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.

Impact of COVID-19 pandemic on cardiovascular diseases hospitalisation, management and mortality in Switzerland.

BACKGROUND: COVID-19 pandemic led to a reduction in hospital admissions and intervention for other diseases in many countries. We aimed to assess the effect of COVID-19 pandemic on cardiovascular disease (CVD) hospitalisations, management and mortality in Switzerland. METHODS: Swiss hospital discharge and mortality data for period 2017-2020. CVD hospitalisations, CVD interventions and CVD mortality were assessed before (2017-2019) and during (2020) the pandemic. Expected numbers of admissions, interventions and deaths for 2020 were computed using simple linear regression model. RESULTS: Compared with 2017-2019, 2020 was characterised by a reduction of CVD admissions in age groups 65-84 and ≥85 by approximately 3700 and 1700 cases, respectively, and by an increase in the percentage of admissions with a Charlson index >8. The total number of CVD-related deaths decreased from 21 042 in 2017 to 19 901 in 2019, and increased to 20 511 in 2020, with an estimated excess of 1139 deaths. This increase was due to out-of-hospital deaths (+1342), while the number of in-hospital deaths decreased from 5030 in 2019 to 4796 in 2020, which concerned mostly subjects aged ≥85 years. The total number of admissions with cardiovascular interventions increased from 55 181 in 2017 to 57 864 in 2019, and decreased in 2020, with an estimated reduction of 4414 admissions; percutaneous transluminal coronary angioplasty (PTCA) was the exception, as the number and percentage of emergency admissions with PTCA increased. The preventive measures applied against COVID-19 inverted the seasonal pattern of CVD admissions, the highest number of admissions being found in summer and the lowest in winter. CONCLUSION: The COVID-19 pandemic led to a reduction in CVD hospital admissions, planned CVD interventions, an increase in total and out-of-hospital CVD deaths and a change in seasonal patterns.

Prevalence and predictors of psychological distress before, during, and after a COVID-19 pandemic wave in Switzerland, 2021.

There are concerns about acute and long-term mental health effects of the COVID-19 pandemic. This study examined the prevalence and predictors of psychological distress before, during, and after a pandemic wave in Switzerland, 2021. Prevalence of psychological distress was estimated in adults aged 35-96 years using the General Health Questionnaire-12 administered in June 2021 (Specchio-COVID19 cohort, N = 3965), and compared to values from 2003 to 2006 (CoLaus|PsyCoLaus cohort, N = 5667). Anxiety and depression were assessed from February to June 2021 using the Generalised Anxiety Disorder scale-2 and the Patient Health Questionnaire-2, respectively. Prevalence of psychological distress in June 2021, after the pandemic wave (16.0% [95% CI, 14.6%-17.4%]) was comparable to pre-pandemic levels (15.1% [14.0%-16.2%]). Anxiety and depression were highest at the start of the pandemic wave in February 2021, and declined from February to June with the relaxation of measures. Predictors of psychological distress included being younger, female, a single parent, unemployed, a change in working hours or job loss in the past 6 months, greater perceived severity and contagiousness of COVID-19, and self-reported post COVID-19. By June 2021, following a pandemic wave, prevalence of psychological distress in Switzerland was closer to pre-pandemic levels. These findings highlight the need for additional mental health support during times of stricter government policies relating to COVID-19; yet they also suggest that individuals can adapt relatively quickly to the changing context.

The cytokines HGF and CXCL13 predict the severity and the mortality in COVID-19 patients.

The objective of the present study was to identify biological signatures of severe coronavirus disease 2019 (COVID-19) predictive of admission in the intensive care unit (ICU). Over 170 immunological markers were investigated in a 'discovery' cohort (n = 98 patients) of the Lausanne University Hospital (LUH-1). Here we report that 13 out of 49 cytokines were significantly associated with ICU admission in the three cohorts (P < 0.05 to P < 0.001), while cellular immunological markers lacked power in discriminating between ICU and non-ICU patients. The cytokine results were confirmed in two 'validation' cohorts, i.e. the French COVID-19 Study (FCS; n = 62) and a second LUH-2 cohort (n = 47). The combination of hepatocyte growth factor (HGF) and C-X-C motif chemokine ligand 13 (CXCL13) was the best predictor of ICU admission (positive and negative predictive values ranging from 81.8% to 93.1% and 85.2% to 94.4% in the 3 cohorts) and occurrence of death during patient follow-up (8.8 fold higher likelihood of death when both cytokines were increased). Of note, HGF is a pleiotropic cytokine with anti-inflammatory properties playing a fundamental role in lung tissue repair, and CXCL13, a pro-inflammatory chemokine associated with pulmonary fibrosis and regulating the maturation of B cell response. Up-regulation of HGF reflects the most powerful counter-regulatory mechanism of the host immune response to antagonize the pro-inflammatory cytokines including CXCL13 and to prevent lung fibrosis in COVID-19 patients.