Early nutritional risk detection and intervention in COVID-19 hospitalized patients through the implementation of electronic automatized alarms

Abstract

Introduction: Hospitalized COVID-19 patients may present acute malnutrition which could influence morbidity and mortality. In the first wave of the pandemic severe weight loss was observed in many hospitalized patients. This pilot study evaluates the usefulness of an electronic automatized alarm for the early quantification of a low food intake as a predictor of the risk of malnutrition using COVID-19 disease as a model of severe illness.

Methods: Observational prospective nutritional screening with a daily automatized warning message to the Endocrinology and Nutrition Service provided by the Information Systems. All adult patients admitted for COVID-19 from November 2020 to February 2021 were included. When diet intake was <50% during consecutive 48h, an automated message was generated identifying the patient as "at nutritional risk (NR)" and additional specialist nutritional evaluation and therapy was performed within the next 24h.

Results: 205 patients out of 1176 (17.4%) were detected by automatized alarm and were considered as presenting high NR; 100% were concordant by the validated nutritional screening SNAQ. Nutritional support after detection was: 77.6% dietary adaptation+oral supplements; 9.3% enteral nutrition (EN); 1.5% parenteral nutrition (PN); 1% EN+PN and 10.7% no intervention is performed due to an end-of-life situation. Median weight loss during admission was 2.5kg (p25 0.25-p75: 6kg). Global mortality was 6.7% while in those detected by automatized alarm was 31.5%.

Conclusions: The implementation of an electronic NR screening tool was feasible and allowed the early nutritional assessment and intervention in COVID-19 hospitalized patients and can be useful in patients hospitalized for other pathologies.

Keywords: Alarmas electrónicas automatizadas; COVID-19; Desnutrición; Detección temprana del riesgo nutricional; Early nutritional risk detection; Electronic automatized alarms; Malnutrition.