Skip to main content
PLOS ONE logoLink to PLOS ONE
. 2024 Jun 3;19(6):e0304508. doi: 10.1371/journal.pone.0304508

Lung ultrasound is associated with distinct clinical phenotypes in COVID-19 ARDS: A retrospective observational study

Roy Rafael Dayan 1,*,#, Maayan Blau 1,#, Jonathan Taylor 2, Ariel Hasidim 1, Ori Galante 1,3, Yaniv Almog 1,3, Tomer Gat 1, Darya Shavialiova 1, Jacob David Miller 1, Georgi Khazanov 1, Fahmi Abu Ghalion 1, Iftach Sagy 1,4, Itamar Ben Shitrit 1,4, Lior Fuchs 1,3
Editor: Francesca Pennati5
PMCID: PMC11146726  PMID: 38829891

Abstract

Background

ARDS is a heterogeneous syndrome with distinct clinical phenotypes. Here we investigate whether the presence or absence of large pulmonary ultrasonographic consolidations can categorize COVID-19 ARDS patients requiring mechanical ventilation into distinct clinical phenotypes.

Methods

This is a retrospective study performed in a tertiary-level intensive care unit in Israel between April and September 2020. Data collected included lung ultrasound (LUS) findings, respiratory parameters, and treatment interventions. The primary outcome was a composite of three ARDS interventions: prone positioning, high PEEP, or a high dose of inhaled nitric oxide.

Results

A total of 128 LUS scans were conducted among 23 patients. The mean age was 65 and about two-thirds were males. 81 scans identified large consolidation and were classified as “C-type”, and 47 scans showed multiple B-lines with no or small consolidation and were classified as “B-type”. The presence of a “C-type” study had 2.5 times increased chance of receiving the composite primary outcome of advanced ARDS interventions despite similar SOFA scores, Pao2/FiO2 ratio, and markers of disease severity (OR = 2.49, %95CI 1.40–4.44).

Conclusion

The presence of a “C-type” profile with LUS consolidation potentially represents a distinct COVID-19 ARDS subphenotype that is more likely to require aggressive ARDS interventions. Further studies are required to validate this phenotype in a larger cohort and determine causality, diagnostic, and treatment responses.

Introduction

The coronavirus disease 2019 (COVID-19) pandemic is a global crisis, that has challenged healthcare and economic systems worldwide [1]. COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, predominantly causes viral pneumonia, with severity ranging from asymptomatic infection to fatal respiratory failure and acute respiratory distress syndrome (ARDS) [2]. The significant disease heterogeneity and potential for rapid deterioration mandates an objective, quick, bedside lung assessment tool that helps assess illness severity and guide clinical decisions.

Recent years have brought increasing recognition that ARDS represents a complex and heterogenous syndrome, with distinctive anatomic, physiologic, and molecular patterns [3]. Landmark work by Calfee and colleagues has demonstrated distinct ARDS phenotypes that respond differently to therapeutic interventions such as high PEEP and liberal fluid strategies [4,5]. Radiographic subtypes of ARDS, delineated as nonfocal/diffuse and focal/lobar, have also been described [610]. The distribution of pulmonary opacities and degree of lung consolidation represent variables with the potential to change lung mechanics and impact mechanical ventilation strategies [11]. In the LIVE trial, a personalized PEEP and prone positioning strategy based on radiographic sub-phenotypes achieved a reduction in 90-day mortality when only considering per-protocol treated patients [10].

In COVID-19 pneumonia, lung ultrasound (LUS) correlates with chest computerized tomography (CT) and is superior to chest X-ray in detecting pulmonary pathologies [1215]. Chest CT findings have also been associated with COVID-19 pneumonia severity [16], collectively suggesting LUS may serve as a surrogate that is accurate, safe, and can be performed bedside. The characteristic LUS findings in COVID-19 patients involve B-lines, consolidations, and pleural irregularities (S1 Fig) [17]. These sonographic lung artifacts collectively have been associated with mortality and Intensive Care Unit (ICU) admission [1820]; lung consolidations were specifically associated with critical illness [21,22]. A recent study by our group [23] described a simple clinical sonographic score based on known point-of-care ultrasound (POCUS) lung findings of COVID-19 pneumonia patients. The score, called "Point-of-care ultrasound Lung Injury Score" (PLIS) (S2 Fig and S1 Table) correlated with SOFA score, ICU admission, and mortality in patients with COVID-19 pneumonia, and was conducted successfully by novice operators to facilitate clinical patient care. In this follow-up study, we aim to investigate whether the sonographic detection of a large consolidation compared to either small or no consolidations, as represented by the C score component of the PLIS, can help stratify and phenotype patients with COVID-19 ARDS requiring mechanical ventilation. We examined whether patient PLIS C-score grades were associated with different outcomes, including respiratory parameters, mechanical ventilation characteristics, and response to therapeutic interventions.

Methods

This observational retrospective cohort study was conducted at the Soroka University Medical Center, a tertiary care academic medical center in southern Israel. The data was collected during the COVID-19 pandemic among patients admitted to the medical intensive care unit (ICU) between April 1st and September 30th, 2020. De-identified data was accessed between June 2021 and May 2022. Patients were included in the study if they had a diagnosis of COVID-19 confirmed via positive polymerase chain reaction for SARS-COV2 virus, required invasive mechanical ventilation, and were diagnosed with ARDS as set forth in the Berlin criteria [24]. Patients treated with extracorporeal membrane oxygenation in their clinical course were excluded. This study was approved by the institutional ethics committee (IRB #0195–20) with a waiver of informed consent. PLIS scans were completed by senior physicians experienced with LUS scans and internal medicine residents who received dedicated training with the LUS PLIS protocol. LUS scans were performed bedside during morning rounds as part of routine clinical assessment as an extension of the physical exam, as well as during specific clinical deterioration events, and findings were formally documented in the medical record. The ultrasound machines used were VENUE GO, GE Healthcare, R2 version. LUS scans were conducted with the 3SC phased-array probe, using the lung preset as set by the manufacturer to detect B-lines, and the cardiac preset to detect lung consolidations.

A total of 128 PLIS scans were conducted among 23 mechanically ventilated COVID-19 ARDS patients during the study duration. The PLIS scans were classified as “B-type” or “C-type” based on the value of the C component of the PLIS score. The "C-type" represents COVID-19 patients requiring mechanical ventilation with large LUS sonographic consolidations, defined as a consolidation measuring over 4 cm in the largest diameter (PLIS C-score classification of C2). All ultrasound images evaluating for consolidations were obtained in the mid-posterior axillary line above the diaphragm (Fig 1, designated zone 2). We classified the "B-type" phenotype as those who had minimal to small consolidations (less than 4 cm at greatest diameter) and met the criteria for a PLIS C-score of C0 or C1. L.R., an attending intensivist with over 10 years of LUS experience reviewed and agreed with the classifications.

Fig 1. Ultrasound image acquisition and sonographic sub-pleural lung consolidations.

Fig 1

The figure depicts the location of ultrasound image acquisition, situated at the mid-posterior axillary line above the diaphragm (A), alongside two distinct sonographic sub-pleural lung consolidations. These consolidations exhibit varying sizes: A small consolidation (B) and a larger consolidation (C).

Each patient could shift between the “B type” and “C type” phenotypes throughout their clinical course, according to the findings from the specific PLIS scan conducted that day. Real-time sonographic results and PLIS scores were not used to guide clinical practice but were collected for isolated research purposes to assess for clinical associations. Other variables collected included demographic characteristics, vital signs, laboratory results, admission characteristics, ventilation, and physiologic parameters. Oxygenation was assessed by measuring the PaO2/FiO2 ratio, while ventilation was estimated by using the Bohr equation, with Enghoff’s modification [25]. Data was matched to each PLIS study according to the time the sonographic scan was conducted. Our primary outcome was a composition of three cardinal ARDS interventions: prone positioning, a high PEEP (≥ 12 mmHg), and a high dose of inhaled nitric oxide (NO) (≥ 15 ppm). This composite was selected to represent interventions associated with more significant ARDS illness (“advanced ARDS interventions”). Secondary outcomes included PaO2/FiO2 ratio and other respiratory parameters.

Data is expressed as mean ± standard deviation (SD), median ± interquartile range (IQR), or number and percentage. Each single PLIS scan obtained from the patients who met inclusion criteria composed the unit used for analysis. Patients were stratified by “B-type” versus “C-type” PLIS, and data was analyzed using the t-test for continuous variables, the chi-square for dichotomous variables, and parametric tests for ordinal variables. Multivariate generalized estimating equation (GEE) regression was used to evaluate the covariates associated with the study outcomes: PEEP, inhaled NO doses, and prone position—a composite outcome of the above. The GEE model allows the analysis of repeated measures with non-normal response variables, including the primary outcome. The final model was selected based on the plausible clinical explanation, statistical significance, and goodness of fit. The statistical analysis was conducted using SPSS version 25.0.

Results

A total of 47 PLIS scans were classified as “B-type” studies (owing to a C-score of C0-C1), and 81 scans were classified as “C-type” studies (C-score of C2). Patients’ baseline characteristics and admission information are presented in Table 1. The average age of patients in the cohort was 65.3 years (±11.9) and about two-thirds were males (69.9%, n = 16). Mean body mass index (BMI) was 27.3 (±3.9), 47.8% (n = 11) had diabetes mellitus, and 17.4% (n = 4) from chronic obstructive pulmonary disease. The median ICU length of stay was 17 days and the mortality in the cohort was 61%.

Table 1. General characteristics of the cohort.

Variable All Patients (n = 23)
Age (years) (mean ± SD) 65.3 ± 11.9
Males n(%) 16 (69.9%)
Smoking n(%) 5 (21.7%)
Body Mass Index (mean ± SD) 27.3 ± 3.9
Diabetes n(%) 11 (47.8%)
Chronic obstructive pulmonary disease n(%) 4 (17.4%)
Malignancy n(%) 3 (13%)
Chronic kidney disease n(%) 2 (8.7%)
Cerebrovascular disease n(%) 2 (8.7%)
Congestive heart failure n(%) 0 (0)
Mortality n(%) 14 (60.9%)
Hospitalization days in Intensive Care Unit (median, interquartile range) 17 (7–32)
Total hospitalization days (median, interquartile range) 24 (14–38)
Days on mechanical ventilation
(median, interquartile range)
16 (6–27)

Table 2 compares the clinical characteristics, ventilatory parameters, and therapies at the time of POCUS scanning and PLIS acquisition, comparing “B-type” and “C-type” studies (for complete and comprehensive cohort outcomes, see S2 Table).

Table 2. Clinical characteristics, respiratory parameters, and interventions regarding B-type versus C-type patterns during the PLIS scan.

Variable B-Type scans
(n = 47)
C-Type scans
(n = 81)
P-value
Clinical Characteristics and Laboratory Results
Heart rate (mean ± SD) (bpm) 94 ± 15 92 ± 11 0.5
Mean arterial pressure (mean ± SD) (mmHg) 83 ± 37 76 ± 39 0.36
Systolic blood pressure (mean ± SD) (mmHg) 136 ± 21 128 ± 18 0.05
Diastolic blood pressure (mean ± SD) (mmHg) 78 ± 11 77 ± 14 0.63
Temperature (mean ± SD) (Celsius) 37.2 ± 0.8 37.2 ± 0.6 0.61
Oxygen saturation % (mean ± SD) 91 ± 7 91 ± 3 0.62
International Normalized Ratio (mean ± SD) 1.28 ± 0.3 1.15 ± 0.14 0.12
Serum Albumin (mean ± SD) (g/dl) 2.53 ± 0.38 2.23 ± 0.38 0.015
Total Bilirubin (mean ± SD) (mg/dl) 0.48 ± 0.23 0.48 ± 0.3 >0.9
Platelet count (mean ± SD) (per μL of blood) 325 ± 110 348 ± 124 0.3
Serum Creatinine (mean ± SD) (mg/dl) 1.11 ± 1.13 0.85 ± 0.66 0.11
SOFA score (median, interquartile range) 5 (4–7) 6 (4–7) 0.39
Total PLIS (median, interquartile range) 2 (1–3) 4 (3–4) <0.001
Lactate (median, interquartile range) (mmol/L) 1.4 (1.2–2.1) 1.9 (1.2–2.3) 0.14
Ventilation and Respiratory Parameters
PaO2/FiO2 (median, interquartile range) 178 (123–242) 137 (95–193) 0.06
PaCO2 (median, interquartile range) (mmHg) 50 (44–58) 52 (45–57) 0.29
End-Tidal CO2 (median, interquartile range) (mmHg) 32 (29–36) 35 (31–38) 0.01
Respiratory rate (median, interquartile range) (breaths per minute) 20 (15–24) 20 (16–24) 0.26
Tidal volume (median, interquartile range) (ml) 555 (500–600) 535 (500–580) 0.28
Minute ventilation (median, interquartile range) (ml/minute) 10,000 (7,650–12,440) 10,700 (8,580–12,000) 0.8
Dead space (vd/vt) (% from Tidal volume) 33 (23–40) 32 (26–42) 0.86
Peak pressure (median, interquartile range) 17 (15–20) 19 (15–23) 0.42
ARDS Interventions
Prone position n(%) 3 (6.4) 14 (17.3%) 0.08
PEEP (median, interquartile range) (CmH2O) 10 (6–13) 12 (10–14) 0.14
NO administration n(%) 9 (19.1) 29 (35.8%) 0.047
NO dose (median, interquartile range) (ppm) 15 (9–16) 15 (13–17) 0.59
Advanced ARDS interventions* n(%) 19 (40.4) 48 (59.3%) 0.04
Vasopressor administration n(%) 36 (76.6) 70 (86.4%) 0.22

ARDS- Acute Respiratory Distress Syndrome; FiO2—Fractional-inspired oxygen; NO—nitric oxide; PLIS—Point-of-care Lung Ultrasound Injury Score; PaCO2- Partial pressure of CO2 in arterial blood; PaO2- Partial pressure of oxygen in arterial blood; PEEP—positive end-expiratory pressure; SOFA score—Sequential Organ Failure Assessment score.

*Advanced ARDS interventions–a composite outcome of prone positioning, high PEEP (≥ 12 CmH2O), or high dose of inhaled NO (≥15 ppm).

The median PLIS was higher in the “C-type” group as anticipated (4 vs 2, p <0.001) while the median SOFA score did not differ significantly between groups (SOFA score of 6 versus 5 points, p = 0.39). The median PaO2/FiO2 ratio was 178 in the “B-type” as compared to 137 in the “C-type” group, a difference that was not statistically significant (p = 0.06). Ventilation parameters were similar between the two sonographic groups; peak inspiratory pressures (PIP) and tidal volumes (TV) were unchanged, with a median PIP of 19 CmH2O vs 17 CmH2O, (p = 0.42) and TV of 555 ml vs 535 ml (p = 0.28). The primary composite outcome of applied high levels of PEEP (≥ 12 CmH2O), high doses of inhaled NO (≥15 ppm) or proning was found at significantly higher rates in patients with a “C-type” study (59% vs 40%, p = 0.04). Analyzing the components of the composite outcome separately, patients with the “C-type” phenotype were significantly more likely to be treated with inhaled NO at the time of sonography acquisition (36% vs 19%, p = 0.047), and were more likely to be placed in the prone position, though this specific difference in positioning did not meet the threshold for significance (17% vs 6%, p = 0.08). Applied PEEP alone at the time of PLIS scanning did not differ significantly between groups.

Table 3 describes a generalized multivariate estimation (GEE) model for the odds of being treated with the advanced ARDS therapeutic interventions including prone position, high PEEP, or high doses of inhaled NO therapy for “C-type” versus “B-type” phenotypes. Comorbid diabetes mellitus, age, BMI, and PaO2/FiO2 ratio did not significantly increase the risk for the need for these interventions. However, possessing a “C-type” PLIS sonographic study pattern was found to significantly increase the odds of receiving such an intervention as represented by the composite outcome by 2.5 times compared to having a “B-type” study (OR = 2.49, CI = 1.40–4.44).

Table 3. Multivariate Generalized Estimating Equation (GEE) regression for the composite outcome of advanced ARDS interventions*.

Variable OR P-value 95% Confidence interval
Age 0.99 0.82 0.91–1.07
Body mass index 1.04 0.81 0.72–1.51
PaO2/FiO2 1.01 0.01 1.00–1.02
Diabetes 0.24 0.13 0.04–1.15
C-type 2.49 0.01 1.40–4.44

FiO2- Fractional inspired oxygen; PaO2- Partial pressure of oxygen in arterial blood.

*Advanced ARDS interventions–a composite outcome of prone positioning, high PEEP (≥ 12 CmH2O), or high dose of inhaled NO (≥15 ppm).

Fig 2 depicts the course of ten selected COVID-19 ARDS patients on mechanical ventilation, and visually illustrates their clinical status, ARDS interventions required, and the corresponding LUS sub-group (“C-type” vs “B-Type” studies) during their ICU stay. Patients with the most available PLIS data were selected to represent the study concept visually.

Fig 2. The course of ten representative COVID-19 ARDS ventilated patients* during their Intensive care unit hospitalization.

Fig 2

The figure graphically represents the course of ten ventilated patients with COVID-19 ARDS. half survived (in blue) and half died (in red). The PaO2 to FiO2 ratio is plotted on the y-axis and the days of mechanical ventilation on the x-axis. Each circle represents a single PLIS study performed (red circle for the “c-type” and blue circle for the “b-type”). Vertical arrows signify patients ventilated with prone positioning. Backgrounds colored yellow and green represent patients currently ventilated with a high PEEP (12 cmH2o or more) and a high dose of inhaled nitric oxide (15ppm or above), respectively. *Patients with the most available PLIS data were selected to visually represent the cohort.

Discussion

In this follow-up study to our original description of the PLIS, we aim to further categorize heterogenous COVID-19 ARDS patients requiring mechanical ventilation and identify distinctive sonographic phenotypes according to the presence (“C-type”) or absence (“B-type”) of large lung consolidation by bedside ultrasound. Our previous work [23] concerning hospitalized COVID-19 pneumonia patients described the PLIS. This new simple clinical-sonographic lung ultrasound score is quick, reproducible, and easy to perform at the bedside, and has been shown to correlate with the SOFA score, ICU rate of admission, and the risk of in-hospital mortality. Here we further categorized patients into two broad sonographic lung patterns based on the burden of lung consolidation. Our results demonstrate that for similar SOFA scores, PaO2/FiO2 ratios, and markers of clinical illness severity, those characterized by a “C-type” PLIS study were more likely to be treated with inhaled NO at the time of POCUS scanning and had a significantly increased likelihood of concurrently receiving a composite outcome of high PEEP, high dose of inhaled NO (>15 ppm) or ventilation in the prone position (OR = 2.49). Our data suggests that the “C-type” profile of COVID-19 ARDS patients represents a distinct sub-phenotype of COVID-19 ARDS, irrespective of illness severity, that may be more likely to require advanced therapies to improve oxygenation.

Fig 2 graphically delineates the course of ten representative patients during their ICU stay to illustrate the study concept. Those with the most PLISs available were chosen for the purpose of visual representation. As a representative example, patients #2, #,3, and #4 (all survivors) possessed mostly the “C-Type” profiling at the beginning of their critical illness, which was characterized by severe hypoxemia and more advanced ARDS interventions, relative to the end of their clinical course, which was characterized with “B-type” phenotype and fewer interventions. The opposite was true regarding patients #6 and #9 (non-survivors): near the end of their course, they were characterized mostly by “C-type” lung injury and required advanced interventions.

As the field of critical care increasingly moves towards precision medicine, several authors have sought to profile heterogeneous lung injury in COVID-19 ARDS. The Gattinoni model [26] early in the pandemic proposed two different phenotypes on a time-related disease spectrum: The “L-phenotype” and the “H-phenotype”. The latter is characterized by high lung weight, and high consolidation burden, with a relatively high potential for recruitment of non-aerated lung areas. Although this has subsequently been challenged [27], conceptually, the “H-phenotype” may parallel the “C-type” of the PLIS and could potentially be identified early by LUS. In a landmark study in ARDS before the COVID-19 pandemic, latent class analysis identified two distinct ARDS phenotypes: one termed “hyperinflammatory”, associated with more inflammatory cytokines, lower serum bicarbonate, and higher vasopressor requirements, and a different “hypoinflammatory” phenotype, with lower concentrations of cytokines, higher bicarbonate, and decreased vasopressor needs [4]. These phenotypes have been validated in multiple large observational cohorts, with post hoc analysis of landmark ARDS trials demonstrating differing responses to randomized PEEP strategies between phenotypic profiles [4]. This categorization has extended to patients with COVID-19, where the hyperinflammatory phenotype showed an improved response to corticosteroids [28]. Radiographic subphenotypes of ARDS have similarly been described, stratified into nonfocal and lobar types [57]. Nonfocal/diffuse ARDS has been associated with worse lung compliance, higher mortality, and lower levels of sRAGE, a plasma biomarker of epithelial damage [8]. Similarly, in a per-protocol analysis of the LIVE trial, a personalized PEEP and prone positioning strategy based on radiographic sub-phenotypes achieved a reduction in 90-day mortality [10]. These concepts have been extended to COVID-19 ARDS, as latent class analysis has revealed multiple COVID-19 ARDS sub-phenotypes, stratified by dead space ventilation and mechanical power, with important patient-related downstream outcomes [29]. Together, this work demonstrates that subgroups of ARDS may have differential responses to therapy and underscores the importance and urgency of research to prospectively identify treatment-responsive subgroups, along with markers to identify them at the bedside.

Lung ultrasound is ripe for sonographic ARDS phenotyping. Wang et al. [30] showed that in non-COVID-19 ARDS patients, response to prone positioning can be predicted by the LUS score composed of 16 scanning sites. This has subsequently been replicated in awake and spontaneously breathing severe COVID-19 patients [31]. Bouhemad et al. [32] demonstrated a significant correlation between PEEP-induced lung recruitment as measured by pressure-volume curves and an ultrasound reaeration score. Lichter et al. [33] showed an association between worsening LUS scores and increased PEEP requirements in COVID-19 ARDS ventilated patients, though the score used in this study consisted of a complicated 12-point scanning protocol.

The totality of the evidence suggests that lung ultrasound has an important role to play in further characterizing and phenotyping this population, and perhaps guiding interventions. The strength of the PLIS protocol lies in its feasibility and simplicity. While the above studies used more complicated and time-consuming LUS scores based on multiple scanning points, we dichotomized the lung injury status based solely on the presence of sonographic sub-pleural consolidations. A “C-type” scanning profile, consisting of a LUS consolidation measuring over 4 cm in the largest diameter, was associated with higher rates of concurrently receiving a composite of high PEEP, high doses of inhaled NO, or prone positioning, regardless of illness severity. We believe this finding is thought-provoking and should be further studied on a larger scale with a controlled population. A proposed update to the global definition of ARDS included the use of ultrasound as an acceptable imaging modality [34], and the new 2023 European Society of Intensive Care Medicine guidelines on ARDS [35] explicitly call for simple, real-time, and rapid tests to aid in ARDS subphenotype classification in prospective studies. We posit, and feel that our results demonstrate, that this is a role that lung ultrasound is well suited for.

Our study has several limitations. It is a small and observational retrospective study, performed in a single center large academic medical ICU. Although a significant difference in the primary outcome between the two study groups was demonstrated, some of the separate individual components of the composite failed to reach statistical significance, likely due to the small sample size. While many different clinical factors go into the decision to prone patients, initiate pulmonary vasodilators, or use a high PEEP strategy, these clinical interventions comprising the composite primary outcome are all associated with a more severe ARDS illness course. Thus, the significant association with large sonographic subpleural consolidations still serves as an important finding, despite the limitations of using a composite measurement. Additionally, the single-center nature of our cohort limits generalizability and external validity. Our study was also not blinded, as the physicians who conducted the PLIS scans were the same treating physicians making decisions regarding patient management. However, the presence and size of consolidations during the PLIS scan were not considered in clinical decision-making due to the lack of clarity regarding how to appropriately translate LUS findings into practical clinical care, and thus the PLIS was conducted and recorded prospectively solely for research purposes. The observational nature of these findings does not allow any conclusions regarding causality and only suggests associations, while the ultimate goal would be to predict which subset of patients may respond to specific therapies or recruitment maneuvers. To this end, we recommend a prospective clinical investigation to further assess if the “C-type” phenotype has a relatively more favorable response to therapeutic interventions such as high PEEP, inhaled NO, or prone positioning.

Conclusions

The PLIS protocol is a simple and reproducible LUS tool that can characterize and phenotype COVID-19 ARDS patients requiring invasive mechanical ventilation based on the presence or absence of large sonographic sub-pleural lung consolidations, independent of clinical disease severity. Patients characterized with the “C-type” scanning profile, with large consolidations on ultrasound, were more likely to require advanced ARDS interventions as represented by a composite outcome of high PEEP, high dose of inhaled NO, or prone positioning. Further larger-scale studies are required to assess the causality of this relationship, its association with physiologic parameters like mechanical power and dead space, and its potential for targeted therapeutic interventions.

Supporting information

S1 Fig. The classic ultrasonographic lung findings in COVID-19 patients.

(TIF)

pone.0304508.s001.tif (1.7MB, tif)
S2 Fig. Areas of lung ultrasound scanning.

(TIF)

pone.0304508.s002.tif (1.9MB, tif)
S1 Table. The Point of Care Lung Ultrasound Injury Score (PLIS) grading system.

(DOCX)

pone.0304508.s003.docx (18KB, docx)
S2 Table. A comprehensive cohort data for each patient.

(DOCX)

pone.0304508.s004.docx (46.6KB, docx)

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

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

References

  • 1.Mallah SI, Ghorab OK, Al-Salmi S, Abdellatif OS, Tharmaratnam T, Iskandar MA, et al. COVID-19: breaking down a global health crisis. Ann Clin Microbiol Antimicrob. 2021;20:35. doi: 10.1186/s12941-021-00438-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Gao Z, Xu Y, Sun C, Wang X, Guo Y, Qiu S, et al. A systematic review of asymptomatic infections with COVID-19. J Microbiol Immunol Infect. 2021;54:12–16. doi: 10.1016/j.jmii.2020.05.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Rizzo AN, Aggarwal NR, Thompson BT, Schmidt EP. Advancing Precision Medicine for the Diagnosis and Treatment of Acute Respiratory Distress Syndrome. J Clin Med. 2023;12:1563. doi: 10.3390/jcm12041563 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Calfee CS, Delucchi K, Parsons PE, Thompson BT, Ware LB, Matthay MA, et al. Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials. Lancet Respir Med. 2014;2:611–20. doi: 10.1016/S2213-2600(14)70097-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Puybasset L, Cluzel P, Gusman P, Grenier P, Preteux F, Rouby JJ. Regional distribution of gas and tissue in acute respiratory distress syndrome. I. Consequences for lung morphology. Intensive Care Med. 2000;26:857–69. [DOI] [PubMed] [Google Scholar]
  • 6.Reilly JP, Calfee CS, Christie JD. Acute Respiratory Distress Syndrome Phenotypes. Semin Respir Crit Care Med. 2019;40:19–30. doi: 10.1055/s-0039-1684049 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Rouby JJ, Puybasset L, Cluzel P, Richecoeur J, Lu Q, Grenier P. Regional distribution of gas and tissue in acute respiratory distress syndrome. II. Physiological correlations and definition of an ARDS severity score. Intensive Care Med. 2000;26:1046–56. [DOI] [PubMed] [Google Scholar]
  • 8.Mrozek S, Jabaudon M, Jaber S, Paugam-Burtz C, Lefrant JY, Rouby JJ, et al. Elevated Plasma Levels of sRAGE Are Associated With Nonfocal CT-Based Lung Imaging in Patients With ARDS: A Prospective Multicenter Study. Chest. 2016;150:998–1007. doi: 10.1016/j.chest.2016.03.016 [DOI] [PubMed] [Google Scholar]
  • 9.Constantin JM, Grasso S, Chanques G, Aufort S, Futier E, Sebbane M, et al. Lung morphology predicts response to recruitment maneuver in patients with acute respiratory distress syndrome. Crit Care Med. 2010;38:1108–17. doi: 10.1097/CCM.0b013e3181d451ec [DOI] [PubMed] [Google Scholar]
  • 10.Constantin JM, Jabaudon M, Lefrant JY, Jaber S, Quenot JP, Langeron O, et al. Personalised mechanical ventilation tailored to lung morphology versus low positive end-expiratory pressure for patients with acute respiratory distress syndrome in France (the LIVE study): a multicentre, single-blind, randomised controlled trial. Lancet Respir Med. 2019;7:870–880. doi: 10.1016/S2213-2600(19)30138-9 [DOI] [PubMed] [Google Scholar]
  • 11.Goligher EC, Telias I, Sahetya SK, Baedorf-Kassis E, Patel BK, Yehya N, et al. Physiology Is Vital to Precision Medicine in Acute Respiratory Distress Syndrome and Sepsis. Am J Respir Crit Care Med. 2022;206:14–16. doi: 10.1164/rccm.202202-0230ED [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Xiao J, Li X, Xie Y, Huang Z, Ding Y, Zhao S, et al. Maximum chest CT score is associated with progression to severe illness in patients with COVID-19: a retrospective study from Wuhan, China. BMC Infect Dis. 2020;20:953. doi: 10.1186/s12879-020-05683-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Danish M, Agarwal A, Goyal P, Gupta D, Lal H, Prasad R, et al. Diagnostic performance of 6-point lung ultrasound in ICU patients: A comparison with chest X-ray and CT thorax. Turk J Anaesthesiol Reanim. 2019;47:307–319. doi: 10.5152/TJAR.2019.73603 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Pare JR, Camelo I, Mayo KC, Leo MM, Dugas JN, Nelson KP, et al. Point-of-care lung ultrasound is more sensitive than chest radiograph for evaluation of COVID-19. West J Emerg Med. 2020;21:771–778. doi: 10.5811/westjem.2020.5.47743 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Zieleskiewicz L, Markarian T, Lopez A, Taguet C, Mohammedi N, Boucekine M, et al. Comparative study of lung ultrasound and chest computed tomography scan in the assessment of severity of confirmed COVID-19 pneumonia. Intensive Care Med. 2020;46:1707–1713. doi: 10.1007/s00134-020-06186-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Vetrugno L, Baciarello M, Bignami E, Bonetti A, Saturno F, Orso D, et al. The “pandemic” increase in lung ultrasound use in response to Covid-19: can we complement computed tomography findings? A narrative review. Ultrasound J. 2020;12:39. doi: 10.1186/s13089-020-00185-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Smith MJ, Hayward SA, Innes SM, Miller ASC. Point-of-care lung ultrasound in patients with COVID-19 –a narrative review. Anaesthesia. 2020;75:1096–1104. doi: 10.1111/anae.15082 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Bonadia N, Carnicelli A, Piano A, Buonsenso D, Gilardi E, Kadhim C, et al. Lung Ultrasound Findings Are Associated with Mortality and Need for Intensive Care Admission in COVID-19 Patients Evaluated in the Emergency Department. Ultrasound Med Biol. 2020;46:2927–2937. doi: 10.1016/j.ultrasmedbio.2020.07.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Trias-Sabrià P, Molina-Molina M, Aso S, Argudo MH, Diez-Ferrer M, Sabater J, et al. Lung ultrasound score to predict outcomes in COVID-19. Respir Care. 2021;66:1263–1270. doi: 10.4187/respcare.08648 [DOI] [PubMed] [Google Scholar]
  • 20.de Alencar JCG, Marchini JFM, Marino LO, da Costa Ribeiro SC, Bueno CG, da Cunha VP, et al. Lung ultrasound score predicts outcomes in COVID-19 patients admitted to the emergency department. Ann Intensive Care. 2021;11:6. doi: 10.1186/s13613-020-00799-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Bitar ZI, Shamsah M, Maadarani O, Bamasood OM, Bitar AZ, Alfoudri H. Lung Ultrasound and Sonographic Subpleural Consolidation in COVID-19 Pneumonia Correlate with Disease Severity. Crit Care Res Pract. 2021;2021:6695033. doi: 10.1155/2021/6695033 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Sapienza LG, Nasra K, Calsavara VF, Little TB, Narayana V, Abu-Isa E. Risk of in-hospital death associated with Covid-19 lung consolidations on chest computed tomography–A novel translational approach using a radiation oncology contour software. Eur J Radiol Open. 2021;8:100322. doi: 10.1016/j.ejro.2021.100322 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Fuchs L, Galante O, Almog Y, Dayan RR, Smoliakov A, Ullman Y, et al. Point of Care Lung Ultrasound Injury Score—A simple and reliable assessment tool in COVID-19 patients (PLIS I): A retrospective study. PLoS One. 2022;17:e0267506 doi: 10.1371/journal.pone.0267506 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Ranieri VM, Rubenfeld GD, Thompson BT, Ferguson ND, Caldwell E, Fan E, et al. Acute respiratory distress syndrome: The Berlin definition. JAMA. 2012;307:2526–33. doi: 10.1001/jama.2012.5669 [DOI] [PubMed] [Google Scholar]
  • 25.Verscheure S, Massion PB, Verschuren F, Damas P, Magder S. Volumetric capnography: Lessons from the past and current clinical applications. Crit Care. 2016;20:184. doi: 10.1186/s13054-016-1377-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Gattinoni L, Chiumello D, Caironi P, Busana M, Romitti F, Brazzi L, et al. COVID-19 pneumonia: different respiratory treatments for different phenotypes? Intensive Care Med. 2020;46:1099–1102. doi: 10.1007/s00134-020-06033-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Fusina F, Albani F, Crisci S, Morandi A, Tansini F, Beschi R, et al. Respiratory system compliance at the same PEEP level is similar in COVID and non-COVID ARDS. Respir Res. 2022;23:7. doi: 10.1186/s12931-022-01930-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Sinha P, Furfaro D, Cummings MJ, Abrams D, Delucchi K, Maddali MV, et al. Latent class analysis reveals COVID-19-related acute respiratory distress syndrome subgroups with differential responses to corticosteroids. Am J Respir Crit Care Med. 2021;204:1274–1285. doi: 10.1164/rccm.202105-1302OC [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Bos LDJ, Sjoding M, Sinha P, Bhavani SV, Lyons PG, Bewley AF, et al. Longitudinal respiratory subphenotypes in patients with COVID-19-related acute respiratory distress syndrome: results from three observational cohorts. Lancet Respir Med. 2021;9:1377–1386. doi: 10.1016/S2213-2600(21)00365-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Wang XT, Ding X, Zhang HM, Chen H, Su LX, Liu DW, et al. Lung ultrasound can be used to predict the potential of prone positioning and assess prognosis in patients with acute respiratory distress syndrome. Crit Care. 2016;20:385. doi: 10.1186/s13054-016-1558-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Avdeev SN, Nekludova GV, Trushenko NV, Tsareva NA, Yaroshetskiy AI, Kosanovic D. Lung ultrasound can predict response to the prone position in awake non-intubated patients with COVID 19 associated acute respiratory distress syndrome. Crit Care. 2021;25:35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Bouhemad B, Brisson H, Le-Guen M, Arbelot C, Lu Q, Rouby JJ. Bedside ultrasound assessment of positive end-expiratory pressure-induced lung recruitment. Am J Respir Crit Care Med. 2011;183:341–7. doi: 10.1164/rccm.201003-0369OC [DOI] [PubMed] [Google Scholar]
  • 33.Lichter Y, Topilsky Y, Taieb P, Banai A, Hochstadt A, Merdler I, et al. Lung ultrasound predicts clinical course and outcomes in COVID-19 patients. Intensive Care Med. 2020;46:1873–1883. doi: 10.1007/s00134-020-06212-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Matthay MA, Arabi Y, Arroliga AC, Bernard GR, Bersten AD, Brochard LJ, et al. A New Global Definition of Acute Respiratory Distress Syndrome. Am J Respir Crit Care Med. 2023;207:A6229. Available from: www.atsjournals.org [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Grasselli G, Calfee CS, Camporota L, Poole D, Amato MBP, Antonelli M, et al. ESICM guidelines on acute respiratory distress syndrome: definition, phenotyping and respiratory support strategies. Intensive Care Med. 2023;49:727–759. doi: 10.1007/s00134-023-07050-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

Decision Letter 0

Roberta Ribeiro De Santis Santiago

13 Nov 2023

PONE-D-23-24480Lung ultrasound is associated with distinct clinical phenotypes in COVID-19 ARDS: A retrospective observational studyPLOS ONE

Dear Dr. Dayan,

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.

Three experts in the subject matter reviewed your paper. Although the reviewers noted the importance of the topic, they expressed major concerns about the manuscript.

The authors performed a retrospective study involving 23 patients with COVID-19-related ARDS, proposing lung ultrasound findings as an imaging marker for ARDS phenotyping. The manuscript is well-written and organized. The reviewers emphasized the authors' work of performing multiple scans and analyzing the images and the role lung imaging can play in ARDS phenotyping.

A common concern among reviewers was the lack of details about the criteria/methods for patient selection, imaging scores, and scans included in the analysis since multiple measurements were performed for each enrolled patient. In addition, there is a need for more clarification about the statistical approach used for the repeated measurement. Finally, I'd like to point out that an essential observation addressed is the limitation of a composite outcome formed by a combination of interventions, and it should be addressed more in-depth throughout the manuscript.

I look forward to your revision.Please ensure that your decision is justified on PLOS ONE’s publication criteria and not, for example, on novelty or perceived impact.

For Lab, Study and Registered Report Protocols: These article types are not expected to include results but may include pilot data. 

==============================

Please submit your revised manuscript by Dec 28 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Roberta Ribeiro De Santis Santiago, M.D., Ph.D., R.R.T.

Academic Editor

PLOS ONE

Journal requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf.

2. Did you know that depositing data in a repository is associated with up to a 25% citation advantage (https://doi.org/10.1371/journal.pone.0230416)? If you’ve not already done so, consider depositing your raw data in a repository to ensure your work is read, appreciated and cited by the largest possible audience. You’ll also earn an Accessible Data icon on your published paper if you deposit your data in any participating repository (https://plos.org/open-science/open-data/#accessible-data).

3. Thank you for stating the following in the Competing Interests section:

“I have read the journal's policy and the authors of this manuscript have the following competing interests: Lior Fuchs is a consultant of General Electric Healthcare. All other authors have no conflicts of interest to declare.”

We note that one or more of the authors are employed by a commercial company: General Electric Healthcare

a.        Please provide an amended Funding Statement declaring this commercial affiliation, as well as a statement regarding the Role of Funders in your study. If the funding organization did not play a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript and only provided financial support in the form of authors' salaries and/or research materials, please review your statements relating to the author contributions, and ensure you have specifically and accurately indicated the role(s) that these authors had in your study. You can update author roles in the Author Contributions section of the online submission form.

Please also include the following statement within your amended Funding Statement.

“The funder provided support in the form of salaries for authors [insert relevant initials], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.”

If your commercial affiliation did play a role in your study, please state and explain this role within your updated Funding Statement.

b. Please also provide an updated Competing Interests Statement declaring this commercial affiliation along with any other relevant declarations relating to employment, consultancy, patents, products in development, or marketed products, etc. 

Within your Competing Interests Statement, please confirm that this commercial affiliation does not alter your adherence to all PLOS ONE policies on sharing data and materials by including the following statement: "This does not alter our adherence to  PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests) . If this adherence statement is not accurate and  there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.

Please include both an updated Funding Statement and Competing Interests Statement in your cover letter. We will change the online submission form on your behalf.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: I Don't Know

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Roy Rafael Dayan, M.D., and colleagues investigate the utility of lung ultrasound (using a previously published scoring system) in distinguishing clinical phenotypes among patients with ARDS caused by COVID-19 and its associations with clinical outcomes.

The text is well written, however I have some mayor andminor recommendations

Mayor reviews:

# Multiple evaluations of LUS

-It is not clear from which point of the patient´s history the authors defined the main score of each patient. So, the final classification of each patient came from the first evaluation, maximum score, etc?

- How was the multivariable model fit? Using repeated measures? Please, clarify.

- How can a clinician know which profile a patient has? For instance, a patient score B, B, and C? or B-C-C?

Minor reviews:

-This reviewer believes that the introduction is too large. It will be better to condense the introduction to provide a clear and concise overview of your study objectives. You will expand upon the detailed information in the discussion section.

Reviewer #2: Major Comments

-Overall, this study is well-written and organized. The Discussion in particular provides a thorough summary of existing literature and ties in the study findings nicely. I also commend the authors on performing the arduous task of performing and interpreting serial lung ultrasound examinations. However, there are major flaws with the study design that would need to be addressed.

-The author’s primary outcome is heavily flawed. The stated objective of this study was to investigate whether the presence of large consolidation on lung ultrasound alone was predictive of outcomes among COVID-19 ARDS patients. However, the primary outcome was not a measure of patient outcomes (ie. duration of mechanical ventilation, duration of ICU stay, mortality) but instead a composite of whether the patient required proning, high PEEP, or inhaled pulmonary vasodilator. The decision to employ one of these interventions is heavily biased by the treating physician and is often related to the patient’s underlying comorbidities rather than simply the severity or type of ARDS. For example, an obese patient would necessitate high PEEP regardless of the presence or severity of ARDS to facilitate alveolar recruitment and minimize atelectasis, while a patient with pulmonary hypertension may require an inhaled pulmonary vasodilator even with very mild ARDS. The combination of these 3 very different interventions into a composite outcome further weakens the study findings, as stated in the Discussion (Lines 281 – 284).

-Phenotyping in ARDS has typically referred to the underlying molecular mechanisms involved in the lung damage, based on local and systemic biomarkers, and degree of inflammation. Here, the authors instead use the term phenotype to describe whether or not the patient had large consolidations on lung ultrasound. The use of “phenotyping” in this manuscript is misleading and should be avoided or specified as “sonographic phenotyping”, as the presence of consolidation does not constitute a molecular phenotype but simply describes an imaging finding.

- In the methods, the authors state (line 139-140): " A single PLIS scan per patient composed the unit used for analysis”. This seems to be incorrect, as 128 data points (47 B-type and 81 C-type) scans were included in the results. Please clarify. If a single scan was used for each patient, please describe which scan was selected for analysis and how this selection was justified.

-The patients performed serial ultrasound examinations on each patient, which provides a robust data set when looking at each individual patient longitudinally (as shown in Figure 1) but allows for confounding if treating each scan as a separate data point, as they appear to be.

-Figure 1 is very well designed and formatted to capture the clinical courses of these patients. However, the conclusion that is drawn from this data seems contrary to the author’s main conclusion, showing that the non-survivors tended to develop consolidations while the survivors tended to have isolated B-lines without consolidation. This would imply that consolidations are associated with more severe disease, which could very well be true and this study was simply underpowered and not properly designed to detect this.

Minor Comments

-Lines 23, 32: please avoid or define non-standard abbreviations in the abstract, including “PLIS” and “LUS”

-Lines 31, 130: please use appropriate capitalization and subscript for “PaO2/FiO2 ratio”

-Line 42: the authors should rephrase “asymptomatic carriage”; could simply say “asymptomatic”

-Lines 44-45: I would argue against the description of COVID-19 as “ambiguous clinical presentation”. Rather, these patients routinely present with symptoms of dyspnea and increased work of breathing. Instead, I would describe how these patients often present similarly but early in their course it can be difficult to differentiate those who will progress to severe disease.

-Line 53: use distinct rather than distinctive here

-Line 54: I believe you mean restrictive fluid strategies (rather than liberal), as liberal use of fluids is not a therapeutic intervention in ARDS

-Line 66: insert comma after COVID-19. Also, this sentence needs to be shorted.

-Line 71: This should be a new sentence (after reference 18).

-Line 78: intensive care unit should not be capitalized

-Table 1: please reformat as the current formatting of data is confusing. Continuous data (mean ± SD) should be written as such. For example, age (years) should be written as 65.3 ± 11.9 rather than 65.3 (11.9). Non-continuous data should be written, for example for males, as 16 (69.9%) and specified as n (%) rather than n, %.

-Line 157: POCUS is used as an abbreviation and has not yet been defined.

Reviewer #3: It was a pleasure for me to read your manuscript and your previous work on the PLIS scanning protocol. I am personally a big fan of this thought process, and in general, I am an advocate for bedside phenotyping of ARDS. I suggest the methods to be explained a little bit more in detail in terms of patient selection. I sense that a certain amount of patients admitted to your center were screened, and that only patients that had "enough" scans were considered for the composite outcome. In my mind, it should be explained more clearly who was screened, and hence what were the inclusion and the exclusion criteria (I see ECMO clearly stated). Table 2 should have driving pressure, and tidal volume per kg of IBW among the variables. I like the concept of Figure 3, but if this is a study on 23 patients, I think they should all be presented instead of 10, either as supplemental material or in the main manuscript if physically possible. The choice for advanced ARDS interventions mentioned in the composite outcome seem to correlate with the C-phenotype more than oxygenation. But it is oxygenation what normally clinically drives these interventions. It makes me wonder whether in your center you include ultrasound evaluation to back up those decisions at rounds. I guess it could make sense in the setting of widespread ultrasound use and proficiency. Also, with this being a retrospective study, I imagine that there is a chance that the arterial blood gases do not always match the scans. These are all aspects that should be covered in the methods, in the discussion and in the conclusion. Finally, I would add a supplementary table about the advanced interventions with the PaO2/FiO2 ratio at the moment when the advanced intervention were started, what was the PLIS score that day, the group B vs C the patients "belonged to" that day, the average daily score from admission to advanced intervention, and the average daily score from intubation to advanced intervention, if data is available.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Raffaele Di Fenza

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Attachment

Submitted filename: Comments to Author.docx

pone.0304508.s005.docx (17.9KB, docx)
PLoS One. 2024 Jun 3;19(6):e0304508. doi: 10.1371/journal.pone.0304508.r002

Author response to Decision Letter 0


24 Dec 2023

Dear PLOS One Editorial and Reviewing Team,

Dear PLOS One Editorial and Reviewing Team,

We are writing to express our sincere gratitude for the time and effort you invested in reviewing our manuscript. We value your insightful comments and suggestions, which have significantly contributed to improving the quality of our work.

We have carefully considered all of your feedback and have incorporated them into the revised manuscript. We have addressed each comment point-by-point in a separate document, which we have attached for your reference. We believe that the revised manuscript is now more complete.

We are pleased to present the revised manuscript to you for your further consideration. We are confident that it addresses all of your concerns and meets the high standards of PLOS One.

We appreciate your expertise and dedication to publishing high-quality research. We look forward to your feedback on the revised manuscript.

Thank you again for your time and consideration.

Sincerely,

Roy Rafael Dayan

Attachment

Submitted filename: PLIS2_Revision Letter.docx

pone.0304508.s006.docx (29.6KB, docx)

Decision Letter 1

Francesca Pennati

13 Feb 2024

PONE-D-23-24480R1Lung ultrasound is associated with distinct clinical phenotypes in COVID-19 ARDS: A retrospective observational studyPLOS ONE

Dear Dr. Dayan,

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.

Although the reviewers acknowledged the improvement of the manuscript, there are still some issues. In particular, the manuscript should report more details about the ultrasound evaluation. Also, a more concise introduction would improve the manuscript.

Please submit your revised manuscript by Mar 29 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Francesca Pennati, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

According to the second reviewer, more details about the ultrasound evaluation should be provided. Also, a more concise introduction would improve the manuscript.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #3: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #3: (No Response)

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Roy Rafael Dayan et al. submitted a paper presenting retrospective data on the efficacy of lung ultrasound in identifying distinct clinical phenotypes in COVID-19 ARDS, each with unique outcomes.

Major comments:

* The authors propose that patients may exhibit various phenotypes throughout their clinical course. However, the analysis of outcomes associated with phenotypes C and B appears to represent two distinct populations. It remains unclear at which point in the patients' clinical history the lung ultrasound (LUS) was conducted and when a patient was classified as having phenotype C or B.

* Although the group refers to a previous ultrasound score, providing a more detailed explanation of the ultrasound evaluation would enhance clarity. Specifically, it would be helpful to elaborate on which part of the thorax was assessed. For instance, determining whether the dorsal region, where larger consolidations are typically found, can be reliably assessed by ultrasound, especially in patients in the prone position, would be valuable. This aspect is crucial to the methodology and limitations, as an inability to evaluate a certain thoracic region via ultrasound may lead to a potential underestimation of the phenotype.

Minor Comments:

* The introduction is lengthy; it would benefit from being more concise. To achieve this, consider avoiding the repetition of studies and concepts already discussed in the subsequent sections.

Reviewer #3: Thank you for resubmitting. Thank you for clarifying the inclusion/exclusion criteria in your dataset. I agree that oxygenation should be only one small part of what triggers interventions, which is why I was hoping for more data regarding protective ventilation. But I appreciate your clarifications about the method and how hypothesis were generated.

US can complement CXR to quickly photograph patients that have less homogeneously ventilated lungs, shunt more, and trigger specific treatments. Please, keep up: an ultrasound-trained generation of intensivists is expected to multiply the number of patients and observations, correlate with other imaging techniques and patient's respiratory mechanics.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #3: Yes: Raffaele Di Fenza

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2024 Jun 3;19(6):e0304508. doi: 10.1371/journal.pone.0304508.r004

Author response to Decision Letter 1


16 Mar 2024

Please see the attached "Response to Reviewers" for a point-by-point response to the reviewers’ comments and concerns.

Sincerely,

Dr. Roy Rafael Dayan

Attachment

Submitted filename: PLOS One- Response to Reviewers - March2024.docx

pone.0304508.s007.docx (22.6KB, docx)

Decision Letter 2

Francesca Pennati

14 May 2024

Lung ultrasound is associated with distinct clinical phenotypes in COVID-19 ARDS: A retrospective observational study

PONE-D-23-24480R2

Dear Dr. Dayan,

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.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Francesca Pennati, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Francesca Pennati

25 May 2024

PONE-D-23-24480R2

PLOS ONE

Dear Dr. Dayan,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Francesca Pennati

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. The classic ultrasonographic lung findings in COVID-19 patients.

    (TIF)

    pone.0304508.s001.tif (1.7MB, tif)
    S2 Fig. Areas of lung ultrasound scanning.

    (TIF)

    pone.0304508.s002.tif (1.9MB, tif)
    S1 Table. The Point of Care Lung Ultrasound Injury Score (PLIS) grading system.

    (DOCX)

    pone.0304508.s003.docx (18KB, docx)
    S2 Table. A comprehensive cohort data for each patient.

    (DOCX)

    pone.0304508.s004.docx (46.6KB, docx)
    Attachment

    Submitted filename: Comments to Author.docx

    pone.0304508.s005.docx (17.9KB, docx)
    Attachment

    Submitted filename: PLIS2_Revision Letter.docx

    pone.0304508.s006.docx (29.6KB, docx)
    Attachment

    Submitted filename: PLOS One- Response to Reviewers - March2024.docx

    pone.0304508.s007.docx (22.6KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.


    Articles from PLOS ONE are provided here courtesy of PLOS

    RESOURCES