NMB nonuser (n = 395) NMB user (n = 395) P value Standardized mean difference
Age (years) 74.3±12.4 71.1±12.8 <0.001 72.7±12.9 71.0±12.9 0.058 0.130
Male sex (%) 465 (65.7) 294 (69.7) 0.188 274 (69.4) 277 (70.1) 0.875 0.017
Body mass index (kg/m2) 21.5±4.4 22.0±4.3 0.054 21.9±4.7 22.0±4.3 0.665 0.030
Time from hospitalization to ICU admission (d) 1.8±5.8 1.8±4.6 0.986 1.5±4.3 1.6±3.9 0.592 0.037
Time from hospitalization to MV initiation (d) 4.5±16.5 3.8±6.5 0.316 3.5±7.2 3.5±5.8 0.974 0.002
APACHE II score 24.9±5.7 25.4±5.9 0.173 25.3±5.8 25.4±5.9 0.716 0.025
Modified early warning score 5.5±1.7 5.9±1.8 <0.001 5.7±1.7 5.9±1.8 0.039 0.144
CURB-65 2.8±0.9 2.7±1.0 0.147 2.8±0.9 2.7±1.0 0.509 0.047
Transferred from skilled nursing facility (%) 192 (27.1) 68 (16.1) <0.001 79 (20.0) 63 (15.9) 0.160 0.106
Charlson Comorbidity Index 4.8±2.3 4.4±2.2 0.001 4.6±2.2 4.3±2.2 0.081 0.117
Aspiration pneumonia (%) 145 (20.5) 53 (12.6) 0.001 57 (14.4) 47 (11.9) 0.337 0.075
Comorbiditiesa (%)
    Diabetes 150 (21.2) 83 (19.7) 0.593 81 (20.5) 73 (18.5) 0.837 0.051
    Congestive heart failure 113 (16.0) 56 (13.3) 0.254 61 (15.4) 52 (13.2) 0.402 0.065
    Myocardial infarction 34 (4.8) 22 (5.2) 0.868 23 (5.8) 21 (5.3) 0.877 0.022
    Chronic pulmonary disease 151 (21.3) 94 (22.3) 0.765 87 (22.0) 88 (22.3) 1.000 0.006
    Liver disease 48 (6.8) 35 (8.3) 0.409 34 (8.6) 35 (8.9) 1.000 0.009
    Moderate to severe CKD 88 (12.4) 35 (8.3) 0.039 36(9.1) 31(7.8) 0.603 0.045
    Any malignancy 66 (9.3) 52 (12.3) 0.135 43 (10.9) 47 (11.9) 0.731 0.032
    Rheumatic disease 9 (1.3) 19 (4.5) 0.001 9 (2.3) 17 (4.3) 0.153 0.114
    Dementia 92 (13.0) 39 (9.2) 0.070 40 (10.1) 35 (8.9) 0.620 0.043
    Cerebrovascular disease 194 (27.4) 77 (18.2) 0.001 97 (24.6) 70 (17.7) 0.018 0.168
Continuous renal replacement therapy (%) 59 (8.3) 36 (8.5) 0.996 33 (8.4) 36 (9.1) 0.798 0.027
Transfusion (%) 110 (15.5) 80 (19.0) 0.160 60 (15.2) 72 (18.2) 0.271 0.082
Vasopressors and inotropes (%) 304 (42.9) 206 (48.8) 0.063 190 (48.1) 197 (49.9) 0.664 0.035
Corticosteroids (%) 82 (11.6) 84 (19.9) <0.001 62 (15.7) 78 (19.7) 0.118 0.106
Opioids (%) 516 (72.9) 357 (84.6) <0.001 320 (81.0) 335 (84.8) 0.164 0.101
Sedatives (%) 443 (62.6) 380 (90.0) <0.001 348 (88.1) 355 (89.9) 0.337 0.057
PaO2/FiO2 (mmHg) 91.6±30.7 87.6±30.8 0.036 90.9±30.9 87.5±30.8 0.125 0.110
PEEP 7.1±2.6 8.2±3.1 <0.001 7.5±2.8 8.2±3.1 0.001 0.239
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Values are presented as mean±SD or n (%).

a The CURB-65 score is comprised of five separate elements including confusion, uremia, respiratory rate, blood pressure, and age ≥ 65 years.

b Comorbidities were categorized by the Charlson Comorbidity Index.

NMB, neuromuscular blockade; ICU, intensive care unit; MV, mechanical ventilation; APACHE, Acute Physiology and Chronic Health Evaluation; CKD, chronic kidney disease; PaO2, arterial partial pressure of oxygen; FiO2, fraction of inspired oxygen; and PEEP, positive end expiratory pressure.

Outcomes

Overall mortalities at 30 d and 90 d were 29.5% (n = 333) and 35.1% (n = 397), respectively.

NMB users had significantly higher 30 d and 90 d mortalities than NMB nonusers (30 d mortality 33.9% vs. 26.8%, P = 0.014; 90 d mortality 40.0% vs. 32.2%, P = 0.009) (Table 2). ICU stay and duration of mechanical ventilation were significantly longer in the NMB users than the NMB nonusers. The incidence of tracheostomy was significantly higher in the NMB users (tracheostomy 28.7% vs. 11.9%, p<0.001). After PS matching, 30 d mortality was not significantly different between NMB users and nonusers (33.4% vs. 27.8%, p = 0.089). However, 90 d mortality was significantly higher in the NMB users (39.7% vs. 31.9%, p = 0.021).

Table 2. Clinical outcomes.

Before matching After matching
Variables NMB nonuser (n = 708) NMB user (n = 422) P value NMB nonuser (n = 395) NMB user (n = 395) P value
Mortality at 30 d (%) 190 (26.8) 143 (33.9) 0.014 110 (27.8) 132 (33.4) 0.089
Mortality at 90 d (%) 228 (32.2) 169 (40.0) 0.009 126 (31.9) 157 (39.7) 0.021
Length of stay (d) 31.1±34.9 32.5±28.0 0.440 31.7±34.9 32.8±28.5 0.621
Length of ICU stay (d) 19.3±20.8 23.4±22.5 0.002 19.9±23.0 23.6±23.0 0.020
Duration of MV (d) 13.4±15.7 18.6±19.6 <0.001 14.0±17.4 18.8±20.1 <0.001
Tracheostomy (%) 84 (11.9) 121 (28.7) <0.001 52 (13.2) 112 (28.4) <0.001
Chest tube insertion (%) 43 (6.1) 28 (6.6) 0.803 29 (7.3) 26 (6.6) 0.775
Use of quetiapine (%) 150 (21.2) 108 (25.6) 0.102 91 (23.0) 103 (26.1) 0.346
Use of amiodarone (%) 81 (11.4) 63 (14.9) 0.108 48 (12.2) 60 (15.2) 0.271
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Values are presented as mean±SD or n (%).

NMB, neuromuscular blockade; ICU, intensive care unit; MV, mechanical ventilation.

In the Kaplan–Meier survival analyses, there was no significant difference in 30 d mortality (p = 0.152), however, 90 d mortality was significantly higher in the NMB users (p = 0.047) (Fig 2). In the multivariate Cox regression analysis, NMB use was not independently associated with a higher risk of mortality: HRs for 30 d and 90 d mortalities according to NMB use were 1.06 ([95% CI: 0.82–1.37], P = 0.659) and 1.14 ([95% CI: 0.90–1.44], P = 0.294), respectively (Table 3).

Fig 2.

Fig 2

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Kaplan–Meier survival analyses (A) 30 d mortality according to NMB use. (B) 90 d mortality according to NMB use. NMB, neuromuscular blockade.

Table 3. Univariate and multivariate Cox regression analyses for 30 d and 90 d mortalities.

Univariate model Multivariate model
30 d mortality No. of patients No. of events HR (95% CI) P value HR (95% CI) P value
NMB nonusers 395 110 1 (reference) 1 (reference)
NMB users 395 132 1.20 (0.93–1.55) 0.152 1.06 (0.82–1.37) 0.659
NMB < 3 d 183 51 1 (reference) 1 (reference)
NMB ≥ 3 d 212 81 1.41 (0.99–2.00) 0.055 1.30 (0.91–1.85) 0.147
90 d mortality No. of patients No. of events HR (95% CI) P value HR (95% CI) P value
NMB nonusers 395 126 1 (reference) 1 (reference)
NMB users 395 157 1.27 (1.00–1.60) 0.047 1.14 (0.90–1.44) 0.294
NMB < 3 d 183 62 1 (reference) 1 (reference)
NMB ≥ 3 d 212 95 1.39 (1.01–1.91) 0.045 1.31 (0.95–1.8) 0.105
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The multivariable analysis included age, sex, body mass index, time from hospitalization to ICU admission, time from hospitalization to MV initiation, APACHE II score, modified early warning score, CURB-65, transferred from skilled nursing facility, Charlson Comorbidity Index, aspiration pneumonia, diabetes, congestive heart failure, myocardial infarction, chronic pulmonary disease, liver disease, moderate to severe CKD, any malignancy, rheumatic disease, dementia, cerebrovascular disease, continuous renal replacement therapy, transfusion, vasopressors and inotropes, corticosteroids, opioids, sedatives, and PaO2/FiO2 as the covariates.

NMB, neuromuscular blockade; HR, hazard ratio; CI, confidence interval.

Subgroup analysis

In NMB users, there was no significant difference in 30 d mortality (p = 0.055), however, 90 d mortality was significantly higher in the NMB users (p = 0.045) (Fig 3). Multivariable Cox proportional hazard regression analyses showed that NMB use ≥ 3 d was not a predictor of mortality: HRs for 30 d and 90 d mortalities according to NMB use were 1.30 ([95% CI: 0.91–1.85], P = 0.147) and 1.31 ([95% CI: 0.95–1.80], P = 0.105), respectively (Table 3).

Fig 3.

Fig 3

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Kaplan–Meier survival analyses (A) 30 d mortality according to the duration of NMB use. (B) 90 d mortality according to the duration of NMB use. NMB, neuromuscular blockade.

Discussion

This multicenter study revealed that NMB use was not associated with lower 30 d mortality in mechanically ventilated pneumonia patients with moderate to severe hypoxemia. However, 90 d mortality was significantly increased in NMB users. NMB users had a longer duration of mechanical ventilation and/or ICU stay, and underwent tracheostomy more frequently than NMB nonusers. Furthermore, NMB use ≥ 3 d was associated with higher 90-d mortality rate compared to NMB use < 3 d.

Based on the results of the ROSE trial and clinical studies on sedation [18,21–23], a recent practice guideline does not recommend the routine use of NMBs, even in moderate or severe ARDS [24]. This change of strategy in patients with ARDS can cause confusion for physicians regarding the use of NMBs in patients with pneumonia, which is the major cause of acute respiratory failure in the ICU [25]. In this regard, the results of our cohort provide valuable information that the use of NMBs during mechanical ventilation did not have a survival benefit in patients with severe hypoxemic pneumonia. NMBs tended to be administered to more critically ill patients because NMBs are often used in a setting where a lighter sedation strategy does not make the mechanical ventilation tolerable. We matched the clinical variables that can influence the outcomes between NMB users and nonusers as much as possible. Even after PS matching, 30 d mortality rate was not significantly different between NMB users and nonusers. Rather, 90 d mortality rate was significantly higher in NMB users. Therefore, NMBs during mechanical ventilation should be used cautiously in hypoxemic pneumonia patients.

In a recently reported meta-analysis with five randomized controlled trials, NMBs did not reduce the risk of death at 28 days (RR, 0.90; 95% CI, 0.78–1.03, P = 0.12) in ARDS patients [26]. Deep sedation accompanied by NMBs can result in negative outcomes such as mortality or delayed time to extubation [27]. It has been reported that early deep sedation is associated with higher mortality in mechanically ventilated critically ill patients [21–23,27]. Shehabi et al. suggested that the sedation intensity in the first 48 h was an independent predictor of increased 180 d mortality (HR [95% CI], 1.29 [1.15–1.46], p<0.001) [21]. In the multivariable Cox proportional hazard regression models, depth of sedation was positively correlated with mortality. They suggested that light sedation could be a goal to improve patients’ outcomes in the early stage of mechanical ventilation [21,22,27]. Although we did not present the data of sedation intensity, there is a possibility that NMB users were more deeply sedated than NMB nonusers. Therefore, NMBs should be avoided whenever possible in critically ill patients who can tolerate ventilation with a lighter sedation according to recent ARDS guidelines [24].

NMBs have some favorable effects in patients with ARDS. NMB infusion is associated with an improvement in oxygenation and can be beneficial in increasing expiratory transpulmonary pressure in moderate to severe ARDS patients [28]. Ho et al. reported that the PaO2/FIO2 ratio at 48 h in moderate to severe ARDS patients was higher in NMB users than nonusers, and the risk of barotrauma was lower in NMB users than nonusers (RR 0.55 [95% CI: 0.35–0.85], P = 0.007) [26]. On the other hand, NMB use is associated with poor outcomes such as delayed extubation, increased delirium, and a longer duration of mechanical ventilation [21–23,27,29]. In accordance with previous studies, our results revealed that NMB users had longer durations of ICU stay and mechanical ventilation. These may be associated with the higher incidence of tracheostomy in NMB users.

Concerns regarding NMB use include not only early deep sedation but also the prolonged use of NMBs. According to recent guidelines and clinical studies, the use of NMBs for up to 48 h is recommended [3,18,24,30,31]. Dodson et al. reported that long-term NMB infusion is associated with denervation-like changes, which could cause prolonged muscle paralysis [32]. Saccheri et al. reported that ICU‑acquired weakness was associated with increased long-term mortality in critically ill patients [33]. It has been suggested that NMB use ≥ 3 d can cause ICU-acquired weakness, and this may lead to increased 90 d mortality rates. Although the association between NMB use and ICU-acquired weakness remains controversial [34], we found that NMB users had a 1.4 times higher mortality rate at 90 days than NMB nonusers. If NMB is required to achieve lung protective ventilation, it is desirable to discontinue it within 3 days if possible.

This study has some limitations. First, due to the retrospective nature of the study, it was difficult to obtain some information. We did not describe the exact doses of drugs or adjuvant therapy such as prone positioning, which might have affected mortality. In addition, ventilatory parameters and respiratory mechanics such as driving pressure, plateau pressure, tidal volume, and static compliance were not collected. NMB can be used with various indications in critically ill patients such as facilitation of tracheal intubation, facilitation of mechanical ventilation, control of status asthmaticus or therapeutic hypothermia [14]. Although, we cannot demonstrate exact indication of NMB, patients who used NMB for intubation purpose would not be included in NMB users. Second, although PS methods were employed to match the potential differences between the two groups, there might have been residual confounding factors. Therefore, additional clinical studies are needed to assess the effect of NMBs in critically ill patients receiving mechanical ventilation for reasons other than ARDS.

Conclusions

NMB use was not associated with lower 30 d mortality in mechanically ventilated pneumonia patients with moderate to severe hypoxemia. Rather, NMB users had higher 90 d mortality and longer duration of mechanical ventilation or ICU stay than NMB nonusers. Furthermore, NMB use ≥ 3 d was associated with higher 90 d mortality compared to NMB use < 3 d. Therefore, NMBs should be used with caution in critically ill pneumonia patients, and prolonged NMB use should be avoided if possible.

Data Availability

https://doi.org/10.6084/m9.figshare.21391353.v1.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Steven Eric Wolf

22 Aug 2022

PONE-D-21-37840Neuromuscular blockade in mechanically ventilated pneumonia patients with moderate to severe hypoxemiaPLOS ONE

Dear Dr. Kwon,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Academic Editor - Thank you for submitting your paper to us for review.  I sent it to five distinguished referees for comment and decision of whom two agreed to review; you will see these below.  They thought that the paper has merit, but each have raised some substantial issues to be addressed in a revision.  Please carefully consider the comments below and reply directly to each in a cover letter with appropriate marked and linked changes to the manuscript.  I look forward to seeing the revision, which I will send back to the same referees for further comment and decision.  Please understand that this is not a guarantee of future publication, as the revised manuscript itself must stand on its own merit.  In particular, please pay attention to the comments from the first referee in regard to COVID.

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Reviewer #2: Yes

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Reviewer #2: I Don't Know

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Reviewer #2: No

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Reviewer #1: 1)The time frame of this study includes the COVID pandemic. There is no reference to these patients in the paper. Were they excluded? They qualify as pneumonia. COVID patients do not start out with P/F ratios <150, but may progress there as they go into ARDS

2) ADRS vs severe pneumonia is not differentiated. Was this on purpose? How does your diagnosis of severe pneumonia differ from ARDS criteria?

3) Capacity of the institutions state the overall beds in the hospitals. For this paper, it would be useful to also identify how may ICU beds were available.

4) When excluding surgical patients, how was this determined? Any and all surgical procedures (including tracheostomy before inclusion) or just major surgical intervention. There is a good population of surgical patients who suffer from pneumonia post op.

5) There are many different indications to use neuromuscular blockade listed in the manuscript, but the triggers to paralyze are not clear. It would help if the criteria could be defined

Reviewer #2: Thank you for the opportunity to review this interesting manuscript on a relevant theme. The authors conducted a retrospective cohort study to evaluate whether neuromuscular blockade use was associated with improved survival among mechanically ventilated pneumonia patients with moderate to severe hypoxemia. The study's main limitation was that ventilatory parameters and respiratory mechanics were not evaluated between neuromuscular blockade users and nonusers, including driving pressure, plateau pressure, PEEP, tidal volume, and static complacence.

There are some questions and comments below that I hope may contribute to strengthening the paper.

#1 - The authors should indicate that the study is a retrospective cohort.

#2 - The authors should provide full detail of the population sampling technique from each hospital and include both unweight sampling number, weight %, and standard errors.

#3 - For the Cox proportional hazard regression analysis, the authors should clarify the methods for variable selection in the model.

#4 - Were there missing data? If yes, the authors should include complete details of how they handled missing data.

#5 - Regarding propensity, matching variables should be selected based on their theoretical association with both the outcome and treatment group assignment. Further information should be included in the methods to replicate and justify the matched sample. Which model (logit/probit regression) was used for the propensity score? Additionally, please provide propensity score analysis estimates and their precision, e.g., 95% confidence interval. Was there any iteration in the variable selection for the propensity scores?

#6 - Please clarify the working definition used for acute respiratory distress syndrome in the Methods. Was it Berlin definition of acute respiratory distress syndrome? Were patients with COVID-19 diagnosis included in the study?

**********

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Reviewer #2: No

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PLoS One. 2022 Dec 15;17(12):e0277503. doi: 10.1371/journal.pone.0277503.r002

Author response to Decision Letter 0

20 Sep 2022

September 20, 2022

Manuscript ID Number: PONE-D-21-37840

Neuromuscular blockade in mechanically ventilated pneumonia patients with moderate to severe hypoxemia: a multicenter retrospective study

Dear Editor

Thank you for your careful reviewing our manuscript and giving valuable comments. We have made some corrections and modification following the helpful comments. I am enclosing a list of the modification of the manuscript that we have made and our replies to the comments.

We believe we have addressed all questions and comments, but please give us more opportunity to respond if there is anything unsatisfactory or questionable.

We thank you and reviewers again for the constructive review. We are looking forward to hearing positive reply from you soon.

Sincerely yours,

Young Suk Kwon, MD

Department of Anesthesiology and Pain Medicine, Chuncheon Sacred Heart Hospital, 77 Sakju-ro, Chuncheon, 24253, South Korea

Tel: +82-10-8745-7514

Response to Reviewer 1

Q1) The time frame of this study includes the COVID pandemic. There is no reference to these patients in the paper. Were they excluded? They qualify as pneumonia. COVID patients do not start out with P/F ratios <150, but may progress there as they go into ARDS

A1) Thank you for your thoughtful comments. In this study, we enrolled the patients until December 31, 2020. Per your concern, it is a time that overlaps with the COVID pandemic. However, Korean government has prepared and responded effectively to COVID-19 crisis in the early stage. From November 2021, deaths due to severe COVID-19 was increased, executive order by Korean government was performed for preparedness of ICU beds for patients with severe COVID-19. Therefore, our five hospitals started isolation beds for critically ill COVID-19 patients at this time. So, we did not include COVID-19 patients in our study population. We have revised the manuscript as follows:

Materials and methods (revised manuscript, page 4 lines 11)

During the study period, severe COVID-19 patients were not hospitalized in the ICU.

Q2) ADRS vs severe pneumonia is not differentiated. Was this on purpose? How does your diagnosis of severe pneumonia differ from ARDS criteria?

A2) We aimed to investigated the effect of NMB in mechanically ventilated “pneumonia patients”. And pneumonia is one of the common cause of ARDS, so these could be overlapped. We did not differentiate the diseases. However, per your suggestion, we identified 27 patients with ARDS diagnosis via ICD-10 codes of diagnosis (J80). Therefore, we excluded these patients, and statistical analyses were conducted again with the help of Statistics Department of Chung-Ang University. Therefore, All Tables and Figures were revised. We have revised the flow-chart as follows:

Figure 1. Flowchart (revised manuscript, page 7 lines 13~15)

Materials and methods (revised manuscript, page 4 lines 18~19)

Patients who received a bolus injection of NMBs and with a diagnosis of ARDS were excluded.

Results (revised manuscript, page 7 lines 2~3)

had a diagnosis of ARDS (n = 27), and received a bolus injection of NMBs (n = 69).

Q3) Capacity of the institutions state the overall beds in the hospitals. For this paper, it would be useful to also identify how may ICU beds were available.

A3) Our hospitals included 231 ICU beds. Per your suggestion, we have revised the manuscript as follows:

Materials and methods (revised manuscript, page 4 lines 7~9)

The overall bed capacity and annual number of inpatients were approximately 3,000 beds (231 ICU beds) and 100,000 patients, respectively.

Q4) When excluding surgical patients, how was this determined? Any and all surgical procedures (including tracheostomy before inclusion) or just major surgical intervention. There is a good population of surgical patients who suffer from pneumonia post op.

A4) Except for 69 tracheostomy before inclusion, all surgical patients were excluded. Per your comments, there is a possibility that surgical patients can be underwent pneumonia as post op complication. However, this retrospective study can not identify the exact cause of pneumonia in surgical patients. Moreover, surgical patients may have trauma, and this can influence to the mortality, hence surgical patients can be potentially heterogeneous. In addition, surgical patients can receive mechanical ventilation and neuromuscular blockades for the surgery. For these reasons, we excluded surgical patients.

Q5) There are many different indications to use neuromuscular blockade listed in the manuscript, but the triggers to paralyze are not clear. It would help if the criteria could be defined

A5) Per your comments, there are several indications of neuromuscular blockade. According to the Renew et al., neuromuscular blockade has been used for the facilitation of tracheal intubation and facilitation of mechanical ventilation in critically ill patients (Renew et al. Journal of Intensive Care (2020) 8:37). Status asthmaticus or therapeutic hypothermia can be indications for the use of neuromuscular blockades. However, we cannot demonstrate the clear indication fo neuromuscular blockade because of the nature of retrospective study. Generally, neuromuscular blockades used bolus injection during endotracheal intubation. Therefore, we defined neuromuscular blocker user as cisatracrium and vecuronium via continuous infusion, and 69 patients received NMB via injection was excluded. not injection mehod. Although, we cannot demonstrate exact indication of neuromuscular blockade, patients who used neuromuscular blockade for intubation purpose would not be included in NMB users. Per your concern, we further described this in the limitation section. We have revised the manuscript as follows:

Materials and methods (revised manuscript, page 4 lines 18~19)

Patients who received a bolus injection of NMBs and with a diagnosis of ARDS were excluded.

Materials and methods (revised manuscript, page 5 lines 17~18)

To avoid including NMB users requiring a bolus injection for endotracheal intubation, we defined NMB users as patients who received a continuous infusion of NMBs.

Results (revised manuscript, page 7 lines 2~3)

had a diagnosis of ARDS (n = 27), and received a bolus injection of NMBs (n = 69).

Discussion (revised manuscript, page 13 lines 9~13)

NMBs may be used for various purposes in critically ill patients, such as facilitation of tracheal intubation, facilitation of mechanical ventilation, control of status asthmaticus, or therapeutic hypothermia.[18] Although we could not identify the exact indications for NMB use, patients who used NMBs for intubation were not included in the group of NMB users in this study.

 

Response to Reviewer 2

Reviewer #2: Thank you for the opportunity to review this interesting manuscript on a relevant theme. The authors conducted a retrospective cohort study to evaluate whether neuromuscular blockade use was associated with improved survival among mechanically ventilated pneumonia patients with moderate to severe hypoxemia. The study's main limitation was that ventilatory parameters and respiratory mechanics were not evaluated between neuromuscular blockade users and nonusers, including driving pressure, plateau pressure, PEEP, tidal volume, and static complacence.

A) Thank you for your thoughtful commens. Unfourtunately, several parameters such as driving pressure, plateau pressure or tidal volume did not obtained due to the retrospective study design. There are a lot of missing data in these variables. However, per your suggestion, we added PEEP varable in this revision, and we have revised the limitation section as follows:

Moreover, per Reviewr #1’s suggestion, we identified 27 patients with ARDS and 69 bolus injection of NMB, and excluded them. All statistical analysis was conducted again with the help of Statistics Department of Chung-Ang University. Therefore, Tables and Figures were revised.

Discussion (revised manuscript, page 13 lines 7~9)

In addition, ventilatory and respiratory parameters such as driving pressure, plateau pressure, tidal volume, and static compliance were not collected.

There are some questions and comments below that I hope may contribute to strengthening the paper.

Q1) The authors should indicate that the study is a retrospective cohort.

A1) Thank you for your thoughtful comment. Per your suggestion, we have revised the title as follows:

Title

Neuromuscular blockade in mechanically ventilated pneumonia patients with moderate to severe hypoxemia: a multicenter retrospective study

Q2) The authors should provide full detail of the population sampling technique from each hospital and include both unweight sampling number, weight %, and standard errors.

A2) Hallym University Medical Center (HUMC) had clinical big data analytic solution Smart CDW, which can analyze the electronic medical record text and integrated fixed data at five hospitals. Thus, using the Smart CDW, we collected clinical data of total patients with pneumonia at five hospitals.

During the study period (between Jan. 1, 2011, and Dec. 31, 2020), 1,146,506 patients admitted to hospitals. Patients who admitted to the ICU were 112,322, and mechanically ventilated patients were 29,554. Among them, patients with pneumonia (≥18 yr) were 3,357. We have revised the manuscript as follows:

Materials and methods (revised manuscript, page 5 lines 1~3)

We used a clinical big data analytic solution (Smart CDW), which can analyze the electronic medical record text and integrate the data of five hospitals. The following data on the day of initiation of mechanical ventilation were obtained

Results (revised manuscript, page 6 lines 22~24)

During the study period, 1,146,506 patients were admitted to the hospitals, and 112,322 patients were admitted to the ICU. The number of mechanically ventilated patients was 29,554, and there were 3,357 patients with pneumonia aged over 18 years (Fig 1).

Q3) For the Cox proportional hazard regression analysis, the authors should clarify the methods for variable selection in the model.

A3) In this paper, univariable and multivariable stratified Cox proportional hazard regression models were used to compare the survival between two groups. Please note that we used stratified Cox proportional hazard regression, because it is a proper method for the matched (correlated) data set. Multivariate regression analysis was used to adjust the effect of imbalance in the baseline. Age, Modified early warning score, Charlson comorbidity index, and PEEP were selected as the adjust variables, because there were significant differences between two groups even after matching. We have revised the manuscript as follows:

Materials and methods (revised manuscript, page 6 lines 12~17)

Univariable and multivariable stratified Cox proportional hazard regression models were used to calculate the hazard ratio (HR) and 95% confidence interval (CI) for the risk of mortality. Multivariate regression analysis was used to adjust the effect of imbalance in the baseline. Age, modified early warning score, CCI, and positive end expiratory pressure (PEEP) were selected as adjusted variables as there were significant differences between two groups even after matching.

Q4) Were there missing data? If yes, the authors should include complete details of how they handled missing data.

A4) There were total 1103 patients in this data set, and 411 patients used NMB. The number of missing values in each variable is as follows.

Number of missing observations : PEEP - 5 , BMI - 39, APACHE - 45

Several studies recommend multiple imputation to impute missing data, but there is still debate as to which method is the most appropriate for propensity score matching [1,2]. Even we excluded the missing values in the matching process, only 27 (6.5%) patients of the NMB users are excluded from the original data set and 384 NMB users are obtained after matching. Therefore, we did not consider any imputation method in this study.

1. Stuart EA. Matching methods for causal inference: A review and a look forward. Stat Sci 2010;25:1-21.

2. Leite W, Aydin B. editors. A comparison of methods for imputation of missing covariate data prior to propensity score analysis. Washington, DC: American Education Research Association Conference, 2016.

Q5) Regarding propensity, matching variables should be selected based on their theoretical association with both the outcome and treatment group assignment. Further information should be included in the methods to replicate and justify the matched sample. Which model (logit/probit regression) was used for the propensity score? Additionally, please provide propensity score analysis estimates and their precision, e.g., 95% confidence interval. Was there any iteration in the variable selection for the propensity scores?

A5) Thank you for the comment.

Propensity score analysis estimates and their precision (standard error) are presented in the following table (Table 1). As you pointed out, matching variables can be selected based on the theoretical association with both the outcome and treatment group assignment. However, some variables should be included as matching variables based on the previous clinical research even if they were not statistically significant. Therefore, in this paper we selected matching variables based on both theoretical association in our data and also on the clinical research.

In the revised paper, age, sex, body mass index, time from hospitalization to ICU admission, time from hospitalization to mechanical ventilation initiation, APACHE II score, modified early warning score, CURB-65, transferred from skilled nursing facility, CCI, aspiration pneumonia, diabetes, congestive heart failure, myocardial infarction, chronic pulmonary disease, liver disease, moderate to severe chronic kidney disease, any malignancy, rheumatic disease, dementia, cerebrovascular disease, continuous renal replacement therapy, transfusion, vasopressors and inotropes, corticosteroids, opioids, sedatives, and PEEP are used as matching variables.

For the matching process, we used nearest neighbor 1: 1 matching method with logit regression distance.

(Table 1)

Q6) Please clarify the working definition used for acute respiratory distress syndrome in the Methods. Was it Berlin definition of acute respiratory distress syndrome? Were patients with COVID-19 diagnosis included in the study?

A6) Since 2012 Berlin definition of ARDS, recent guidelines have been published based on the Berlin definition. However, in this retrospective study, the population of this study included the patients before 2012 Berlin definition of ARDS. Therefore, we enrolled ARDS patients according to the ICD-10 codes of diagnosis.

We did not include COVID-19 patients in our study population. Although, study period was overlapped with COVID-19 pandemic, our five hospitals started isolatation beds for critically ill COVID-19 patients from November 2021. We have revised the manuscript as follows:

Materials and methods (revised manuscript, page 5 lines 16~17)

ARDS was identified with an ICD-10 code of J80.

Materials and methods (revised manuscript, page 4 lines 11)

During the study period, severe COVID-19 patients were not hospitalized in the ICU.

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Decision Letter 1

Steven Eric Wolf

24 Oct 2022

PONE-D-21-37840R1Neuromuscular blockade in mechanically ventilated pneumonia patients with moderate to severe hypoxemia: a multicenter retrospective studyPLOS ONE

Dear Dr. Kwon,

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Reviewer #2: All comments have been addressed

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Reviewer #1: The use of a sedation score that is not universally used in their study is a limitation, but the data and conclusions are sound and supported by what they have observed.

Reviewer #2: Thank you for addressing the comments. The authors have made appropriate adjustments to the original submission, refining and strengthening it to good effect. I have only one concern regarding excluding patients with ARDS diagnoses since it is impossible to exclude some patients with missing ARDS diagnoses remained in the included patients due to the retrospective study design. In the LUNG SAFE study, the largest international cohort among patients with ARDS, the diagnosis of ARDS was missed entirely in 40% of patients, while ARDS ​​recognition ranged from 51% in mild ARDS to 79% in severe ARDS. In this respect, I suggest the authors keep patients with ARDS diagnosis recognition in the analysis or present both analyses, including and excluding patients with ARDS diagnosis recognition.

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Reviewer #2: No

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PLoS One. 2022 Dec 15;17(12):e0277503. doi: 10.1371/journal.pone.0277503.r004

Author response to Decision Letter 1

27 Oct 2022

Response to Reviewer 1

Q) Reviewer #1: The use of a sedation score that is not universally used in their study is a limitation, but the data and conclusions are sound and supported by what they have observed.

A) Thank you for your thoughtful comment. Per your suggestion, we deleted the description in limitation section: “including the level of sedation (e.g., the Richmond Agitation and Sedation Scale, RASS) or delirium (e.g., the Confusion Assessment Method for the Intensive Care Unit, CAM-ICU).”

Response to Reviewer 2

Q)Reviewer #2: Thank you for addressing the comments. The authors have made appropriate adjustments to the original submission, refining and strengthening it to good effect. I have only one concern regarding excluding patients with ARDS diagnoses since it is impossible to exclude some patients with missing ARDS diagnoses remained in the included patients due to the retrospective study design. In the LUNG SAFE study, the largest international cohort among patients with ARDS, the diagnosis of ARDS was missed entirely in 40% of patients, while ARDS recognition ranged from 51% in mild ARDS to 79% in severe ARDS. In this respect, I suggest the authors keep patients with ARDS diagnosis recognition in the analysis or present both analyses, including and excluding patients with ARDS diagnosis recognition.

A) Thank you for your thoughtful commens. Per your suggestion, we reanalyzed the data including ARDS. After included of ARDS diagnosis, 90 d mortality rate was significiantly higher in NMB users (39.7% vs. 31.9%, p = 0.021). We described the revised results of the entire paper. We highlighted the main changes as yellow color. We thank you for your thoughtful comments again.

Attachment

Submitted filename: Response to Reviewers10.27.docx

Click here for additional data file. (45.9KB, docx)

Decision Letter 2

Steven Eric Wolf

31 Oct 2022

Neuromuscular blockade in mechanically ventilated pneumonia patients with moderate to severe hypoxemia: a multicenter retrospective study

PONE-D-21-37840R2

Dear Dr. Kwon,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Steven Eric Wolf, MD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Steven Eric Wolf

18 Nov 2022

PONE-D-21-37840R2

Neuromuscular blockade in mechanically ventilated pneumonia patients with moderate to severe hypoxemia: a multicenter retrospective study

Dear Dr. Kwon:

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on behalf of

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Academic Editor

PLOS ONE

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