Semi-supervised COVID-19 volumetric pulmonary lesion estimation on CT images using probabilistic active contour and CNN segmentation.

Purpose: A semi-supervised two-step methodology is proposed to obtain a volumetric estimation of COVID-19-related lesions on Computed Tomography (CT) images. Methods: First, damaged tissue was segmented from CT images using a probabilistic active contours approach. Second, lung parenchyma was extracted using a previously trained U-Net. Finally, volumetric estimation of COVID-19 lesions was calculated considering the lung parenchyma masks.Our approach was validated using a publicly available dataset containing 20 CT COVID-19 images previously labeled and manually segmented. Then, it was applied to 295 COVID-19 patients CT scans admitted to an intensive care unit. We compared the lesion estimation between deceased and survived patients for high and low-resolution images. Results: A comparable median Dice similarity coefficient of 0.66 for the 20 validation images was achieved. For the 295 images dataset, results show a significant difference in lesion percentages between deceased and survived patients, with a p-value of 9.1 × 10-4 in low-resolution and 5.1 × 10-5 in high-resolution images. Furthermore, the difference in lesion percentages between high and low-resolution images was 10 % on average. Conclusion: The proposed approach could help estimate the lesion size caused by COVID-19 in CT images and may be considered an alternative to getting a volumetric segmentation for this novel disease without the requirement of large amounts of COVID-19 labeled data to train an artificial intelligence algorithm. The low variation between the estimated percentage of lesions in high and low-resolution CT images suggests that the proposed approach is robust, and it may provide valuable information to differentiate between survived and deceased patients.

Evaluation of the usefulness of vitamin D as a predictor of mortality in patients with COVID-19.

INTRODUCTION: One of the functions of vitamin D is to regulate respiratory epithelium inflammatory response; therefore, deficiency of this vitamin in the context of COVID-19 could constitute a predictive biomarker of the disease outcome. OBJECTIVE: To evaluate the usefulness of vitamin D for predicting mortality in patients with COVID-19. METHODS: Observational, retrospective study in which 154 patients diagnosed with COVID-19 were included, out of whom 111 survived and 43 died. Vitamin D concentration was determined in all of them. RESULTS: A log-rank p-value < 0.032 was obtained for survival when vitamin D concentration was used as a categorical variable (≤ 20 ng/mL and > 20 ng/mL). On Cox proportional analysis, age and vitamin D concentration were shown to be risk factors associated with mortality in patients with COVID-19 (age: HR = 1.036, 95% CI = 1.016-1.058, p < 0.001; vitamin D: HR (≤ 20 ng/mL and > 20 ng/mL) = 0.478, 95% CI = 0.237-0.966, p < 0.040). CONCLUSION: Age and vitamin D concentration were predictive factors for mortality in COVID-19-infected patients.

INTRODUCCIÓN: Una de las funciones de la vitamina D es regular la respuesta inflamatoria del epitelio respiratorio; por ello, la deficiencia de esa vitamina en el contexto de COVID-19 podría constituir un biomarcador preditivo del desenlace de COVID-19. OBJETIVO: Evaluar la utilidad de la vitamina D para predecir la mortalidad en pacientes con COVID-19. MÉTODOS: Estudio observacional y retrospectivo en el que se incluyeron 154 pacientes con diagnóstico de COVID-19, de los cuales 111 sobrevivieron y 43 fallecieron. En todos se determinó la concentración de vitamina D. RESULTADOS: Se obtuvo un valor log-rank de p < 0.032 para la supervivencia al utilizar la concentración de vitamina D como variable categórica (≤ 20 ng/mL y > 20 ng/mL). Mediante análisis proporcional de Cox se encontró que la edad y concentración de vitamina D mostraron ser factores de riesgo asociados a la mortalidad en pacientes con COVID-19 (edad: HR = 1.036, IC 95 % = 1.016-1.058, p < 0.001; vitamina D: HR ≤ 20 ng/mL y > 20 ng/mL = 0.478, IC 95 % = 0.237-0.966, p < 0.040). CONCLUSIÓN: La edad y la concentración de vitamina D constituyeron factores predictivos de mortalidad en pacientes infectados por COVID-19.

Evaluación de la utilidad de la vitamina D como predictor de mortalidad en pacientes con COVID-19 / Evaluation of the usefulness of vitamin D as a predictor of mortality in patients with COVID-19

Resumen Introducción: Una de las funciones de la vitamina D es regular la respuesta inflamatoria del epitelio respiratorio; por ello, la deficiencia de esa vitamina en el contexto de COVID-19 podría constituir un biomarcador preditivo del desenlace de COVID-19. Objetivo: Evaluar la utilidad de la vitamina D para predecir la mortalidad en pacientes con COVID-19. Métodos: Estudio observacional y retrospectivo en el que se incluyeron 154 pacientes con diagnóstico de COVID-19, de los cuales 111 sobrevivieron y 43 fallecieron. En todos se determinó la concentración de vitamina D. Resultados: Se obtuvo un valor log-rank de p < 0.032 para la supervivencia al utilizar la concentración de vitamina D como variable categórica (≤ 20 ng/mL y > 20 ng/mL). Mediante análisis proporcional de Cox se encontró que la edad y concentración de vitamina D mostraron ser factores de riesgo asociados a la mortalidad en pacientes con COVID-19 (edad: HR = 1.036, IC 95 % = 1.016-1.058, p < 0.001; vitamina D: HR ≤ 20 ng/mL y > 20 ng/mL = 0.478, IC 95 % = 0.237-0.966, p < 0.040). Conclusión: La edad y la concentración de vitamina D constituyeron factores predictivos de mortalidad en pacientes infectados por COVID-19.

Abstract Introduction: One of the functions of vitamin D is to regulate respiratory epithelium inflammatory response; therefore, deficiency of this vitamin in the context of COVID-19 could constitute a predictive biomarker of the disease outcome. Objective: To evaluate the usefulness of vitamin D for predicting mortality in patients with COVID-19. Methods: Observational, retrospective study in which 154 patients diagnosed with COVID-19 were included, out of whom 111 survived and 43 died. Vitamin D concentration was determined in all of them. Results: A log-rank p-value < 0.032 was obtained for survival when vitamin D concentration was used as a categorical variable (≤ 20 ng/mL and > 20 ng/mL). On Cox proportional analysis, age and vitamin D concentration were shown to be risk factors associated with mortality in patients with COVID-19 (age: HR = 1.036, 95% CI = 1.016-1.058, p < 0.001; vitamin D: HR [≤ 20 ng/mL and > 20 ng/mL] = 0.478, 95% CI = 0.237-0.966, p < 0.040). Conclusion: Age and vitamin D concentration were predictive factors for mortality in COVID-19-infected patients.

Prospective predictive performance comparison between clinical gestalt and validated COVID-19 mortality scores.

Most COVID-19 mortality scores were developed at the beginning of the pandemic and clinicians now have more experience and evidence-based interventions. Therefore, we hypothesized that the predictive performance of COVID-19 mortality scores is now lower than originally reported. We aimed to prospectively evaluate the current predictive accuracy of six COVID-19 scores and compared it with the accuracy of clinical gestalt predictions. 200 patients with COVID-19 were enrolled in a tertiary hospital in Mexico City between September and December 2020. The area under the curve (AUC) of the LOW-HARM, qSOFA, MSL-COVID-19, NUTRI-CoV, and NEWS2 scores and the AUC of clinical gestalt predictions of death (as a percentage) were determined. In total, 166 patients (106 men and 60 women aged 56±9 years) with confirmed COVID-19 were included in the analysis. The AUC of all scores was significantly lower than originally reported: LOW-HARM 0.76 (95% CI 0.69 to 0.84) vs 0.96 (95% CI 0.94 to 0.98), qSOFA 0.61 (95% CI 0.53 to 0.69) vs 0.74 (95% CI 0.65 to 0.81), MSL-COVID-19 0.64 (95% CI 0.55 to 0.73) vs 0.72 (95% CI 0.69 to 0.75), NUTRI-CoV 0.60 (95% CI 0.51 to 0.69) vs 0.79 (95% CI 0.76 to 0.82), NEWS2 0.65 (95% CI 0.56 to 0.75) vs 0.84 (95% CI 0.79 to 0.90), and neutrophil to lymphocyte ratio 0.65 (95% CI 0.57 to 0.73) vs 0.74 (95% CI 0.62 to 0.85). Clinical gestalt predictions were non-inferior to mortality scores, with an AUC of 0.68 (95% CI 0.59 to 0.77). Adjusting scores with locally derived likelihood ratios did not improve their performance; however, some scores outperformed clinical gestalt predictions when clinicians' confidence of prediction was <80%. Despite its subjective nature, clinical gestalt has relevant advantages in predicting COVID-19 clinical outcomes. The need and performance of most COVID-19 mortality scores need to be evaluated regularly.

The low-harm score for predicting mortality in patients diagnosed with COVID-19: A multicentric validation study.

Objective: We sought to determine the accuracy of the LOW-HARM score (Lymphopenia, Oxygen saturation, White blood cells, Hypertension, Age, Renal injury, and Myocardial injury) for predicting death from coronavirus disease 2019) COVID-19. Methods: We derived the score as a concatenated Fagan's nomogram for Bayes theorem using data from published cohorts of patients with COVID-19. We validated the score on 400 consecutive COVID-19 hospital admissions (200 deaths and 200 survivors) from 12 hospitals in Mexico. We determined the sensitivity, specificity, and predictive values of LOW-HARM for predicting hospital death. Results: LOW-HARM scores and their distributions were significantly lower in patients who were discharged compared to those who died during their hospitalization 5 (SD: 14) versus 70 (SD: 28). The overall area under the curve for the LOW-HARM score was 0.96, (95% confidence interval: 0.94-0.98). A cutoff > 65 points had a specificity of 97.5% and a positive predictive value of 96%. Conclusions: The LOW-HARM score measured at hospital admission is highly specific and clinically useful for predicting mortality in patients with COVID-19.

[The process of death in the intensive care unit (ICU). From a medical, thanatological and legislative point of view]. / El proceso de muerte en la unidad de cuidados intensivos (UCI). Punto de vista médico, tanatológico y legislativo.

Traditional goals in the intensive care unit are to reduce morbidity and mortality. Despite medical and technological advances, death in the intensive care unit remains commonplace and the modern critical care team should be familiar with palliative care and legislation in Mexico. Preserving the dignity of patients, avoiding harm, and maintaining communication with the relatives is fundamental. There is no unique, universally accepted technical approach in the management of the terminal critical care patient, so it is important to individualize each case and define objectives together under the legal framework in Mexico.