Standardizing PaO2 for PaCO2 in P/F ratio predicts in-hospital mortality in acute respiratory failure due to Covid-19: A pilot prospective study

When to intubate in acute hypoxaemic respiratory failure? Options and opportunities for evidence-informed decision making in the intensive care unit

The optimal timing of intubation in acute hypoxaemic respiratory failure is uncertain and became a point of controversy during the COVID-19 pandemic. Invasive mechanical ventilation is a potentially life-saving intervention but carries substantial risks, including injury to the lungs and diaphragm, pneumonia, intensive care unit-acquired muscle weakness, and haemodynamic impairment. In deciding when to intubate, clinicians must balance premature exposure to the risks of ventilation with the potential harms of unassisted breathing, including disease progression and worsening multiorgan failure. Currently, the optimal timing of intubation is unclear. In this Personal View, we examine a range of parameters that could serve as triggers to initiate invasive mechanical ventilation. The utility of a parameter (eg, the ratio of arterial oxygen tension to fraction of inspired oxygen) to predict the likelihood of a patient undergoing intubation does not necessarily mean that basing the timing of intubation on that parameter will improve therapeutic outcomes. We examine options for clinical investigation to make progress on establishing the optimal timing of intubation.

Machine learning-based prediction models for home discharge in patients with COVID-19: Development and evaluation using electronic health records

OBJECTIVE

This study aimed to develop and validate predictive models using electronic health records (EHR) data to determine whether hospitalized COVID-19-positive patients would be admitted to alternative medical care or discharged home.

METHODS

We conducted a retrospective cohort study using deidentified data from the University of Florida Health Integrated Data Repository. The study included 1,578 adult patients (≥18 years) who tested positive for COVID-19 while hospitalized, comprising 960 (60.8%) female patients with a mean (SD) age of 51.86 (18.49) years and 618 (39.2%) male patients with a mean (SD) age of 54.35 (18.48) years. Machine learning (ML) model training involved cross-validation to assess their performance in predicting patient disposition.

RESULTS

We developed and validated six supervised ML-based prediction models (logistic regression, Gaussian Naïve Bayes, k-nearest neighbors, decision trees, random forest, and support vector machine classifier) to predict patient discharge status. The models were evaluated based on the area under the receiver operating characteristic curve (ROC-AUC), precision, accuracy, F1 score, and Brier score. The random forest classifier exhibited the highest performance, achieving an accuracy of 0.84 and an AUC of 0.72. Logistic regression (accuracy: 0.85, AUC: 0.71), k-nearest neighbor (accuracy: 0.84, AUC: 0.63), decision tree (accuracy: 0.84, AUC: 0.61), Gaussian Naïve Bayes (accuracy: 0.84, AUC: 0.66), and support vector machine classifier (accuracy: 0.84, AUC: 0.67) also demonstrated valuable predictive capabilities.

SIGNIFICANCE

This study's findings are crucial for efficiently allocating healthcare resources during pandemics like COVID-19. By harnessing ML techniques and EHR data, we can create predictive tools to identify patients at greater risk of severe symptoms based on their medical histories. The models developed here serve as a foundation for expanding the toolkit available to healthcare professionals and organizations. Additionally, explainable ML methods, such as Shapley Additive Explanations, aid in uncovering underlying data features that inform healthcare decision-making processes.

Prognostic value of respiratory parameters for COVID-19 patients in the emergency department: results from the EC-COVID study

While several studies have evaluated the prognostic weight of respiratory parameters in patients with COVID-19, few have focused on patients' clinical conditions at the first emergency department (ED) assessment. We analyzed a large cohort of ED patients recruited within the EC-COVID study over the year 2020, and assessed the association between key bedside respiratory parameters measured in room air (pO2, pCO2, pH, and respiratory rate [RR]) and hospital mortality, after adjusting for key confounding factors. Analyses were based on a multivariable logistic Generalized Additive Model (GAM). After excluding patients who did not perform a blood gas analysis (BGA) test in room air or with incomplete BGA results, a total of 2458 patients were considered in the analyses. Most patients were hospitalized on ED discharge (72.0%); hospital mortality was 14.3%. Strong, negative associations with hospital mortality emerged for pO2, pCO2 and pH (p-values: < 0.001, < 0.001 and 0.014), while a significant, positive association was observed for RR (p-value < 0.001). Associations were quantified with nonlinear functions, learned from the data. No cross-parameter interaction was significant (all p-values were larger than 0.10), suggesting a progressive, independent effect on the outcome as the value of each parameter departed from normality. Our results collide with the hypothesized existence of patterns of breathing parameters with specific prognostic weight in the early stages of the disease.

A retrospective analysis of COVID-19 tracheostomies: Early versus late tracheostomy

Objectives

To assess the impact of early tracheostomy (ET) versus late tracheostomy (LT) placement on mortality and decannulation rates of COVID patients.

Methods

A retrospective chart review was performed of all patients infected with COVID-19 who underwent tracheostomy tube placement in an Ochsner-affiliated hospital from March 2020 to May 2022. Patients were identified using the electronic medical record and data was collated using the "Epic SlicerDicer" tool. Descriptive statistics were gathered and compared between patients who underwent ET placement and those who underwent LT placement. Patient demographics, previous medical history, tracheostomy procedural details, arterial blood gases, complications, and outcomes including time to wean from the ventilator, and time to decannulation were recorded.

Results

Two-hundred nineteen patients were included in the study. There were no statistically significant differences in liberation from mechanical ventilation rates between early and LT (62% vs. 55%, p = .19), or in decannulation rates (40% vs. 32%, p = .14). The mean duration of time to liberation from mechanical ventilation for early trach was 13.88 versus 18.17 days for late trach, however, no statistically significant difference was found (p = .12). Similarly, mean duration of time to decannulation was 41.17 days for early versus 47.72 for late trach (p = .15).

Conclusion

Contrary to some studies in the literature, the results presented here suggest ETs are not associated with hastened liberation from mechanical ventilation or increased decannulation rates. Further prospective studies may be warranted in assessing the impact of early versus LT in the COVID patient population.

Level of Evidence

III.

Hemodynamic, Oxygenation and Lymphocyte Parameters Predict COVID-19 Mortality

The mortality of COVID-19 patients has left the world devastated. Many scoring systems have been developed to predict the mortality of COVID-19 patients, but several scoring components cannot be carried out in limited health facilities. Herein, the authors attempted to create a new and easy scoring system involving mean arterial pressure (MAP), PF Ratio, or SF ratio-respiration rate (SF Ratio-R), and lymphocyte absolute, which were abbreviated as MPL or MSLR functioning, as a predictive scoring system for mortality within 30 days for COVID-19 patients. Of 132 patients with COVID-19 hospitalized between March and November 2021, we followed up on 96 patients. We present bivariate and multivariate analyses as well as the area under the curve (AUC) and Kaplan-Meier charts. From 96 patients, we obtained an MPL score of 3 points: MAP < 75 mmHg, PF Ratio < 200, and lymphocyte absolute < 1500/µL, whereas the MSLR score was 6 points: MAP < 75 mmHg, SF Ratio < 200, lymphocyte absolute < 1500/µL, and respiration rate 24/min. The MPL cut-off point is 2, while the MSLR is 4. MPL and MSLR have the same sensitivity (79.1%) and specificity (75.5%). The AUC value of MPL vs. MSLR was 0.802 vs. 0.807. The MPL ≥ 2 and MSLR ≥ 4 revealed similar predictions for survival within 30 days (p < 0.05). Conclusion: MPL and MSLR scores are potential predictors of mortality in COVID-19 patients within 30 days in a resource-limited country.

Hypocapnia as a predictor of the need for non-invasive mechanical ventilation in subjects with SARS-CoV-2 related pneumonia

Background: SARS-CoV-2 related pneumonia is characterized by moderate-to severe hypoxemia often associated with hypocapnia the prognostic role of which is poorely documented. Aims: evaluate if hypocapnia can predict the need for non-invasive mechanical ventilation (NIMV) in this setting. Materials and methods: we prospectively studied 52 subjects with moderate-severe SARS-CoV-2 related pneumonia. All the following data were collected at admission to the Emergency Department and processed by univariate and multivariate analysis: clinical and laboratory data, blood gas analysis in room air and lung ultrasound. Results: 33/52 subjects (63,4%) underwent NIMV. At univariate analysis PaCO2 was inversely associated to the need for NIMV (OR 0,82, CI 95% 0,689-0,976, p .025). At multivariate analysis PaCO2 predicted the need for NIMV independently from age, gender, number of comorbidities, d-dimer, CRP, PaO2 and LUS SCORE (OR 0,838, CI 95% 0,710-0,988, p .035). Conclusions: our data suggest that hypocapnia could be an early predictor of clinical worsening in these patients independently from other known predictors of unfavourable outcome, reflecting the occurrence of a deep and frequent respiratory pattern possibly related to the generation of excessive transpulmonary pressure swings leading to a self-induced lung injury (P-SILI). Further studies are needed for validating these data on greater populations.

Predicting factors associated with prolonged intensive care unit stay of patients with COVID-19

BACKGROUND

Predicting the length of stay (LOS) for coronavirus disease 2019 (COVID-19) patients in the intensive care unit (ICU) is essential for efficient use of ICU resources. We analyzed the clinical characteristics of patients with severe COVID-19 based on their clinical care and determined the predictive factors associated with prolonged LOS.

METHODS

We included 96 COVID-19 patients who received oxygen therapy at a high-flow nasal cannula level or above after ICU admission during March 2021 to February 2022. The demographic characteristics at the time of ICU admission and results of severity analysis (Sequential Organ Failure Assessment [SOFA], Acute Physiology and Chronic Health Evaluation [APACHE] II), blood tests, and ICU treatments were analyzed using a logistic regression model. Additionally, blood tests (C-reactive protein, D-dimer, and the PaO2 to FiO2 ratio [P/F ratio]) were performed on days 3 and 5 of ICU admission to identify factors associated with prolonged LOS.

RESULTS

Univariable analyses showed statistically significant results for SOFA score at the time of ICU admission, C-reactive protein level, high-dose steroids, mechanical ventilation (MV) care, continuous renal replacement therapy, extracorporeal membrane oxygenation, and prone position. Multivariable analysis showed that MV care and P/F ratio on hospital day 5 were independent factors for prolonged ICU LOS. For D-dimer, no significant variation was observed at admission; however, after days 3 and 5 days of admission, significant between-group variation was detected.

CONCLUSIONS

MV care and P/F ratio on hospital day 5 are independent factors that can predict prolonged LOS for COVID-19 patients.

Association between PaO2/FiO2 ratio and thrombotic events in COVID-19 patients

PaO₂/FiO₂ (P/F ratio) is considered a marker of hypoxia/hypoxemia and mortality. Several prothrombotic changes are associated with the decrease of P/F ratio. The role of P/F ratio in patients with arterial and venous thrombosis remains unclear. The aim of this study was to assess in patients with coronavirus disease 2019 (COVID-19), the association between P/F ratio and arterial/venous thrombosis. One thousand and four hundred and six COVID-19 patients were recruited; 289 (21%) patients had P/F ratio < 200 and 1117 (79%) ≥ 200. Compared to the patients with P/F ratio ≥ 200, those with P/F ratio < 200 were older and with higher levels of glycemia, D-dimer and lower levels of albumin. Multiple linear regression analysis showed that albumin (standardized coefficient β:  0.156; SE: 0.001; p = 0.0001) and D-dimer (standardized coefficient β: -0.135; SE: 0.0001; p = 0.0001) were associated with P/F ratio. During the hospitalization 159 patients were transferred in intensive care unit (ICU), 253 patients died, 156 patients had arterial or venous thrombotic events. A bivariate logistic analysis was performed to analyze the predictors of thrombosis in COVID-19 patients; P/F ratio < 200 (Odds Ratio: [OR] 1.718, 95% Confidence Interval [CI] 1.085-2.718, p = 0.021), albumin (OR 1.693, 95% CI 1.055-2.716, p = 0.029), D-dimer (OR 3.469, 95% CI 2.110-5.703, p < 0.0001), coronary artery disease (CAD) (OR 1.800, 95% CI 1.086-2.984, p = 0.023) and heart failure (OR 2.410 95% CI 1.385-4.193, p = 0.002) independently predicted thrombotic events in this population. This study suggests that the P/F ratio is associated with thrombotic events by promoting a hypercoagulation state in patients hospitalized for COVID-19.

Conservative oxygen supplementation during Helmet CPAP therapy in patients with COVID-19 and respiratory failure: A pilot study

Background

Respiratory failure is a severe complication in COVID-19 pneumonia that, in addition to oxygen therapy, may require CPAP support. It has been postulated that COVID-19 lung injury may share some features with those observed in HALI. Thus, a correct target PaO2during oxygen supplementation may be crucial to protect the lung from further tissue damage. Aims of the study were: 1) to evaluate the effects of conservative oxygen supplementation during Helmet CPAP therapy on mortality and ICU admission in patients with COVID-19 and respiratory failure; 2) to evaluate the effect of conservative oxygen supplementation on new-onset organ failure and secondary pulmonary infections.

Methods

This was a single-center, historically controlled study of patients with severe respiratory failure due to COVID-19 pneumonia, receiving either conservative or non-conservative oxygen supplementation during Helmet CPAP. A cohort receiving conservative oxygen supplementation was studied prospectively in which oxygen supplementation was administered with a target PaO2<100 mmHg. Results of this cohort were compared with those of a cohort who had received liberal oxygen supplementation.

Results

Seventy-one patients were included in the conservative cohort and 75 in the non-conservative cohort. Mortality rate was lower in the conservative cohort (22.5%versus62.7%, p<0.001). Rates of ICU admission and new-onset rate organ failure were lower in conservative cohort (14.1%versus37.3%, p=0.001, and 9.9%versus45.3% p<0.001, respectively).

Conclusions

In patients with COVID-19 and severe respiratory failure, conservative oxygen supplementation during Helmet CPAP was associated to improved survival, lower ICU admission rate and less new-onset organ failure.

COPD, but Not Asthma, Is Associated with Worse Outcomes in COVID-19: Real-Life Data from Four Main Centers in Northwest Italy

Introduction: Asthma, along with inhaled steroids, was initially considered a risk factor for worse clinical outcomes in COVID-19. This was related to the higher morbidity observed in asthma patients during previous viral outbreaks. This retrospective study aimed at evaluating the prevalence of asthma among patients admitted due to SARS-CoV-2 infection as well as the impact of inhaled therapies on their outcomes. Furthermore, a comparison between patients with asthma, COPD and the general population was made. Methods: All COVID-19 inpatients were recruited between February and July 2020 from four large hospitals in Northwest Italy. Data concerning medical history, the Charlson Comorbidity Index (CCI) and the hospital stay, including length, drugs and COVID-19 complications (respiratory failure, lung involvement, and the need for respiratory support) were collected, as well as the type of discharge. Results: patients with asthma required high-flow oxygen therapy (33.3 vs. 14.3%, p = 0.001) and invasive mechanical ventilation (17.9 vs. 9.5%, p = 0.048) more frequently when compared to the general population, but no other difference was observed. Moreover, asthma patients were generally younger than patients with COPD (59.2 vs. 76.8 years, p < 0.001), they showed both a lower mortality rate (15.4 vs. 39.4%, p < 0.001) and a lower CCI (3.4 vs. 6.2, p < 0.001). Patients with asthma in regular therapy with ICS at home had significantly shorter hospital stay compared to those with no treatments (25.2 vs. 11.3 days, p = 0.024). Discussion: Our study showed that asthma is not associated with worse outcomes of COVID-19, despite the higher need for respiratory support compared with the general population, while the use of ICS allowed for a shorter hospital stay. In addition, the comparison of asthma with COPD patients confirmed the greater frailty of the latter, according to their multiple comorbidities.

Co-Administration of Remdesivir and Azithromycin May Protect against Intensive Care Unit Admission in COVID-19 Pneumonia Requiring Hospitalization: A Real-Life Observational Study

The benefits of remdesivir treatment, with or without co-administration of antibiotics such as azithromycin, are uncertain in COVID-19 pneumonia. The aim of this retrospective single-center study was to assess the effects of remdesivir, with or without azithromycin, on hospital mortality, intensive care unit (ICU) admission, and need of non-invasive ventilation. The clinical records of the COVID-19 patients hospitalized in an Italian ward in March 2021 were analyzed, and data on comorbidities and clinical, radiological, and laboratory presentation of the disease were collected. Among 394 participants (234 M), 173 received remdesivir (43.9%), including 81 with azithromycin (20.5%). Remdesivir recipients were younger, with less comorbidities, and had better PaO₂/FiO₂ and clinical outcomes, including reduced mortality, but the differences were not independent of covariates. Rates of ICU transferal were 17%, 9%, and 1% in the no remdesivir, remdesivir without azithromycin, and remdesivir/azithromycin groups, respectively. In a stepwise multivariate logistic regression model, remdesivir/azithromycin co-treatment was independently associated with reduced ICU admission (vs remdesivir alone, OR 0.081, 95% CI 0.008-0.789, p = 0.031; vs no remdesivir, OR 0.060, 95% CI 0.007-0.508, p = 0.010). These data suggest that the therapeutical effect of remdesivir in COVID-19 pneumonia may be potentiated by azithromycin. The association between the two drugs should be further investigated.

Use of the Pao2/Fio2 Ratio in Pulmonary Embolism: Evaluation of its Correlation with Pulmonary Arterial Computed Tomography Obstruction Index

RATIONALE AND OBJECTIVES

The pulmonary arterial computed tomography obstruction index ratio (PACTOIR) is a parameter that provides an idea of the clinical severity of acute pulmonary embolism (APE). This study aimed to examine the correlation between the PaO₂ /FiO₂ ratio and PACTOIR in patients who presented to the emergency department and received a preliminary diagnosis of APE.

MATERIALS AND METHODS

This study was conducted prospectively in the emergency department. The patients' sociodemographic characteristics, vital signs, PACTOIR, and PaO₂ /FiO₂ ratio were obtained. The correlation between PACTOIR and PaO₂ /FiO₂ ratio was then statistically evaluated.

RESULTS

The study included 50 patients, of whom 31 (62%) were women, and 19(38%) were men. The female patients had a PaO₂ /FiO₂ ratio of 209 ± 67 and PACTOIR of 36.3 ± 15.5. The male patients had a PaO₂ /FiO₂ ratio of 169 ± 43 and PACTOIR of 39.7 ± 19. The PaO₂ /FiO₂ ratio of the patients with APE was negatively correlated with the PACTOIR value at a statistically significant level (r = -0.308, p = 0.031). The regression equation was as follows: PACTOIR = (-0.0869) x (PaO₂ / FiO₂) + (54.489).

CONCLUSION

By calculating the PaO₂ /FiO₂ ratio in patients with APE, the degree of pulmonary artery obstruction and clinical severity can be predicted. Therefore, the ratio PaO₂ /FiO₂ can be used instead of PACTOIR.

Alveolar-Arterial Gradient Is an Early Marker to Predict Severe Pneumonia in COVID-19 Patients

Background: One of the main challenges in the management of COVID-19 patients is to early assess and stratify them according to their risk of developing severe pneumonia. The alveolar−arterial oxygen gradient (D(A-a)O2) is defined as the difference between the alveolar and arteriolar concentration of oxygen, an accurate index of the ventilatory function. The aim of this study is to evaluate D(A-a)O2 as a marker for predicting severe pneumonia in COVID-19 patients, in comparison to the PaO2/FiO2. Methods: This retrospective, multicentric cohort study included COVID-19 patients admitted to two Italian hospitals between April and July 2020. Clinical and laboratory data were retrospectively collected at the time of hospital admission and during hospitalization. The presence of severe COVID-19 pneumonia was evaluated, as defined by the Infectious Diseases Society of America (IDSA) criteria for community-acquired pneumonia (CAP). Patients were divided in severe and non-severe groups. Results: Overall, 53 COVID-19 patients were included in the study: male were 30/53 (57%), and 10/53 (19%) had severe pneumonia. Patients with severe pneumonia reported dyspnea more often than non-severe patients (90% vs. 39.5%; p = 0.031). A history of chronic obstructive pulmonary disease (COPD) was recalled by 5/10 (50%) patients with severe pneumonia, and only in 6/43 (1.4%) of non-severe cases (p = 0.023). A ROC curve, for D(A-a)O2 >60 mmHg in detecting severe pneumonia, showed an area under the curve (AUC) of 0.877 (95% CI: 0.675−1), while the AUC of PaO2/FiO2 < 263 mmHg resulted 0.802 (95% CI: 0.544−1). D(A-a)O2 in comparison to PaO2/FiO2 had a higher sensibility (77.8% vs. 66.7%), positive predictive value (75% vs. 71.4%), negative predictive value (94% vs. 91%), and similar specificity (94.4% vs. 95.5%). Conclusions: Our study suggests that the D(A-a)O2 is more appropriate than PaO2/FiO2 to identify COVID-19 patients at risk of developing severe pneumonia early.

Predictors of SARS-CoV-2 IgG Spike Antibody Responses on Admission and Clinical Outcomes of COVID-19 Disease in Fully Vaccinated Inpatients: The CoVax Study

Background: SARS-CoV-2 vaccines have shown high efficacy in protecting against COVID-19, although the determinants of vaccine effectiveness and breakthrough rates are yet to be determined. We aimed at investigating several factors affecting the SARS-CoV-2 IgG Spike (S) antibody responses on admission and clinical outcomes of COVID-19 disease in fully vaccinated, hospitalized patients. Methods: 102 subjects were enrolled in the study. Blood serum samples were collected from each patient upon admission for the semiquantitative determination of the SARS-CoV-2 IgG S levels with lateral flow assays. Factors influencing vaccine responses were documented. Results: 27 subjects had a negative antibody test upon hospital admission. Out of the 102 patients admitted to the hospital, 88 were discharged and 14 died. Both the absence of anti-S SARS-CoV-2 antibodies and poor clinical outcomes of COVID-19 disease were associated with older age, lower Ct values, and a shorter period between symptom onset and hospital admission. Ct values and time between symptom onset and hospitalization were independently associated with SARS-CoV-2 IgG S responses upon admission. The PaO2/FiO2 ratio was identified as an independent predictor of in-hospital mortality. Conclusions: Host- and disease-associated factors can predict SARS-CoV-2 IgG S responses and mortality in hospitalized patients with breakthrough SARS-CoV-2 Infection.

The PaCO2/FiO2 ratio as outcome predictor in SARS-COV-2 related pneumonia: a retrospective study

BACKGROUND AND AIM

Respiratory failure in SARS-CoV-2 patients is characterized by the presence of hypoxemia and hypocapnia without relevant dyspnea. To date, the use of respiratory parameters other than PaO2/FiO2 ratio to stratify the risk of worsening of these patients has not been sufficiently studied.  Aim of this work was to evaluate whether the ratio between partial pressure levels of carbon dioxide (PaCO2) and the fraction of inspired oxygen (FiO2) measured at emergency department (ED) admission is predictive of the clinical course of patients suffering from SARS-CoV-2 pneumonia.

METHODS

We retrospectively studied 236 patients with SARS-CoV-2 pneumonia evaluated at the ED of the Perugia Hospital. The end-points were: in-hospital mortality, need for invasive mechanical ventilation (IMV) and length of in-hospital stay (LOS). Clinical, blood gas and laboratory data were collected at ED admission.

RESULTS

Of the 236 patients 157 were male, the mean age was 64 ± 16. Thirtythree patients (14%) needed IMV, 49 died (21%). In the univariate analysis, the PaCO2/FiO2 ratio was inversely associated with the need for IMV (p <0.001), mortality (p <0.001) and LOS (p = 0.005). At the multivariate analysis the PaCO2/FiO2 ratio was found to be predictive of the need for IMV, independently from age, gender, number of comorbidities, neutrophils, lymphocytes, glomerular filtrate, d-dimer, LDH and CRP.

CONCLUSIONS

the PaCO2/FiO2 ratio is predictive of the risk of respiratory failure worsening in patients with SARS-CoV-2 pneumonia, independently from other several confounding factors.

Single-Breath Counting Test Predicts Non-Invasive Respiratory Support Requirements in Patients with COVID-19 Pneumonia

The use of non-invasive respiratory strategies (NIRS) is crucial to improve oxygenation in COVID-19 patients with hypoxemia refractory to conventional oxygen therapy. However, the absence of respiratory symptoms may delay the start of NIRS. The aim of this study was to determine whether a simple bedside test such as single-breath counting test (SBCT) can predict the need for NIRS in the 24 h following the access to Emergency Department (ED). We performed a prospective observational study on 120 patients with COVID-19 pneumonia. ROC curves were used to analyze factors which might predict NIRS requirement. We found that 36% of patients had normal respiratory rate and did not experience dyspnea at rest. 65% of study population required NIRS in the 24 h following the access to ED. NIRS-requiring group presented lower PaO₂/FiO₂ (235.09 vs. 299.02), SpO₂/FiO₂ ratio (357.83 vs. 431.07), PaCO₂ (35.12 vs. 40.08), and SBCT (24.46 vs. 30.36) and showed higher incidence of dyspnea at rest (57.7% vs. 28.6%). Furthermore, SBCT predicted NIRS requirement even in the subgroup of patients without respiratory symptoms (AUC = 0.882, cut-off = 30). SBCT might be a valuable tool for bedside assessment of respiratory function in patients with COVID-19 pneumonia and might be considered as an early clinical sign of impending respiratory deterioration.