Population
Prospective, observational pilot study performed in a COVID-19 Intensive Care Unit (ICU) and a mixed medical-surgical ICU at University Hospital of Ferrara, Italy. The study was approved by the ethic committee (approval number 339/2020). We included consecutive patients with SARS-COV-2 ARDS or ARDS undergoing mechanical ventilation. Exclusion criteria were: diagnosis of AKI before ICU admission, unsatisfactory ultrasound visualization, arrhythmia, renal replacement therapy and denied consent. All patients included in the SARS-COV-2 ARDS group had laboratory-confirmed COVID-19.
Mechanical ventilation settings
At the time of renal blood flow assessment, all patients were deeply sedated and paralyzed with continuous infusion of cis-atracurium 1–3 mcg/kg/min for clinical reasons. Mechanical ventilation settings included constant-flow controlled ventilation, a tidal volume of 6 ml/kg of ideal body weight and the PEEP level titrated to the lowest driving pressure. [14, 15] Briefly, PEEP was increased by 2 cm H2O step starting from 6 cm H2O, up to the PEEP level leading to a static end-inspiratory plateau pressure (PPLAT) of 28–30 cm H2O; then, the PEEP level corresponding to the lowest driving pressure was chosen.
The driving pressure was measured as:
$${\text{P}}_{\text{P}\text{LAT}}-{\text{P}\text{EEP}}_{\text{TOT}}.$$
where PEEPTOT is the total static positive end-expiratory pressure. PPLAT and PEEPTOT were measured through the occlusion technique (i.e. a 4 s airway opening occlusion maneuver at end-inspiration and end-expiration, respectively) [16].
Renal blood flow assessment
Ultrasound evaluation of renal blood flow was performed within 24 h from starting of MV. All the measurements were taken by a single well-trained anesthesiologist with certified experience (FA) on the right kidney with the patient in semi-recumbent position (30°), through a posterolateral approach. Color Doppler images were used to identify the interlobar vessels. An interlobar or arcuate artery was selected for pulse wave Doppler measurements and RRI was calculated as:
$$\text{peak}\ \text{systolic}\ \text{velocity}-\text{end}\ \text{diastolic}\ \text{velocity}/\text{peak}\ \text{systolic}\ \text{velocity}.$$
A representative Renal Resistivity Index measurement technique performed is showed in Fig. 1.
An RRI > 0.7 was deemed pathological. [11,12,13]
The RVF pattern was classified as continuous, biphasic or monophasic [11]. Under physiological conditions, the RVF pattern is continuous, whereas during renal congestion it becomes biphasic or even monophasic [11].
For both RRI and RVF three measurements were obtained over 3 cardiac cycles and the mean value was recorded for analysis.
Secondary outcomes
The occurrence of AKI, as well as need for renal replacement therapy (RRT), was recorded. Further, we investigated the ability of RRI to predict the occurrence of AKI and the need of RRT. AKI was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines as an increase in serum creatinine of 0.3 mg/dL within 48 h, an increase in serum creatinine to 1.5 times the baseline value present within the previous 7 days, or a urinary output <0.5 mL/kg/h for 6 h [17]. Indications for RRT were serum urea >150 mg/dL, severe hyperkalemia (over 6 mmol/L or with sign of electrocardiogram abnormalities), urine output <200 mL/die, fluid overload despite diuretic treatment [18].
Statistical analysis
Categorical data are presented as frequencies and percentages, while continuous variables as mean ± standard deviation or medians with interquartile range, as appropriate. The Shapiro-Wilk test was used to assess the assumption of normality. Categorical data were compared using the χ2 test or Fisher exact test as appropriate. Mann-Whitney U tests was used to compare continuous variables. Pearson correlation with R square was used to analyze the correlation. Receiver operator characteristic (ROC) curves were used to analyze the ability of RRI to predict AKI. ROC curve analyses are reported as AUROC with 95% confidence interval (95% CI). Optimal cut-off scores were determined using Youden’s Index. Differences in repeated measurements in the two groups were analyzed using Friedman’s rank analysis. Statistical analyses were performed using SPSS 25.0 statistical software (SPSS Inc., Chicago, IL). For each statistical test a 2-tailed test was performed and a p value of 0.05 was considered statistically significant.
Sample size
Using the upper confidence interval for the population variance approach to the sample size calculation a pilot sample size between 20 and 40 correspond to standardized effect sizes of 0.4 and 0.7 (for 90% power based on a standard sample size calculation). According to this issue, 30 patients (15 for each group) were included in the study.