Papamichalis P, Oikonomou KG, Xanthoudaki M, Papathanasiou SK, Papadogoulas A, Skoura AL, Valsamaki A, Plageras D, Papamichalis M, Katsiafylloudis P, Papapostolou E, Mantzarlis K, Koukoulis A, Mavrommati G, Giannakos P, Chovas A. Length of stay, duration of mechanical ventilation, mortality, and acute kidney injury in acute respiratory failure requiring endotracheal intubation. World J Crit Care Med 2025; 14(4): 103708 [DOI: 10.5492/wjccm.v14.i4.103708]
Corresponding Author of This Article
Panagiotis Papamichalis, MD, PhD, Intensive Care Unit, General Hospital of Larissa, 1 Tsakalof, Larissa 41221, Thessaly, Greece. ppapamih@med.uth.gr
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Critical Care Medicine
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Retrospective Cohort Study
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Dec 9, 2025 (publication date) through Dec 9, 2025
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World Journal of Critical Care Medicine
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Papamichalis P, Oikonomou KG, Xanthoudaki M, Papathanasiou SK, Papadogoulas A, Skoura AL, Valsamaki A, Plageras D, Papamichalis M, Katsiafylloudis P, Papapostolou E, Mantzarlis K, Koukoulis A, Mavrommati G, Giannakos P, Chovas A. Length of stay, duration of mechanical ventilation, mortality, and acute kidney injury in acute respiratory failure requiring endotracheal intubation. World J Crit Care Med 2025; 14(4): 103708 [DOI: 10.5492/wjccm.v14.i4.103708]
Panagiotis Papamichalis, Katerina G Oikonomou, Maria Xanthoudaki, Antonios Papadogoulas, Periklis Katsiafylloudis, Evangelia Papapostolou, Achilleas Chovas, Intensive Care Unit, General Hospital of Larissa, Larissa 41221, Thessaly, Greece
Sophia K Papathanasiou, Dimitrios Plageras, Gkreta Mavrommati, Department of Internal Medicine, General Hospital of Larissa, Larissa 41221, Thessaly, Greece
Apostolia Lemonia Skoura, Department of Transfusion Medicine, University Hospital of Larissa, Larissa 41110, Thessaly, Greece
Asimina Valsamaki, Konstantinos Mantzarlis, Department of Critical Care, University Hospital of Larissa, Larissa 41110, Thessaly, Greece
Michail Papamichalis, Department of Cardiology, University Hospital of Larissa, Larissa 41110, Thessaly, Greece
Athanasios Koukoulis, Faculty of Medicine, University of Thessaly, Larissa 41500, Thessaly, Greece
Panagiotis Giannakos, Department of Cardiology, General Hospital of Larissa, Larissa 41221, Thessaly, Greece
Author contributions: Papamichalis P, Oikonomou KG, Xanthoudaki M, and Papathanasiou SK designed the article; Papadogoulas A, Valsamaki A, Skoura AL, Katsiafylloudis P, Papapostolou E, Plageras D, Koukoulis A, Mavrommati G, Giannakos P, and Mantzarlis K assisted in data gathering; Papamichalis P, Oikonomou KG, Xanthoudaki M, and Papathanasiou SK wrote the final version of the manuscript; Oikonomou KG performed English editing; Chovas A critically reviewed the paper; all authors approved the final version to publish.
Institutional review board statement: The study was approved by the institutional review board of General Hospital of Larissa, No. 4851.
Informed consent statement: Due to the retrospective nature of the study and in accordance with the Institutional review board statement, informed consent statement was waived.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Data sharing statement: Data that support the findings of this study will be available upon request at the e-mail address of the corresponding author for research purposes.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Panagiotis Papamichalis, MD, PhD, Intensive Care Unit, General Hospital of Larissa, 1 Tsakalof, Larissa 41221, Thessaly, Greece. ppapamih@med.uth.gr
Received: November 29, 2024 Revised: April 28, 2025 Accepted: July 7, 2025 Published online: December 9, 2025 Processing time: 365 Days and 5.2 Hours
Abstract
BACKGROUND
Critically ill patients often present on admission or develop acute respiratory failure requiring intubation and application of positive pressure ventilation during their hospital stay.
AIM
To investigate and identify the epidemiological data, parameters associated with respiratory settings or the mechanics, and values related to arterial blood gases (ABGs) that are associated with outcomes in critically ill patients.
METHODS
A retrospective analysis of 131 patients [mean age, 67.3 years; mean acute physiology and chronic health evaluation (APACHE) score, 21.4] with acute respiratory failure requiring invasive mechanical ventilation was performed. The parameters that were statistically analyzed included demographic data, the presence of comorbidities, the presence of coronavirus disease 19 (COVID-19), the respiratory rate (RR), peak airway pressure (Ppeak), minute ventilation (MV), positive end-expiratory pressure, and the values related to ABGs. In order to facilitate the statistical analysis, patients were evaluated and compared in groups: Survivors (n = 41) vs non-survivors (n = 90) and patients without acute kidney injury (AKI) (n = 60) vs patients with AKI (n = 71). Four endpoints were studied: Mortality, length of stay, duration of mechanical ventilation, and AKI. Group comparisons were performed using the following statistical tests: The χ2 test with Yates’ correction, Fisher’s exact test, the Mann-Whitney U test, and Spearman’s rank correlation analysis. Binary logistic regression analysis conducted after the univariate statistical tests facilitated the investigation of the independent predictors of mortality and AKI. A two-sided P value of less than 0.05 was considered the threshold of statistical significance.
RESULTS
Non-survivors presented statistically significant differences in terms of being older in age, the presence of comorbidities, elevated APACHE score, medical (vs surgical) reasons for admission, presence of COVID-19, lower pH at ABGs, lower values of the oxygenation ratio (arterial oxygen partial pressure to the fraction of inspired oxygen) and arterial oxygen partial pressure, and elevated values of Ppeak, positive end-expiratory pressure, RR, arterial carbon dioxide partial pressure, and MV. The factors identified as independent predictors of mortality were the presence of comorbidities, APACHE score, COVID-19 status, arterial carbon dioxide partial pressure, Ppeak, RR, and MV. COVID-19 presence and elevated values of RR and Ppeak were positively correlated with the other three endpoints (length of stay, the duration of mechanical ventilation in survivors, and the occurrence of AKI in the entire study population) that were studied. The other parameters exhibited a variable (either positive/negative, or no) correlation to the four endpoints under investigation.
CONCLUSION
Among all investigated outcome measures, COVID-19, Ppeak, and RR were strongly associated with all the endpoints studied, suggesting that proper interventions involving the modifiable respiratory parameters Ppeak and RR could improve the overall outcome in these patients. A novel finding of this study was the relationship between RR and AKI, which is worthy of further investigation. Future studies may explore the clinical interpretation of these findings to improve outcomes in critically ill patients with acute respiratory failure.
Core Tip: Identifying prognostic factors in patients with acute respiratory failure requiring invasive mechanical/positive pressure ventilation remains a challenge to date. In the present study, the relationships of the epidemiological, respiratory, and arterial blood gas parameters to the four outcome measures of mortality, development of acute kidney injury, length of stay, and the duration of mechanical ventilation were evaluated. It was revealed that epidemiological factors such as the coronavirus disease 2019 presence and the respiratory parameters peak airway pressure and respiratory rate (RR) affected all the studied outcome measures. The possibility of improving outcomes by reducing the peak airway pressure and the RR and the observed association between RR and acute kidney injury needs further evaluation in future studies.
Citation: Papamichalis P, Oikonomou KG, Xanthoudaki M, Papathanasiou SK, Papadogoulas A, Skoura AL, Valsamaki A, Plageras D, Papamichalis M, Katsiafylloudis P, Papapostolou E, Mantzarlis K, Koukoulis A, Mavrommati G, Giannakos P, Chovas A. Length of stay, duration of mechanical ventilation, mortality, and acute kidney injury in acute respiratory failure requiring endotracheal intubation. World J Crit Care Med 2025; 14(4): 103708
Mechanical ventilation provided through endotracheal intubation represents one of the most advanced means of providing life and respiratory support to critically ill patients[1]. According to the World Health Organization, every year, 3 million patients develop acute respiratory distress syndrome (ARDS) worldwide, and the new definition of ARDS is expected to increase its detection rates owing to the increased sensitivity (prevalence on admission is 21.2% according to the Berlin definition, while that according to the new global definition of ARDS is 35.2%)[2,3]. When acute respiratory failure occurs and a course of non-invasive systems (usually high-flow nasal cannula and/or non-invasive mechanical ventilation) fails to provide adequate support to the patient, intubation and positive-pressure ventilation are needed[4,5]. In the case of patients with as well as those without ARDS, invasive ventilatory support has been delivered with more precision over the last few decades, mainly through the application of protective ventilation strategies [lower tidal volume (VT) targeting 4-6 mL/kg of predicted body weight (PBW), lower values of driving pressure (ΔP) targeting ≤ 15 cmH2O, lower values of plateau pressure (Pplat) targeting ≤ 30 cmH2O, and proper (≥ 5 cmH2O) values of positive end-expiratory pressure (PEEP), e.g., 2 cmH2O higher than the lower inflection point of the pressure-volume curve][6-8]. Metanalyses involving large, multicenter, cohort studies identified potentially modifiable factors that may be associated with worse survival outcomes, in both ARDS patients [lower PEEP, higher peak airway pressure (Ppeak), higher Pplat, higher ΔP, and increased respiratory rate (RR)] and non-ARDS patients (higher maximum airway pressure)[9,10]. However, these studies have not elucidated the impact of these parameters on patient survival rates: whether the modification of these parameters improves the survival rates or whether these parameters are just markers of more severe respiratory failure and increased disease severity remains to be understood[9-11]. On the basis of the abovementioned information, this study aimed to evaluate the prognostic value of epidemiological data, parameters of respiratory mechanics, and values related to arterial blood gases (ABGs) in a cohort of patients with acute respiratory failure requiring intubation, in relation to multiple endpoints.
MATERIALS AND METHODS
Study design
The medical records of 131 patients, who were included in this study based on the criteria of age > 18 years and acute respiratory failure that required invasive mechanical ventilation, regardless of the presence or absence of ARDS, were analyzed retrospectively. The patients had been admitted to the intensive care unit (ICU) of the General Hospital of Larissa over a 4-year period (2020-2023), where they received appropriate medical treatment, which was based on the cause of respiratory failure; e.g., for coronavirus disease 19 (COVID-19) prone position, immunosuppression and antiviral therapy were applied in accordance with the protocols of the World Health Organization; for pneumonia, antibiotics were administered in accordance with the international guidelines for infectious diseases; for extrapulmonary ARDS, etiologic therapy, and for cardiogenic pulmonary edema, diuretics were administered. Exclusion criteria for this retrospective enrollment were as follows: Inability to retrieve the requisite data, intubation for reasons other than acute respiratory failure (e.g., due to inability to maintain airway patency or to protect the airway against aspiration), and death within 24 hours after applying the intubation (moribund patients). Epidemiological data were collected at the time of patients’ admission, whereas the respiratory parameters and values related to ABGs were obtained within 24 hours after applying intubation, at the timepoint of patients’ worst oxygenation ratio [lowest ratio of arterial oxygen partial pressure (PaO2, mmHg) to the fraction of inspired oxygen (FiO2), lowest PaO2/FiO2 value, mmHg]. This study was approved by the institutional review board of the General Hospital of Larissa, No. 4851.
COVID-19 was diagnosed based on the results of reverse-transcriptase polymerase chain reaction for detection of the viral load after proper naso- and oropharyngeal sampling, considering the presence of consistent clinical presentation and computed tomography imaging[12]. The presence of comorbidities, including diabetes mellitus, chronic obstructive pulmonary disease, immunosuppression, coronary disease, heart failure, and chronic renal failure, was considered positive when 1 comorbidity was reported in the patient’s medical history. The term “medical reason for admission” included the admission of any patient who did not have any operating room charge or a surgical procedure code or who did not belong to a surgical diagnosis-related group.
Statistical analysis was conducted based on the analysis of demographic data, comorbidities, the diagnosis of COVID-19, respiratory parameters, including RR (breaths/minute), Ppeak (cmH2O), PEEP (cmH2O), and minute ventilation (MV, L), and ABGs, including arterial lactate levels (mmol/L), arterial blood pH, PaO2, arterial carbon dioxide partial pressure (PaCO2, mmHg), and PaO2/FiO2. VT, which was used for the calculation of MV (MV = VT × RR), was excluded from further analysis because of the lack of available data required for estimating the PBW and then calculating the mL of VT/kg PBW, which is used in all studies that investigate the relationship of VT with outcomes.
Four endpoints were investigated: Mortality, acute kidney injury (AKI), length of stay (LOS), and duration of mechanical ventilation. These four outcomes were used to evaluate the impacts of critical illness and acute respiratory failure on patients’ status, both of which cause synergistic compromise, and to determine the possible effects on the overall outcome when epidemiological and respiratory parameters are altered. In order to facilitate the statistical analysis, patients were evaluated and compared in groups: Survivors [S, absolute number (n) = 41] vs non-survivors (NA, n = 90), to identify the factors associated with patient survival, and patients without the occurrence of AKI (NA, n = 60) vs patients who developed AKI (according to Kidney Disease Improving Global Outcomes recent criteria[13]) (A, n = 71), to identify the factors that potentially lead to AKI. Parameters influencing the LOS and duration of mechanical ventilation were analyzed in the 41 patients who were discharged alive from the ICU, in accordance with the relevant statistical suggestions[14].
Statistical analysis
Statistical analysis was performed using the SPSS version 26 package (IBM Corp., Armonk, NY, United States). The results were expressed as mean ± SE or n (%), as applicable. The data were analyzed using the χ2 test with Yates’ correction, Fisher’s exact test, the Mann-Whitney U test, and Spearman’s rank correlation (correlation coefficient, r) analysis, as applicable. The variables significant in the univariate analysis were incorporated into the binary logistic regression model. A two-sided P value of less than 0.05 was used as the threshold of statistical significance.
RESULTS
The relevant demographic and epidemiological characteristics of the whole study population are presented in Table 1. In terms of patient survival, after comparison of the relative variables, it was revealed that the following parameters were positively correlated to increased mortality (Table 2): Older age (S: 61.8 ± 2.7, and NS: 70 ± 1.2, years; P = 0.009); the presence of comorbidities [S: 31 (27%), and NS: 84 (73%); P = 0.004]; elevated APACHE score (S: 18 ± 1.1, and NS: 23 ± 0.9; P = 0.001); medical reason for admission [S: 25 (25.3%), and NS: 74 (74.7%); P = 0.004]; the presence of COVID-19 [S: 9 (13.6%), and NS: 57 (86.4%); P < 0.001]; lower pH (S: 7.36 ± 0.01, and NS: 7.3 ± 0.01; P = 0.002); lower PaO2 (S: 99.5 ± 5.2, and NS: 87.8 ± 2.3, mmHg; P = 0.001); lower PaO2/FiO2 (S: 177.5 ± 10, and NS: 128.4 ± 5.2, mmHg; P < 0.001); elevated PaCO2 (S: 38.4 ± 1.6, and NS: 45.1 ± 1.2, mmHg; P = 0.05); elevated Ppeak (S: 31.4 ± 1.2, and NS: 38.7 ± 1.1, cmH2O; P < 0.001); elevated PEEP (S: 10 ± 0.5, and NS: 12.6 ± 0.4, cmH2O; P < 0.001); elevated RR (S: 23.7 ± 0.7, and NS: 26.5 ± 0.7, breaths/minute; P = 0.001); elevated MV (S: 10.3 ± 0.3, and NS: 11 ± 0.3, L; P < 0.05).
Table 1 Characteristics of patients in the study population, n (%).
LOS among survivors (n = 41) was positively correlated to the categorical variables, namely, medical reason for admission (Yes: 25.5 ± 4.5, and No: 18.7 ± 7.7, days; P = 0.025) and the presence of COVID-19 (Yes: 37.3 ± 8, and No: 18.7 ± 4.5, days; P = 0.009), and the numerical variables, namely, central venous catheter (CVC) days (r = 0.99; P < 0.001), Ppeak (r = 0.3; P = 0.05), and RR (r = 0.4; P = 0.02), whereas it was negatively correlated to the numerical variable of age (r = -0.4; P = 0.02) (Tables 3 and 4). The duration of mechanical ventilation among survivors (n = 41) was positively correlated to the categorical variable of the presence of COVID-19 (Yes: 28 ± 8.4, and No: 12.6 ± 3.2, days; P = 0.009) and the numerical variables, namely, CVC days (r = 0.96; P < 0.001), Ppeak (r = 0.32; P = 0.04), and RR (r = 0.36; P = 0.02), whereas it was negatively correlated to the numerical variable of age (r = -0.4; P = 0.01) (Tables 3 and 4).
Table 3 Correlation of categorical variables with length of stay and duration of mechanical ventilation amongst survivors, n = 41.
In terms of the occurrence of AKI, after a comparison of the related variables, the following parameters exhibited a positive correlation to the occurrence of AKI: An elevated APACHE score (NA: 19.5 ± 1, and A: 23 ± 1; P = 0.007); increased number of CVC days (NA: 14.7 ± 1.9, and A: 19.8 ± 2.3; P = 0.03); medical reason for admission [NA: 41 (41.4%), and A: 59 (58.6%); P = 0.04]; the presence of COVID-19 [NA: 20 (30.3%), and A: 46 (69.7%); P < 0.001]; elevated Ppeak (NA: 34 ± 1.5, and A: 38.4 ± 1, cmH2O; P < 0.001); elevated PEEP (NA: 10.7 ± 0.5, and A: 12.7 ± 0.4, cmH2O; P = 0.001); elevated RR (NA: 24.6 ± 0.8, and A: 26.6 ± 0.7, breaths/minute; P = 0.02) (Table 5).
Table 5 Correlation of epidemiological and respiratory/arterial blood gases data with occurrence of acute kidney injury, n (%).
When variables that were revealed to be significantly different in the univariate analysis for mortality and AKI were incorporated into the binary logistic regression model, the following parameters were revealed as the independent predictors of mortality: Presence of comorbidities [odds ratio (OR) = 0.038, 95% confidence interval (CI): 0.004-0.323], APACHE score (OR = 1.248, 95%CI: 1.116-1.395), the presence of COVID-19 (OR = 0.14, 95%CI: 0.022-0.879), PaCO2 (OR = 1.091, 95%CI: 1.009-1.181), Ppeak (OR = 1.162, 95%CI: 1.033-1.308), RR (OR = 1.484, 95%CI: 1.059-2.079), and MV (OR = 0.99, 95%CI: 0.99-1). On the other hand, the APACHE score (OR = 1.101, 95%CI: 1.039-1.166) and the presence of COVID-19 (OR = 0.175, 95%CI: 0.048-0.635) were identified as independent factors associated with AKI (Tables 6 and 7). A review of all of the above correlations revealed that the presence of COVID-19 and elevated Ppeak and RR were consistently associated with all four studied outcomes, while age, number of CVC days, and medical reason for admission were correlated to three variables. The correlations of the other parameters with the four endpoints were variable, with fewer than three associations for the remaining studied parameters (Figure 1).
Figure 1 Review of all the correlations of epidemiological and respiratory/arterial blood gas data with the four available outcomes.
Only the presence of coronavirus disease 2019, peak airway pressure, and respiratory rate were correlated to all outcome measures, whereas age, central venous catheter days, and medical reason for admission were correlated to three of the outcome measures. Peak airway pressure and respiratory rate represent interesting targets for intervention to improve outcomes. COVID-19: Coronavirus disease 2019; Ppeak: Peak airway pressure; RR: Respiratory rate; CVC: Central venous catheter; IMV: Invasive mechanical ventilation; AKI: Acute kidney injury; APACHE: Acute physiology and chronic health evaluation; PEEP: Positive end-expiratory pressure; PaO2: Arterial oxygen partial pressure; FiO2: Fraction of inspired oxygen; PaCO2: Arterial carbon dioxide partial pressure; MV: Minute ventilation; ABGs: Arterial blood gases.
Table 6 Variables that were independent predictors of mortality after binary logistic regression analysis.
This study highlights the key prognostic indicators in critically ill patients with acute respiratory failure, distinguishing between modifiable and non-modifiable contributors to adverse outcomes. According to the results, the presence of COVID-19, Ppeak, and RR were associated with all the outcomes of this study. Older age, an increased number of CVC days, and medical reasons for admission were correlated to three out of the four outcomes studied. Elevated PEEP and APACHE score were correlated to two (the occurrence of AKI and increased mortality) out of four outcomes studied, whereas the presence of comorbidities, lower pH, lower PaO2 (hypoxemia), lower PaO2/FiO2, and elevated values of MV and PaCO2 (hypercapnia) were each solely associated with increased mortality, which is in accordance with previous reports[15-17].
Considering these results, Ppeak and RR, the potentially modifiable parameters of respiratory function, could be considered possible targets when designing an intervention, with the hypothesis that lower values would prove to be beneficial. Notably, the binary logistic regression analysis revealed that these variables were independently associated with mortality, further enhancing the strength of these associations. On the other hand, these parameters were not identified as independent predictors for the occurrence of AKI, thus increasing the need for more extensive research to precisely reveal what the observed correlations imply. Parameters that represented either non-modifiable demographic factors or patient characteristics or markers of disease severity (the presence of COVID-19, older age, increased number of CVC days, medical reason for admission, the presence of comorbidities, elevated APACHE score, and lower pH) may serve as triggers for a physician’s awareness of a patient’s compromised status and the possible need for escalation and implementation of the necessary therapeutic measures[9]. The association of RR with the occurrence of AKI, a relationship not proven independent after the regression analysis, needs further investigation, as it is a novel correlation with an outcome not directly related to the respiratory system.
Previous meta-analyses have explored the correlation of respiratory, epidemiological, and laboratory data only to mortality among patients with acute respiratory failure[9,10]. In order to enrich this research area, three additional outcomes were investigated in this study. The drawbacks of the sole use of mortality as an outcome in critically ill patients are well known, and the need for the use of other outcome measures when investigating the effect of an intervention or a parameter in the ICU is well established[18]. The authors of this study believe that the approach of evaluating many outcome measures leads to more definitive conclusions about the possible associations.
COVID-19 is a non-modifiable cause of severe ARDS and respiratory failure, with high rates of mortality[19,20]. The unfavorable effect of COVID-19 on all outcomes is not surprising and is in accordance with other previously reported results regarding AKI[21], duration of mechanical ventilation[22,23], and LOS[23].
The correlation of PEEP to the occurrence of AKI is also in accordance with previous findings[24] and can be attributed to the negative hemodynamic effects of PEEP on critically ill patients, especially for hypovolemic or septic patients, which are mediated by decreases in the venous return and cardiac output, which induce hypoperfusion of the vital organs, including the kidney[25,26]. Another mechanism responsible for the deterioration of renal function is the induction of a detrimental humoral response due to elevated PEEP, which causes activation of the renin–angiotensin system and suppression of atrial natriuretic peptide[26]. At high PEEP values, oxygenation may improve when the patient’s lungs are recruitable, but this may occur at the cost of worsening the perfusion of other vital organs. The association between PEEP and mortality has various possible explanations. Previous studies have reported a correlation between lower PEEP and increased mortality in ARDS patients, especially those with moderate ARDS[9,27]. However, this study has the opposite finding that higher PEEP is associated with increased mortality, and this is in accordance with the subgroup analysis of one of these previously mentioned studies, in which the potential harm of high PEEP in non-ARDS patients was revealed[27]. This study included both ARDS patients and non-ARDS patients, and the obtained results could be attributed to the effect of elevated PEEP on patients without ARDS. Moreover, the effect of PEEP on the occurrence of pulmonary complications depends on changes in ΔP as follows: The same increase in PEEP that leads to lower ΔP is associated with fewer pulmonary complications, whereas when it leads to higher ΔP, more pulmonary complications occur[28]. Pathophysiologically, a lower ΔP implies lung recruitment, whereas an equal or higher ΔP implies the absence of lung recruitability or overdistension when elevated PEEP is applied. The detrimental effects of higher PEEP values can be explained in the context of the mechanical power (MP) concept {MP = 0.098 × VT × RR × [Ppeak – ½ (Pplat - PEEP)]}. When high PEEP is applied, more energy is transferred from the ventilator to the lungs. If the patient’s lungs are recruitable, the improvement in oxygenation overcomes the harmful effect of this extra power, and if not, the harmful effect and the resulting complications outweigh any benefit. Individualization of PEEP settings is, therefore, deemed necessary to exert beneficial effects and avoid hazardous effects[8].
The relationships between Ppeak and RR and increased mortality are in accordance with previous studies[9]. The hazardous effects of PPeak and RR could be explained in relation to their participation in elevating MP, the energy derived from the ventilator to the lungs within a unit of time[29,30], or through other proposed mechanisms, such as for RR and adverse respiratory events (promotion of ventilator-induced lung injury, reverse triggered breaths, ineffective efforts, and induction of dynamic hyperinflation)[31] or for Ppeak and AKI (increase in the intra-abdominal pressure)[32]. The increased RR used frequently in clinical practice could also be the result of the effort to lower PaCO2 through increases in MV (MV = VT × RR) in patients with increased dead space ventilation (VD), which is a frequent characteristic of ARDS, since PaCO2 = K × rate of carbon dioxide production/MV - VD. The need for increased RR is increased by the effort to keep VT at the desired protective values of 4-6 mL/kg PBW. From this perspective, when the efforts for achieving lower RR values with the strategy of permissive hypercapnia reach the limit, strategies that lower PaCO2 in patients with ARDS and/or acute respiratory failure, such as extracorporeal membrane oxygenation and extracorporeal carbon dioxide removal, should be considered for earlier implementation to decrease the RR required for a set VT to achieve the values of MV required to keep PaCO2 within acceptable limits in patients with elevated VD[1]. The negative effect of elevated RR on renal function and its relationship with AKI could be explained pathophysiologically as the result of complex lung-kidney interactions, again through the concept of MP, as the effect of high-power mechanical ventilation on the kidneys. This effect has already been investigated in animal studies, which revealed that in addition to the statistically significant association of PEEP with AKI (P < 0.001), the RR tended to be associated with AKI (P = 0.084)[33,34].
This study has certain limitations that need to be addressed. It was designed as a single-center retrospective cohort study that did not include important parameters such as Pplat and ΔP (which were calculated by the treating physicians who considered the setting of mechanical ventilation parameters, but were not recorded and, thus, were not available for the statistical analysis in this study). This study included both ARDS patients and non-ARDS patients with respiratory failure, and concerns about the heterogeneity of the study group could be raised. However, differentiating ARDS patients from non-ARDS patients is not always feasible in everyday clinical practice. The available literature suggests that: (1) In many cases, in critically ill patients, both etiologies are present, such as in patients with pneumonia and ARDS[35]; (2) A relatively significant proportion of patients, estimated at about 14%, cannot be accurately classified as either ARDS patients or non-ARDS patients[36]; and (3) A significant number of patients with COVID-19, although diagnosed with viral infection and subsequent ARDS, develop or present with bacterial superinfection, with the percentage estimated at about 14%[37]. This percentage is even higher for other viral infections, such as influenza, which is estimated at 20%-30%[38]. Thus, the diagnosis of ARDS at presentation may be tricky, but significant overlap may also exist[35]. Therefore, the study population of this work is representative of ICU patients with acute respiratory failure, regardless of the presence or absence of ARDS. Future research may focus on improving the understanding of the underlying mechanisms of respiratory failure, elucidating the factors that influence the outcome of respiratory failure, distinguishing those that are linked only to disease severity, and searching for new outcome measures for patients surviving severe acute respiratory failure.
CONCLUSION
Although novel treatment strategies have been incorporated for patients with ARDS over the last few decades, many elements regarding the management of these patients need further clarification. Therefore, the present study investigated several outcome measures and identified the potentially modifiable respiratory parameters, such as Ppeak and RR, as having the potential to improve the overall outcome. Another interesting finding from this study that is worthy of further investigation is the association between RR and AKI. Although no definite conclusions can be drawn based on the findings of a single-center retrospective cohort study, the methodology of using many and other than mortality outcome measures represents an interesting proposal for future studies. In addition to the outcomes used in this study, future research could adopt a more holistic approach, with the use of physical, mental, and social health parameters as the possible outcome measures for ARDS and acute respiratory failure survivors. In that way, more global evaluations of survivors’ status and better treatment options could emerge in the future.
ACKNOWLEDGEMENTS
This paper is dedicated to the memory of the dearest friend, Zafeiridis T (1974-2021), as a 4-year tribute to his premature death.
Footnotes
Provenance and peer review: Invited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Critical care medicine
Country of origin: Greece
Peer-review report’s classification
Scientific Quality: Grade A, Grade C, Grade C, Grade C, Grade C
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