The modified NUTRIC score (mNUTRIC) is associated with increased 28-day mortality in critically ill COVID-19 patients: Internal validation of a prediction model.

BACKGROUND: High prevalence of malnutrition was found in critically ill COVID-19 patients. The modified Nutrition Risk in the Critically ill (mNUTRIC) score is frequently used for nutritional risk assessment in intensive care unit (ICU) COVID-19 patients. The aim of this study was to investigate the role of mNUTRIC score to predict 28-day mortality in critically ill COVID-19 patients admitted to ICU. METHODS: A cohort of consecutive COVID-19 critically ill patients admitted to ICU was retrospectively evaluated and the nutritional risk was assessed with the use of mNUTRIC score. A multivariable Cox regression model to predict 28-day mortality was therefore developed including the mNUTRIC as a covariate. Internal validation was performed using the bootstrap resampling technique to reduce possible bias in the estimated risks. The performance of the prediction model was assessed via calibration and discrimination. RESULTS: A total of 98 critically ill COVID-19 patients with a median age of 66 years (56-73 IQR), 81 (82.7%) males were included in this study. A high nutritional risk (mNUTRIC ≥5 points) was observed in 41.8% of our critically ill COVID-19 patients while a low nutritional risk (mNUTRIC <5 points) was observed in 58.2%. Forty-five patients (45.9%) died within 28 days after ICU admission. In multivariable model after internal validation, mNUTRIC ≥5 (optimism adjusted HR 2.38, 95% CI 1.08-5.25, p = 0.02) and high-sensitivity C-reactive protein values (CRP) (optimism adjusted HR 1.02, 95% CI 1.01-1.07, p = 0.005) were independent predictors of 28-day mortality. CONCLUSIONS: A high prevalence of malnutrition as revealed by mNUTRIC was found in our critically ill COVID-19 patients once admitted in ICU. After adjustment for covariables, mNUTRIC ≥5 and CRP levels were independently associated with 28-day mortality in critically ill COVID-19 patients. The final model revealed good discrimination and calibration. Nutritional risk assessment is essential for the management of critically ill COVID-19 patients as well as for outcome prediction.

Prediction of 28-day mortality in critically ill patients with COVID-19: Development and internal validation of a clinical prediction model.

BACKGROUND: COVID-19 pandemic has rapidly required a high demand of hospitalization and an increased number of intensive care units (ICUs) admission. Therefore, it became mandatory to develop prognostic models to evaluate critical COVID-19 patients. MATERIALS AND METHODS: We retrospectively evaluate a cohort of consecutive COVID-19 critically ill patients admitted to ICU with a confirmed diagnosis of SARS-CoV-2 pneumonia. A multivariable Cox regression model including demographic, clinical and laboratory findings was developed to assess the predictive value of these variables. Internal validation was performed using the bootstrap resampling technique. The model's discriminatory ability was assessed with Harrell's C-statistic and the goodness-of-fit was evaluated with calibration plot. RESULTS: 242 patients were included [median age, 64 years (56-71 IQR), 196 (81%) males]. Hypertension was the most common comorbidity (46.7%), followed by diabetes (15.3%) and heart disease (14.5%). Eighty-five patients (35.1%) died within 28 days after ICU admission and the median time from ICU admission to death was 11 days (IQR 6-18). In multivariable model after internal validation, age, obesity, procaltitonin, SOFA score and PaO2/FiO2 resulted as independent predictors of 28-day mortality. The C-statistic of the model showed a very good discriminatory capacity (0.82). CONCLUSIONS: We present the results of a multivariable prediction model for mortality of critically ill COVID-19 patients admitted to ICU. After adjustment for other factors, age, obesity, procalcitonin, SOFA and PaO2/FiO2 were independently associated with 28-day mortality in critically ill COVID-19 patients. The calibration plot revealed good agreements between the observed and expected probability of death.

Practical Advices for Treating Chronic Pain in the Time of COVID-19: A Narrative Review Focusing on Interventional Techniques.

BACKGROUND: Since the management of chronic pain has become even more challenging secondary to the occurrence of SARS-CoV-2 outbreaks, we developed an exhaustive narrative review of the scientific literature, providing practical advices regarding the management of chronic pain in patients with suspected, presumed, or confirmed SARS-CoV-2 infection. We focused particularly on interventional procedures, where physicians are in closer contact with patients. METHODS: Narrative Review of the most relevant articles published between June and December of 2020 that focused on the treatment of chronic pain in COVID-19 patients. RESULTS: Careful triage of patients is mandatory in order to avoid overcrowding of hospital spaces. Telemedicine could represent a promising tool to replace in-person visits and as a screening tool prior to admitting patients to hospitals. Opioid medications can affect the immune response, and therefore, care should be taken prior to initiating new treatments and increasing dosages. Epidural steroids should be avoided or limited to the lowest effective dose. Non urgent interventional procedures such as spinal cord stimulation and intrathecal pumps should be postponed. The use of personal protective equipment and disinfectants represent an important component of the strategy to prevent viral spread to operators and cross-infection between patients due to the SARS-CoV-2 outbreaks.