The Kigali modification of the berlin definition: a new epidemiological tool for ARDS?

Lazzeri, Chiara; Peris, Adriano

doi:10.21037/jtd.2016.03.84

Cited by 20 publications

(13 citation statements)

References 14 publications

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“…con lo cual Riviello y colaboradores decidieron ajustar con SaFi los criterios de Berlín para el diagnóstico de SDRA con la llamada modificación de Kigali y así estimar la incidencia y desenlaces del SDRA en un hospital de Ruanda, con lo cual se definió el SDRA con Opacidades alveolares bilaterales en la radiografía de tórax o el ultrasonido, e hipoxemia definida con una SpO2/FiO2 < 315, con lo que se puede hacer diagnóstico de SDRA en medios de escasos recursos. Sin embargo, aún faltan más estudios para su validación en el diagnóstico de esta entidad (Lazzeri & Peris, 2016;Riviello et al, 2017;Riviello et al, 2016) Existen formas lineales y no lineales para calcular la PaO2 a partir de la SpO2. Severinghaus (Severinghaus, 1979) propuso una ecuación para determinar la saturación de oxígeno a partir de la PaO2 por lo que luego Ellis (Ellis, 1989) elaboró una fórmula para determinar la PaO2 a partir de la SpO2.…”

Section: Safiunclassified

Respiratory Mechanics

Jian-xin

Yang

et al. 2021

Respiratory Monitoring in Mechanical Ventilation

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SIGLAS ABREVIATURAS C. vital Capacidad vital C.S. respiratorio Compliance del sistema respiratorio CaO2 Concentración arterial de oxígeno CcO2 Contenido capilar de oxígeno CO2 Dióxido de carbono COVID-19 Enfermedad causada por el coronavirus 2019 (por sus siglas en inglés) Cpulmón "Compliance" o distensibilidad del pulmón CRF Capacidad residual funcional CvO2 Contenido venoso de oxígeno Cw Caja torácica por sus silgas en inglés

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Section: Safiunclassified

Respiratory Mechanics

Jian-xin

Yang

et al. 2021

Respiratory Monitoring in Mechanical Ventilation

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“…The Kigali definition of acute respiratory distress syndrome (ARDS) was used in those who were not intubated and mechanically ventilated. The Kigali definition of ARDS is as follows: new or worsening respiratory symptoms occurring within one week of clinical insult; bilateral opacities not fully explained by effusions, lobar/lung collapse, or nodules by chest radiograph or ultrasound; and SpO 2 /FiO 2 < 315 [7]. Based on these criteria, all of our patients who were not mechanically ventilated met the criteria for ARDS with SpO 2 /FiO 2 well below the cutoff of 315.…”

Section: Resultsmentioning

confidence: 97%

A Case Series of Secondary Spontaneous Pneumomediastinum and Pneumothorax in Severe COVID-19 Pneumonia

Staiano¹,

Patel²,

Green³

et al. 2022

Cureus

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IntroductionPneumomediastinum and pneumothorax are uncommon complications in COVID-19 patients. The exact prevalence, etiology, and outcomes are not well known. We report a case series of patients in our institution with COVID-19 related pneumomediastinum and pneumothorax and address these questions. MethodsWe conducted a single-center retrospective chart review of patients admitted at our institution with a positive polymerase chain reaction (PCR) confirming the diagnosis of COVID-19. A cohort of 500 potential study candidates was identified, of whom eight were investigated. Demographic data, hospital course, patient co-morbidities, and outcome data were collected. ResultsEight patients were included in our study who were identified as having an event (i.e., pneumomediastinum and/or pneumothorax) during the specified timeframe. Overall, 62% of patients were on high-flow nasal cannula with an average FiO 2 of >70%. The average oxygen saturation//fraction of inspired oxygen (SpO 2 /FiO 2 ) ratio leading up to an event was 113.7286 (range: 101.11-130.66), and all of the patients not on mechanical ventilation met the criteria for acute respiratory distress syndrome (ARDS) based on the Kigali definition with SpO 2 /FiO 2 < 315. The three patients who developed an event while requiring mechanical ventilation both had PaO 2 /FiO 2 < 100, consistent with severe ARDS at the time of an event. The mean time in days, counted from the day of hospital admission until an event, was 10 days (range: 3-23 days). None of the cases had documented pulmonary parenchymal disease prior to developing COVID-19. To the best of our knowledge, these events were not iatrogenic in nature. ConclusionSecondary spontaneous pneumomediastinum and pneumothorax are rare albeit well-documented phenomena in hospitalized patients with COVID-19 infection. Interestingly, the majority of patients in our study were on high-flow nasal cannula at the time of an event. The majority of previously published data on this topic are on those who required positive pressure ventilation; however, there have been more recent papers that also describe these events in non-mechanically ventilated patients. The exact pathophysiology remains unknown, but it is likely multifactorial, and additional studies are needed to further evaluate this phenomenon.

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“…A potential pitfall to consistent use of the S/F ratio to stratify hypoxic respiratory failure is the relative lack of knowledge of the proper cutoffs that guide interventions. The Kigali protocol provides cutoffs, and prior studies have shown linear and nonlinear relationships to P/F, which can be used [ 24 ]. We created a partial dependence plot to illustrate the cutoff at which mortality sharply increases, and this appears to be at an S/F ratio of about 200 ( Figure 6 ).…”

Section: Discussionmentioning

confidence: 99%

Mortality Prediction Using SaO2/FiO2 Ratio Based on eICU Database Analysis

Patel

Singh

Zarbiv

et al. 2021

Critical Care Research and Practice

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Purpose. PaO2 to FiO2 ratio (P/F) is used to assess the degree of hypoxemia adjusted for oxygen requirements. The Berlin definition of Acute Respiratory Distress Syndrome (ARDS) includes P/F as a diagnostic criterion. P/F is invasive and cost-prohibitive for resource-limited settings. SaO2/FiO2 (S/F) ratio has the advantages of being easy to calculate, noninvasive, continuous, cost-effective, and reliable, as well as lower infection exposure potential for staff, and avoids iatrogenic anemia. Previous work suggests that the SaO2/FiO2 ratio (S/F) correlates with P/F and can be used as a surrogate in ARDS. Quantitative correlation between S/F and P/F has been verified, but the data for the relative predictive ability for ICU mortality remains in question. We hypothesize that S/F is noninferior to P/F as a predictive feature for ICU mortality. Using a machine-learning approach, we hope to demonstrate the relative mortality predictive capacities of S/F and P/F. Methods. We extracted data from the eICU Collaborative Research Database. The features age, gender, SaO2, PaO2, FIO2, admission diagnosis, Apache IV, mechanical ventilation (MV), and ICU mortality were extracted. Mortality was the dependent variable for our prediction models. Exploratory data analysis was performed in Python. Missing data was imputed with Sklearn Iterative Imputer. Random assignment of all the encounters, 80% to the training (n = 26690) and 20% to testing (n = 6741), was stratified by positive and negative classes to ensure a balanced distribution. We scaled the data using the Sklearn Standard Scaler. Categorical values were encoded using Target Encoding. We used a gradient boosting decision tree algorithm variant called XGBoost as our model. Model hyperparameters were tuned using the Sklearn RandomizedSearchCV with tenfold cross-validation. We used AUC as our metric for model performance. Feature importance was assessed using SHAP, ELI5 (permutation importance), and a built-in XGBoost feature importance method. We constructed partial dependence plots to illustrate the relationship between mortality probability and S/F values. Results. The XGBoost hyperparameter optimized model had an AUC score of .85 on the test set. The hyperparameters selected to train the final models were as follows: colsample_bytree of 0.8, gamma of 1, max_depth of 3, subsample of 1, min_child_weight of 10, and scale_pos_weight of 3. The SHAP, ELI5, and XGBoost feature importance analysis demonstrates that the S/F ratio ranks as the strongest predictor for mortality amongst the physiologic variables. The partial dependence plots illustrate that mortality rises significantly above S/F values of 200. Conclusion. S/F was a stronger predictor of mortality than P/F based upon feature importance evaluation of our data. Our study is hypothesis-generating and a prospective evaluation is warranted. Take-Home Points. S/F ratio is a noninvasive continuous method of measuring hypoxemia as compared to P/F ratio. Our study shows that the S/F ratio is a better predictor of mortality than the more widely used P/F ratio to monitor and manage hypoxemia.

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The Kigali modification of the berlin definition: a new epidemiological tool for ARDS?

Cited by 20 publications

References 14 publications

Respiratory Mechanics

Respiratory Mechanics

A Case Series of Secondary Spontaneous Pneumomediastinum and Pneumothorax in Severe COVID-19 Pneumonia

Mortality Prediction Using SaO2/FiO2 Ratio Based on eICU Database Analysis

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