COVID-19 can cause a clinical spectrum from asymptomatic disease to life-threatening respiratory failure and acute respiratory distress syndrome (ARDS). There is an ongoing discussion whether the clinical presentation and ventilatory parameters are the same as typical ARDS or not. There is no clear understanding of how the hemodynamic parameters have been affected in COVID-19 ARDS patients. We aimed to compare hemodynamic and respiratory parameters of moderate and severe COVID-19 and non-COVID-19 ARDS patients. These patients were monitored with an advanced hemodynamic measurement system by the transpulmonary thermodilution method in prone and supine positions. Data of 17 patients diagnosed with COVID-19 and 16 patients diagnosed with other types of diseases with moderate and severe ARDS, mechanically ventilated, placed in a prone position, had advanced hemodynamic measurements with PiCCO, and stayed in the intensive care unit for more than a week were analyzed retrospectively. Patient characteristics and arterial blood gases analysis recorded at admission and respiratory and advanced hemodynamic parameters during the first week were compared in prone and supine positions. No difference was observed in the respiratory parameters including respiratory system compliance between COVID-19 and non-COVD-19 patients in prone and supine positions. In comparison of advanced hemodynamic parameters in the first week of intensive care, the extravascular lung water and pulmonary vascular permeability indexes measured in supine position of COVID-19 ARDS patients were found to be significantly higher than non-COVID-19 patients. Duration of prone position was significantly longer in patients diagnosed with COVID-19 ARDS. The results of this study suggested that COVID-19 ARDS is a variant of typical ARDS with a different pathophysiology. Asar S, Acicbe Ö, Sabaz MS, Tontu F, Canan E, Cukurova Z, et al. Comparison of Respiratory and Hemodynamic Parameters of COVID-19 and Non-COVID-19 ARDS Patients. Indian J Crit Care Med 2021;25(6):704–708.

Background: The oxygenation index (OI) and oxygen saturation index (OSI) are proven mortality predictors in pediatric and adult patients, traditionally using mean airway pressure (P_mean). We introduce novel indices, replacing P_mean with DP (ΔP_insp), MP_dyn, and MP_tot, assessing their potential for predicting COVID-19 acute respiratory distress syndrome (ARDS) mortality, comparing them to traditional indices. Methods: We studied 361 adult COVID-19 ARDS patients for 7 days, collecting ΔP_insp, MP_dyn, and MP_tot, OI-ΔP_insp, OI-MP_dyn, OI-MP_tot, OSI-ΔP_insp, OSI-MP_dyn, and OSI-MP_tot. We compared these in surviving and non-surviving patients over the first 7 intensive care unit (ICU) days using Mann–Whitney U test. Logistic regression receiver operating characteristic (ROC) analysis assessed AUC and CI values for ICU mortality on day three. We determined cut-off values using Youden's method and conducted multivariate Cox regression on parameter limits. Results: All indices showed significant differences between surviving and non-surviving patients on the third day of ICU care. The AUC values of OI-ΔP_insp were significantly higher than those of P/F and OI-P_mean ( P values .0002 and <.0001, respectively). Similarly, AUC and CI values of OSI-ΔP_insp and OSI-MP_dyn were significantly higher than those of SpO₂/FiO₂ and OSI-P_mean values (OSI-ΔP_insp: P < .0001, OSI-MP_dyn: P values .047 and .028, respectively). OI-ΔP_insp, OSI-ΔP_insp, OI-MP_dyn, OSI-MP_dyn, OI-MP_tot, and OSI-MP_tot had AUC values of 0.72, 0.71, 0.69, 0.68, 0.66, and 0.64, respectively, with cut-off values associated with hazard ratios and P values of 7.06 (HR = 1.84, P = .002), 8.04 (HR = 2.00, P ≤ .0001), 7.12 (HR = 1.68, P = .001), 5.76 (HR = 1.70, P ≤ .0001), 10.43 (HR = 1.52, P = .006), and 10.68 (HR = 1.66, P = .001), respectively. Conclusions: Critical values of all indices were associated to higher ICU mortality rates and extended mechanical ventilation durations. The OI-ΔP_insp, OSI-ΔP_insp, and OSI-MP_dyn indices displayed the strongest predictive capabilities for ICU mortality. These novel indices offer valuable insights for intensivists in the clinical management and decision-making process for ARDS patients.

Amaç: Yoğun bakım ünitesi (YBÜ) hastalarında elektrolit ve asit-baz bozukluklarının tanı ve tedavisi kritik öneme sahiptir. Asit-baz bozukluklarını açıklamada Stewart yaklaşımının önemi bilinmektedir. Bu yaklaşıma göre tanımlanmış çeşitli parametreler vardır. Bu çalışmanın amacı, Stewart’ın yaklaşımına göre hesaplanan klorür etki (ClEffect), sodyum etki (NaEffect), sodyum-klorür etki (Na-ClEffect) güçlü iyon farkı (SIDnl), Cl/Na oranı değerlerinin YBÜ mortalitesi üzerindeki etkilerini değerlendirmektir. Gereç ve Yöntem: Bilgisayar destekli karar destek sistemine Na, Cl, K, standart baz fazlalığı (SBE), pH değerleri kaydedilen ve sisteme tanımlı formüller aracılığıyla SID, NaEffect, ClEffect, Na-ClEffect, Akut Fizyoloji ve Kronik Sağlık Değerlendirmesi-II (APACHE-II) ve Sıralı Organ Yetmezliği Değerlendirmesi (SOFA) skorları hesaplanan 2.000 hasta bu çalışmaya dahil edilmiştir. ClEffect, NaEffect, Na-ClEffect, SIDnl, Cl/Na oranı değerleri multivariable lojistik regresyon modeli ile YBÜ mortalitesi açısından değerlendirildi. Bulgular: Anormal SIDnl aralıkları (SIDnl 7 ve SIDnl

Mechanical power (MP) integrates the contributors to ventilator-induced lung injury and relates to mortality, yet bedside calculation remains challenging. The dynamic mechanical power equation (MPdyn) offers a simple approach but requires validation against the geometric gold standard (MPgeo). To validate MPdyn against MPgeo in volume-controlled (VCV) and pressure-controlled ventilation (PCV) across I:E ratios of 1:2 and 1:1. Prospective observational study in a tertiary ICU. Adults with ARDS (n = 36) underwent standardized measurements in VCV and PCV at I:E 1:2 and 1:1. For each setting, three complete pressure-volume (P-V) loop screenshots were captured. MPgeo (J/min) was derived using a Python-based image-processing tool (OpenCV/NumPy/PIL) employing grayscale conversion, thresholding, morphological closing, flood-fill segmentation, and area-ratio computation. MPdyn was computed as MV × [WOBv + (PEEP × 0.098)]. Agreement was assessed with univariable linear regression and Bland-Altman analyses. MPdyn correlated strongly with MPgeo in all modes and I:E ratios (R² ≥ 0.97). Biases (MPdyn - MPgeo) were 0.15 J/min (0.8 %) for VCV 1:2, 0.32 J/min (2.1 %) for VCV 1:1, 0.28 J/min (1.9 %) for PCV 1:2, and 0.52 J/min (3.4 %) for PCV 1:1. The standard deviation of the bias remained <0.5 J/min across analyses. MPdyn demonstrates high agreement with MPgeo in both VCV and PCV modes, supporting its use as a simple, reliable, and bedside-applicable tool for calculating mechanical power in ARDS patients.

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