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BACKGROUND: Postoperative pulmonary complications (PPCs) can increase hospital length of stay, postoperative morbidity and mortality. Despite many factors can increase the risk of PPCs, it is not known whether intraoperative ventilation/perfusion (V/Q) mismatch can be associated with an increased risk of PPCs after major non-cardiac surgery. METHODS: We enrolled patients undergoing general anesthesia for non-cardiac surgery and evaluated intraoperative V/Q distribution using the Automatic Lung Parameter Estimator technique. The assessment was done after anesthesia induction (T1), after 1 hour from surgery start (T2) and at the end of surgery (T3). We collected demographic and procedural information and measured intraoperative ventilatory and hemodynamic parameters at each time-point. Patients were followed up for 7 days after surgery and assessed daily for PPCs occurrence. RESULTS: We enrolled 101 patients with a median age of 71 [62-77] years, a BMI of 25 [22.4-27.9] kg/m 2 and a preoperative ARISCAT score of 41 [34-47]. Of them, 29 (29%) developed PPCs, mainly acute respiratory failure (23%) and pleural effusion (11%). Patients with and without PPCs did not differ in levels of shunt at T1 (PPCs:22.4[10.4-35.9] % vs No PPCs:19.3[9.4-24.1] %, p=0.18) or during the protocol, while significantly different levels of high V/Q were found during surgery (PPCs:13[11-15] mmHg vs No PPCs:10[8-13.5] mmHg, p=0.007) and before extubation (PPCs:13[11-14]mmHg vs No PPCs:10[8-12] mmHg, p=0.006). After adjusting for age, ARISCAT, BMI, smoking, fluid balance, anesthesia type, laparoscopic procedure and surgery duration, high V/Q before extubation was independently associated with the development of PPCs (OR 1.147, CI 95% [1.021-1.289], p=0.02). The sensitivity analysis showed an E-value of 1.35 (CI=1.11). CONCLUSIONS: In patients with intermediate/high risk of PPCs undergoing major non-cardiac surgery, intraoperative V/Q mismatch is associated with the development of PPCs. Increased high V/Q before extubation is independently associated with the occurrence of PPCs in the first 7 days after surgery.
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PURPOSE: Growing evidence shows the complex interaction between lung and kidney in critically ill patients. The renal resistive index (RRI) is a bedside measurement of the resistance of the renal blood flow and it is correlated with kidney injury. The positive end-expiratory pressure (PEEP) level could affect the resistance of renal blood flow, so we assumed that RRI could help to monitoring the changes in renal hemodynamics at different PEEP levels. Our hypothesis was that the RRI at ICU admission could predict the risk of acute kidney injury in mechanical ventilated critically ill patients. METHODS: We performed a prospective study including 92 patients requiring mechanical ventilation for ≥ 48 h. A RRI ≥ 0.70, was deemed as pathological. RRI was measured within 24 h from ICU admission while applying 5,10 and 15 cmH2O of PEEP in random order (PEEP trial). RESULTS: Overall, RRI increased from 0.62 ± 0.09 at PEEP 5 to 0.66 ± 0.09 at PEEP 15 (p < 0.001). The mean RRI value during the PEEP trial was able to predict the occurrence of AKI with AUROC = 0.834 [95%CI 0.742-0.927]. Patients exhibiting a RRI ≥ 0.70 were 17/92(18%) at PEEP 5, 28/92(30%) at PEEP 10, 38/92(41%) at PEEP 15, respectively. Thirty-eight patients (41%) exhibited RRI ≥ 0.70 at least once during the PEEP trial. In these patients, AKI occurred in 55% of the cases, versus 13% remaining patients, p < 0.001. CONCLUSIONS: RRI seems able to predict the risk of AKI in mechanical ventilated patients; further, RRI values are influenced by the PEEP level applied. TRIAL REGISTRATION: Clinical gov NCT03969914 Registered 31 May 2019.
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Transpulmonary pressure (PL) calculation requires esophageal pressure (PES) as a surrogate of pleural pressure (Ppl), but its calibration is a cumbersome technique. Central venous pressure (CVP) swings may reflect tidal variations in Ppl and could be used instead of PES, but the interpretation of CVP waveforms could be difficult due to superposition of heartbeat-induced pressure changes. Thus, we developed a digital filter able to remove the cardiac noise to obtain a filtered CVP (f-CVP). The aim of the study was to evaluate the accuracy of CVP and filtered CVP swings (ΔCVP and Δf-CVP, respectively) in estimating esophageal respiratory swings (ΔPES) and compare PL calculated with CVP, f-CVP and PES; then we tested the diagnostic accuracy of the f-CVP method to identify unsafe high PL levels, defined as PL>10 cmH2O. Twenty patients with acute respiratory failure (defined as PaO2/FiO2 ratio below 200 mmHg) treated with invasive mechanical ventilation and monitored with an esophageal balloon and central venous catheter were enrolled prospectively. For each patient a recording session at baseline was performed, repeated if a modification in ventilatory settings occurred. PES, CVP and airway pressure during an end-inspiratory and -expiratory pause were simultaneously recorded; CVP, f-CVP and PES waveforms were analyzed off-line and used to calculate transpulmonary pressure (PLCVP, PLf-CVP, PLPES, respectively). Δf-CVP correlated better than ΔCVP with ΔPES (r = 0.8, p = 0.001 vs. r = 0.08, p = 0.73), with a lower bias in Bland Altman analysis in favor of PLf-CVP (mean bias - 0.16, Limits of Agreement (LoA) -1.31, 0.98 cmH2O vs. mean bias - 0.79, LoA - 3.14, 1.55 cmH2O). Both PLf-CVP and PLCVP correlated well with PLPES (r = 0.98, p < 0.001 vs. r = 0.94, p < 0.001), again with a lower bias in Bland Altman analysis in favor of PLf-CVP (0.15, LoA - 0.95, 1.26 cmH2O vs. 0.80, LoA - 1.51, 3.12, cmH2O). PLf-CVP discriminated high PL value with an area under the receiver operating characteristic curve 0.99 (standard deviation, SD, 0.02) (AUC difference = 0.01 [-0.024; 0.05], p = 0.48). In mechanically ventilated patients with acute respiratory failure, the digital filtered CVP estimated ΔPES and PL obtained from digital filtered CVP represented a reliable value of standard PL measured with the esophageal method and could identify patients with non-protective ventilation settings.
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Pressão Venosa Central , Esôfago , Respiração Artificial , Humanos , Respiração Artificial/métodos , Masculino , Feminino , Pessoa de Meia-Idade , Idoso , Estudos Prospectivos , Monitorização Fisiológica/métodos , Monitorização Fisiológica/instrumentação , Pressão , Insuficiência Respiratória/terapia , Insuficiência Respiratória/fisiopatologia , Reprodutibilidade dos Testes , Idoso de 80 Anos ou mais , Pleura/fisiopatologia , Algoritmos , Volume de Ventilação PulmonarRESUMO
Prone positioning (PP) represents a therapeutic intervention with the proven capacity of ameliorating gas exchanges and ventilatory mechanics indicated in acute respiratory distress syndrome (ARDS). When PP is selectively applied to moderate-severe cases of ARDS, it sensitively affects clinical outcomes, including mortality. After the COVID-19 outbreak, clinical application of PP peaked worldwide and was applied in 60% of treated cases, according to large reports. Research on this topic has revealed many physiological underpinnings of PP, focusing on regional ventilation redistribution and the reduction of parenchymal stress and strain. However, there is a lack of evidence on biomarkers behavior in different phases and phenotypes of ARDS. Patients response to PP are, to date, decided on PaO2/FiO2 ratio improvement, whereas scarce data exist on biomarker tracking during PP. The purpose of this review is to explore current evidence on the clinical relevance of biomarkers in the setting of moderate-severe ARDS of different etiologies (i.e., COVID and non-COVID-related ARDS). Moreover, this review focuses on how PP may modulate biomarkers and which biomarkers may have a role in outcome prediction in ARDS patients.