Resilience and quality of life in patients who underwent mechanical ventilation due to COVID-19, one year after discharge: a cross-sectional study.

BACKGROUND: Patients with COVID-19 often experience severe long-term sequelae. This study aimed to assess resilience and Quality of Life (QoL) of patients who underwent mechanical ventilation due to COVID-19, one year after discharge. METHODS: This cross-sectional study enrolled patients who received mechanical ventilation for severe COVID-19 and were assessed one-year post-discharge. Participants completed a structured questionnaire via telephone comprising the Connor-Davidson Resilience Scale (CD-RISC) and the Post-COVID-19 Functional Status scale (PCFS). To establish the association between QoL and resilience, Spearman correlations were calculated between the PCFS and the CD-RISC. Linear regression models were adjusted to evaluate which factors were associated with QoL, with the total score of PCFS as the dependent variable. RESULTS: A total of 225 patients were included in the analysis. The CD-RISC had a median score of 83 (IQR 74-91). The PCFS results showed that 61.3% (n = 138) of the patients were able to resume their daily activities without limitations. Among them, 37.3% (n = 84) were classified as Grade 0 and 24% (n = 54) as Grade 1. Mild and moderate functional limitations were found in 33.7% of the patients, with 24.8% (n = 56) classified as Grade 2 and 8.8% (n = 20) as Grade 3. Severe functional limitations (Grade 4) were observed in 4.8% (n = 11) of the patients. High CD-RISC scores were associated with lower levels of PCFS score (p < 0.001). CONCLUSIONS: In this cohort of critically ill patients who underwent mechanical ventilation due to COVID-19, 38% of patients experienced a significant decline in their QoL one year after hospital discharge. Finally, a high level of resilience was strongly associated with better QoL one year after discharge.

Correlation between the radial artery resistance index and the systemic vascular resistance index: a cross-sectional study.

INTRODUCTION: Ultrasound measurement of the radial resistance index (RRI) in the anatomical snuffbox has been proposed as a useful method for assessing the systemic vascular resistance index (SVRI). This study aims to establish the correlation between SVRI measured by pulmonary artery catheter (PAC) and RRI. METHODS: A cross-sectional study included all consecutive patients undergoing postoperative (POP) cardiac surgery with hemodynamic monitoring using PAC. Hemodynamic assessment was performed using PAC, and RRI was measured with ultrasound in the anatomical snuffbox. The Pearson correlation test was used to establish the correlation between RRI and SVRI measured using PAC. Hemodynamic behavior concerning RRI with a cutoff point of 1.1 (described to estimate under SVRI) was examined. Additionally, consistency between two evaluators was assessed for RRI using the intraclass correlation coefficient and Bland-Altman analysis. RESULTS: A total of 35 measurements were obtained. The average cardiac index (CI) was 2.73 ± 0.64 L/min/m², and the average SVRI was 1967.47 ± 478.33 dyn·s·m²/cm5. The correlation between RRI and SVRI measured using PAC was 0.37 [95% CI 0.045-0.62]. The average RRI was 0.94 ± 0.11. RRI measurements > 1.1 had a mean SVRI of 2120.79 ± 673.48 dyn·s·m²/cm5, while RRI measurements ≤ 1.1 had a mean SVRI of 1953.1 ± 468.17 dyn·s·m²/cm5 (p = 0.62). The consistency between evaluators showed an intraclass correlation coefficient of 0.88 [95% CI 0.78-0.93], and Bland-Altman analysis illustrated adequate agreement of RRI evaluators. CONCLUSIONS: For patients in cardiac surgery POP, the correlation between the SVRI measured using PAC and the RRI measured in the anatomical snuffbox is low. Using the RRI as a SVRI estimator for patients is not recommended in this clinical scenario.

Prediction model for in-hospital mortality in patients at high altitudes with ARDS due to COVID-19.

INTRODUCTION: The diagnosis of acute respiratory distress syndrome (ARDS) includes the ratio of pressure arterial oxygen and inspired oxygen fraction (P/F) ≤ 300, which is often adjusted in locations more than 1,000 meters above sea level (masl) due to hypobaric hypoxemia. The main objective of this study was to develop a prediction model for in-hospital mortality among patients with ARDS due to coronavirus disease 2019 (COVID-19) (C-ARDS) at 2,600 masl with easily available variables at patient admission and to compare its discrimination capacity with a second model using the P/F adjusted for this high altitude. METHODS: This study was an analysis of data from patients with C-ARDS treated between March 2020 and July 2021 in a university hospital located in the city of Bogotá, Colombia, at 2,600 masl. Demographic and laboratory data were extracted from electronic records. For the prediction model, univariate analyses were performed to screen variables with p <0.25. Then, these variables were automatically selected with a backward stepwise approach with a significance level of 0.1. The interaction terms and fractional polynomials were also examined in the final model. Multiple imputation procedures and bootstraps were used to obtain the coefficients with the best external validation. In addition, total adjustment of the model and logistic regression diagnostics were performed. The same methodology was used to develop a second model with the P/F adjusted for altitude. Finally, the areas under the curve (AUCs) of the receiver operating characteristic (ROC) curves of the two models were compared. RESULTS: A total of 2,210 subjects were included in the final analysis. The final model included 11 variables without interaction terms or nonlinear functions. The coefficients are presented excluding influential observations. The final equation for the model fit was g(x) = age(0.04819)+weight(0.00653)+height(-0.01856)+haemoglobin(-0.0916)+platelet count(-0.003614)+ creatinine(0.0958)+lactate dehydrogenase(0.001589)+sodium(-0.02298)+potassium(0.1574)+systolic pressure(-0.00308)+if moderate ARDS(0.628)+if severe ARDS(1.379), and the probability of in-hospital death was p (x) = e g (x)/(1+ e g (x)). The AUC of the ROC curve was 0.7601 (95% confidence interval (CI) 0.74-0, 78). The second model with the adjusted P/F presented an AUC of 0.754 (95% CI 0.73-0.77). No statistically significant difference was found between the AUC curves (p value = 0.6795). CONCLUSION: This study presents a prediction model for patients with C-ARDS at 2,600 masl with easily available admission variables for early stratification of in-hospital mortality risk. Adjusting the P/F for 2,600 masl did not improve the predictive capacity of the model. We do not recommend adjusting the P/F for altitude.

Clinical characteristics and mortality associated with COVID-19 at high altitude: a cohort of 5161 patients in Bogotá, Colombia.

BACKGROUND: There are few data on the clinical outcomes of patients with coronavirus disease 2019 (COVID-19) in cities over 1000 m above sea level (masl). OBJECTIVES: To describe the clinical characteristics and mortality of patients with COVID-19 treated at a high complexity hospital in Bogotá, Colombia, at 2640 masl. METHODS: This was an observational study of a cohort including 5161 patients with confirmed COVID-19 infection from 19 March 2020 to 30 April 2021. Demographic data, laboratory values, comorbidities, oxygenation indices, and clinical outcomes were collected. Data were compared between survivors and nonsurvivors. An independent predictive model was performed for mortality and invasive mechanical ventilation (IMV) using classification and regression trees (CART). RESULTS: The median cohort age was 66 years (interquartile range (IQR) 53-77), with 1305 patients dying (25%) and 3856 surviving (75%). The intensive care unit (ICU) received 1223 patients (24%). Of 898 patients who received IMV, 613 (68%) of them perished. The ratio of partial pressure arterial oxygen (PaO2) to fraction inspired oxygen (FiO2), or the P/F ratio, upon ICU admission was 105 (IQR 77-146) and 137 (IQR 91-199) in the deceased and survivors, respectively. The CART model showed that the need for IMV, age greater than 79 years, ratio of oxygen saturation (SaO2) to FiO2, or the S/F ratio, less than 259, and lactate dehydrogenase (LDH) greater than 617 U/L at admission were associated with a greater probability of death. CONCLUSION: Among more than 5000 patients with COVID-19 treated in our hospital, mortality at hospital discharge was 25%. Older age, low S/F ratio, and high LDH at admission were predictors of mortality.