Association of Different Malnutrition Parameters and Clinical Outcomes among COVID-19 Patients: An Observational Study

A Novel Facet of In-Hospital Food Consumption Associated with Hospital Mortality in Patients with Scheduled Admission-Addition of a Study Protocol to Test the Existence of Effects of COVID-19 in the Same Study in the Post-COVID-19 Period

BACKGROUND

Humankind has faced unexperienced pandemic events since 2020. Since the COVID-19 pandemic has calmed down, we felt the need to verify whether in-hospital mortality had worsened compared to pre-pandemic conditions due to the COVID-19 pandemic.

OBJECTIVE

To test the hypothesis that daily food consumption is associated with in-hospital mortality during hospitalization and to provide baseline data to examine whether the effects of COVID-19 exist or not in post-pandemic period.

METHODS

All hospitalized patients staying in a single institution on the third Thursday of May, August, November, and the following February were included. Compared data: (1) among four seasons, (2) between age < 75 vs. ≥75 years, (3) between <75% vs. ≥75% of in-hospital food, and (4) logistic regression analysis to identify factors associated with in-hospital mortality.

RESULTS

In 365 inpatients, the following results were obtained: (1) no seasonality or age effect in in-hospital mortality, (2) the novel cutoff value of 75% of the hospital food requirement was used to identify poor in-hospital survivors, (3) logistic regression analysis showed low food consumption, with <75% of the hospital food requirement as the predictor of high in-hospital mortality.

CONCLUSIONS

A small eater of in-hospital food < 75% during hospitalization was associated with significantly higher in-hospital mortality in patients with scheduled hospitalization in the pre-pandemic period. Then, a study protocol is proposed to test the existence of the effects of COVID-19 in the same study in the post-COVID-19 period. This study protocol is, to our knowledge, the first proposal to test the effects of food consumption in the post-COVID-19 period on in-hospital mortality in the clinical nutritional areas.

Predictive value of multiple variable models including nutritional risk score (NRS 2002) on mortality and length of stay of patients with covid-19 infections. The INCOVO study

BACKGROUND AND AIMS

This study aimed at evaluating associations between nutritional status and outcomes in patients with Covid-19 and to identify statistical models including nutritional parameters associated with in-hospital mortality and length of stay.

METHODS

Data of 5707 adult patients hospitalized in the University Hospital of Lausanne between March 2020 and March 2021 were screened retrospectively 920 patients (35% female) with confirmed Covid-19 and complete data including nutritional risk score (NRS 2002), were included. This cohort was divided into three subgroups: NRS <3: no risk of malnutrition; NRS ≥3 to <5: moderate risk malnutrition; and NRS ≥5: severe risk of malnutrition. The primary outcome was the percentage of in-hospital deaths in the different NRS subgroups. The secondary outcomes were the length of hospital stay (LOS), the percentage of admissions to intensive care units (ICU), and the length of stay in the ICU (ILOS). Logistic regression was performed to identify risk factors associated with in-hospital mortality and hospital stay. Multivariate clinical-biological models were developed to study predictions of mortality and very long length of stay.

RESULTS

The mean age of the cohort was 69.7 years. The death rate was 4 times higher in the subgroup with a NRS ≥ 5 (44%), and 3 times higher with a NRS ≥ 3 to <5 (33%) compared to the patients with a NRS<3 (10%) (p < 0.001). LOS was significantly higher in the NRS ≥ 5 and NRS ≥ 3 to <5 subgroups (26.0 days; CI [21; 30.9]; and 24.9; CI [22.5; 27.1] respectively) versus 13.4; CI [12; 14.8] for NRS<3 (p < 0.001). The mean ILOS was significantly higher in the NRS ≥ 5 (5.9 days; versus 2.8 for NRS ≥ 3 to <5, and 1.58 for NRS<3 (p < 0.001)). In logistic regression, NRS ≥ 3 was significantly associated with the risk of mortality (OR: 4.8; CI [3.3; 7.1]; p < 0.001) and very long in-hospital stay (>12 days) (OR: 2.5; CI [1.9; 3.3]; p < 0.001). Statistical models that included a NRS ≥ 3 and albumin revealed to be strong predictors for mortality and LOS (area under the curve 0.800 and 0.715).

CONCLUSION

NRS was found to be an independent risk factor for in-hospital death and LOS in hospitalized Covid-19 patients. Patients with a NRS ≥ 5 had a significant increase in ILOS and mortality. Statistical models including NRS are strong predictors for an increased risk of death and LOS.

Systematic Review and Meta-Analysis: Malnutrition and In-Hospital Death in Adults Hospitalized with COVID-19

BACKGROUND

Malnutrition and increased malnutrition risk are frequently identified in hospitalized adults. The increase in hospitalization rates during the COVID-19 pandemic was accompanied by the documentation of adverse hospitalization outcomes in the presence of certain co-morbidities, including obesity and type 2 diabetes. It was not clear whether the presence of malnutrition increased in-hospital death in patients hospitalized with COVID-19.

OBJECTIVES

To estimate the effect of malnutrition on in-hospital mortality in adults hospitalized with COVID-19; and secondarily, to estimate the prevalence of malnutrition in adults hospitalized with malnutrition during the COVID-19 pandemic.

METHODS

EMBASE, MEDLINE, PubMed, Google Scholar, and Cochrane Collaboration databases were queried using the search terms malnutrition and COVID-19 and hospitalized adults and mortality. Studies were reviewed using the 14-question Quality Assessment Tool for Studies with Diverse Designs (QATSDD) (questions appropriate for quantitative studies). Author names; date of publication; country; sample size; malnutrition prevalence; malnutrition screening/diagnostic method; number of deaths in malnourished patients; and number of deaths in adequately nourished patients were extracted. Data were analyzed using MedCalc software v20.210 (Ostend, Belgium). The Q and I² tests were calculated; a forest plot was generated, and the pooled odds ratio (OR) with 95% confidence intervals (95%CI) were calculated using the random effects model.

RESULTS

Of the 90 studies identified, 12 were finally included in the meta-analysis. In the random effects model, malnutrition or increased malnutrition risk increased odds of in-hospital death by more than three-fold: OR 3.43 (95% CI 2.549-4.60), p < 0.001. The pooled prevalence estimate for malnutrition or increased malnutrition risk was 52.61% (95% CI 29.50-75.14%).

DISCUSSION AND CONCLUSIONS

It is clear that malnutrition is an ominous prognostic sign in patients hospitalized with COVID. This meta-analysis, which included studies from nine countries on four continents with data from 354,332 patients, is generalizable.

Prognostic Nutritional Index, Controlling Nutritional Status (CONUT) Score, and Inflammatory Biomarkers as Predictors of Deep Vein Thrombosis, Acute Pulmonary Embolism, and Mortality in COVID-19 Patients

Background: Numerous tools, including nutritional and inflammatory markers, have been evaluated as the predictors of poor outcomes in COVID-19 patients. This study aims to verify the predictive role of the prognostic nutritional index (PNI), CONUT Score, and inflammatory markers (monocyte to lymphocyte ratio (MLR), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic inflammatory index (SII), Systemic Inflammation Response Index (SIRI), and Aggregate Index of Systemic Inflammation (AISI)) in cases of deep vein thrombosis (DVT) and acute pulmonary embolism (APE) risk, as well as mortality, in COVID-19 patients. Methods: The present study was designed as an observational, analytical, retrospective cohort study, and included 899 patients over the age of 18 who had a COVID-19 infection, confirmed through real time-polymerase chain reaction (RT-PCR), and were admitted to the County Emergency Clinical Hospital and Modular Intensive Care Unit of UMFST “George Emil Palade” of Targu Mures, Romania between January 2020 and March 20212. Results: Non-Surviving patients were associated with a higher incidence of chronic kidney disease (p = 0.01), cardiovascular disease (atrial fibrillation (AF) p = 0.01; myocardial infarction (MI) p = 0.02; peripheral arterial disease (PAD) p = 0.0003), malignancy (p = 0.0001), tobacco (p = 0.0001), obesity (p = 0.01), dyslipidemia (p = 0.004), and malnutrition (p < 0.0001). Multivariate analysis showed that both nutritional and inflammatory markers had a high baseline value and were all independent predictors of adverse outcomes for all enrolled patients (for all p < 0.0001). The presence of PAD, malignancy, and tobacco, were also independent predictors of all outcomes. Conclusions: According to our findings, higher MLR, NLR, PLR, SII, SIRI, AISI, CONUT Score, and lower PNI values at admission strongly predict DVT risk, APE risk, and mortality in COVID-19 patients. Moreover, PAD, malignancy, and tobacco, all predicted all outcomes, while CKD predicts APE risk and mortality, but not the DVT risk.