Lost Weigh Due to Visus Now Start Gaining Again
Clin Nutr. 2022 Apr; 40(4): 2420–2426.
COVID-19 is associated with clinically significant weight loss and hazard of malnutrition, independent of hospitalisation: A postal service-hoc analysis of a prospective cohort study
Luigi Di Filippo
aSchool of Medicine, Vita-Salute San Raffaele University, Milan, Italian republic
Rebecca De Lorenzo
aSchool of Medicine, Vita-Salute San Raffaele Academy, Milan, Italy
Marta D'Amico
aSchoolhouse of Medicine, Vita-Salute San Raffaele University, Milan, Italia
Valentina Sofia
aSchoolhouse of Medicine, Vita-Salute San Raffaele University, Milan, Italia
Luisa Roveri
bIRCCS San Raffaele Scientific Plant, Milan, Italy
Roberto Mele
bIRCCS San Raffaele Scientific Found, Milan, Italy
Alessandro Saibene
bIRCCS San Raffaele Scientific Found, Milan, Italian republic
Patrizia Rovere-Querini
aSchool of Medicine, Vita-Salute San Raffaele University, Milan, Italian republic
bIRCCS San Raffaele Scientific Institute, Milan, Italian republic
Caterina Conte
bIRCCS San Raffaele Scientific Establish, Milan, Italy
Received 2022 Jun 23; Accepted 2022 Oct 21.
- Supplementary Materials
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Supplementary Table 1
GUID: 0B4E48DD-D084-46A8-B689-FA7F7A87DD3F
Supplementary Tabular array 2
GUID: 2176ECC6-055C-4CDC-B298-92940C210954
Abstract
Background & aims
Coronavirus disease 2022 (COVID-19) may associate with clinical manifestations, ranging from alterations in odor and gustation to astringent respiratory distress requiring intensive care, that might associate with weight loss and malnutrition. Nosotros aimed to assess the incidence of unintentional weight loss and malnutrition in COVID-xix survivors.
Methods
In this postal service-hoc analysis of a prospective observational accomplice written report, we enrolled all adult (age ≥eighteen years) patients with a confirmed diagnosis of COVID-19 who had been discharged abode from either a medical ward or the Emergency Department of San Raffaele University Hospital, and were re-evaluated after remission at the Outpatient COVID-xix Follow-Up Clinic of the same Institution from April 7, 2020, to May 11, 2020. Demographic, anthropometric, clinical and biochemical parameters upon admission were prospectively nerveless. At follow-up, anthropometrics, the mini nutritional assessment screening and a visual analogue calibration for appetite were assessed.
Results
A total of 213 patients were included in the analysis (33% females, median historic period 59.0 [49.5–67.9] years, seventy% overweight/obese upon initial assessment, 73% hospitalised). Lx-one patients (29% of the total, and 31% of hospitalised patients vs. 21% of patients managed at home, p = 0.14) had lost >v% of initial body weight (median weight loss vi.5 [v.0–9.0] kg, or eight.1 [6.ane–10.nine]%). Patients who lost weight had greater systemic inflammation (C-reactive protein 62.nine [29.0–129.v] vs.48.7 [16.one–96.3] mg/dL; p = 0.02), impaired renal function (23.vii% vs. eight.7% of patients; p = 0.003) and longer disease duration (32 [27–41] vs. 24 [21–30] days; p = 0.047) as compared with those who did not lose weight. At multivariate logistic regression analysis, only disease duration independently predicted weight loss (OR 1.05 [1.01–i.x] p = 0.022).
Conclusions
COVID-xix might negatively impact body weight and nutritional status. In COVID-19 patients, nutritional evaluation, counselling and treatment should exist implemented at initial assessment, throughout the form of illness, and afterward clinical remission.
Keywords: COVID-19, Weight loss, Malnutrition, Nutritional evaluation, SARS-CoV2, Outpatient management
1. Introduction
Coronavirus disease 2022 (COVID-19), caused past Severe Astute Respiratory Syndrome Coronavirus 2 (SARS-CoV-two), has spread apace worldwide [ane]. COVID-19 patients present primarily with fever, dry cough, and fatigue or myalgia [2]. Clinical manifestations vary widely, ranging from asymptomatic forms to – peculiarly in older and/or polymorbid patients - acute respiratory distress syndrome (ARDS) requiring hospitalisation, assisted ventilation, and intensive care unit (ICU) access, with high bloodshed risk [3]. ICU stay, polymorbidity, and older age are factors that associate with loftier hazard and incidence of malnutrition [[4], [5], [half dozen], [vii]]. In patients with astringent COVID-19 hyperinflammation with massive release of inflammatory cytokines [8,9], as well as use of mechanical ventilation, either not-invasive or invasive, and prolonged infirmary stay could farther increase the take chances of malnutrition.
Patients with mild COVID-xix managed at dwelling might likewise suffer from malnutrition. Alterations of aroma and gustatory modality, as well every bit fatigue and lack of appetite, are reported every bit very prevalent symptoms in COVID-19 patients [10] that could affect food intake. Confinement at home and COVID-19 symptoms may limit the amount of concrete activity, leading to loss of lean mass [11]. These factors, on tiptop of a systemic inflammatory response, might result in malnutrition even in not-hospitalised patients. Nevertheless, no data are available on the impact of COVID-19 on nutritional status.
We sought to evaluate the incidence of unintentional weight loss and malnutrition in COVID-19 survivors who were either hospitalised or managed at habitation and re-evaluated later on clinical remission.
2. Materials and methods
2.1. Report blueprint
This was a post-hoc assay of data collected for the COVID-BioB study, a large prospective observational investigation performed at San Raffaele University Infirmary, a tertiary wellness-intendance hospital in Milan, Italia. The study protocol complies with the Annunciation of Helsinki, was approved by the Infirmary Ethics Committee (protocol no. 34/int/2020), and was registered on ClinicalTrials.gov ({"type":"clinical-trial","attrs":{"text":"NCT04318366","term_id":"NCT04318366"}}NCT04318366). Full description of patient management and clinical protocols were previously published (16). Signed informed consent was obtained from all patients participating in this report. We included adult (age ≥18 years) patients with a confirmed diagnosis of COVID-19 who had been discharged habitation from either a medical ward or the Emergency Department (ED) of San Raffaele Academy Hospital, and were re-evaluated later on remission at the Outpatient COVID-19 Follow-Up Clinic of the same Institution from April seven, 2020, to May 11, 2022 (Supplementary Fig. 1). Confirmed COVID-xix was defined as positive real-fourth dimension reverse-transcriptase polymerase concatenation reaction (RT-PCR) from a nasal and/or throat swab together with signs, symptoms, and/or radiological findings suggestive of COVID-19 pneumonia. Remission was divers as two negative RT-PCR from a nasal and/or throat swab performed 24 h autonomously, and no symptoms. But patients with available anthropometrics (weight and peak) recorded upon admission (to the ED or, if not available and just for hospitalised patients, to the medical ward) were included in the analyses. Patients admitted for other reasons and later diagnosed with superimposed SARS-CoV-2 infection were excluded.
two.two. Data collection
Data were nerveless from medical chart review or directly past patient interview and entered in a dedicated electronic case record form (eCRF) specifically developed for the COVID-BioB study. Prior to the analysis, data were cross-checked with medical charts and verified by information managers and clinicians for accuracy. The following variables were collected for all patients: age, sex, body mass index (BMI, calculated as the ratio of weight in kilograms [kg] divided by height in squared metres), PaOtwo/FiO2 (calculated every bit the ratio between the arterial partial pressure level of oxygen measured on arterial blood gas analysis and the fraction of inspired oxygen), plasma glucose (mg/dL), estimated glomerular filtration rate (eGFR, equally estimated by the CKD-EPI equation and expressed as ml/min/1.73 mii), haemoglobin, lymphocyte and neutrophil counts (x109/L), lactate dehydrogenase (LDH, U/Fifty), and loftier-sensitivity C-reactive poly peptide (CRP, mg/dL) on ED admission, summit CRP during hospital stay, comorbidities (including history of hypertension, diabetes mellitus, dyslipidaemia, ischaemic heart affliction, and active cancer) and clinical outcome (discharge from ED or infirmary ward, admission to ICU the during hospital stay). Measuring weight and height on admission was not feasible due to the workload for nurses and physicians during the peak of the pandemic and the need for contact and airborne precautions in the hospital. Therefore, weight and peak on access were self-reported past patients. Meridian measured at the follow-upwardly visit was subsequently used to calculate baseline BMI for the present analysis. Disease elapsing was defined as the time from the diagnosis of SARS-Cov-ii infection past RT-PCR from a nasal and/or throat swab to the time of remission (ii negative RT-PCR from a nasal and/or throat swab).
Follow-upwards outpatient visits were scheduled approximately three weeks after discharge, and included a complete internal medicine cess (collection of medical history, measurement of vital signs, physical examination), and nutritional evaluation (body weight measured to the nearest 0.ane kg using a balance axle scale, elevation measured to the nearest 0.1 cm using a wall-mounted stadiometer, mini nutritional assessment [MNA] screening and ambition cess using a visual counterpart scale [VAS] ranging from 0 to 100 mm) [12,xiii]. Weight loss was defined as a reduction >5% from initial body weight. At the follow-upwardly visit patients underwent a neurological assessment during which symptoms at disease onset were recorded. Patients were also specifically questioned by the neurologist about whether they had experienced taste and olfactory property disturbances at disease onset.
ii.3. Statistical analysis
Descriptive statistics were obtained for all study variables. Continuous variables were expressed as medians [25th – 75th percentile]. Categorical variables were summarised as counts and percentages. Fisher exact exam or χ2 test and Mann–Whitney U tests were employed to decide the statistical significance of differences in proportions and medians, respectively. All statistical tests were two-sided. A p-value of <0.05 was considered statistically significant. Univariate and multivariate logistic regression analyses were used to guess adjusted odds ratios (ORs) of weight loss with 95% confidence intervals (CIs) in the whole group and in the subgroup of hospitalised patients. Subgroup analysis was not performed for non-hospitalised patients due to the relatively small number of subjects in this group. Demographic and clinical characteristics potentially associated with weight loss were tested in univariate models. All variables that emerged as predictors (p < 0.05) at univariate assay were used as covariates in the multivariate model. Sex and age were retained in the model regardless of their p value at univariate analysis to control for their effect. Missing data were non imputed. Statistical analysis was conducted using IBM SPSS Statistics (IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp.).
3. Results
A full of 213 patients were included in the present analysis (Supplementary Fig. 1). Approximately ane tertiary of patients were females (33.3%), and median historic period was 59.0 [49.5–67.9] years. Median disease elapsing, equally estimated past the time from diagnosis to negative swab, was 30 [[25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38]] days. Patient characteristics upon admission to the ED are summarized in Table 1 .
Table 1
Patient characteristics upon admission to the Emergency Department (whole population and comparison between patients managed at dwelling and hospitalised patients).
| All 213 | Hospitalised 73.2% (156) | Non-Hospitalised 26.8% (57) | p value | Missing | |
|---|---|---|---|---|---|
| Historic period, yrs | 59.0 (49.5–67.nine) | 61 (53–69) | 51 (40–sixty) | <0.001 | – |
| Female, % (n.) | 33.3% (71) | 28.8% (45) | 45.6% (26) | 0.022 | – |
| Race, % (northward.) | |||||
| White | 97.7% (208) | 98.vii% (154) | 94.7% (54) | 0.010 | – |
| Asian | 0.9% (ii) | 1.3% (two) | 0% (0) | ||
| Black | i.4% (3) | 0% (0) | 5.iii% (three) | ||
| Hypertension, % (n.) | 36.0% (76) | 40.0% (62) | 25.0% (14) | 0.045 | 2 |
| Coronary artery disease, % (n.) | half-dozen.six% (14) | 6.4% (10) | vii.ane% (4) | one.0 | two |
| Diabetes Mellitus, % (due north.) | eleven.iv% (24) | 12.ix% (20) | vii.ane% (4) | 0.245 | two |
| COPD, % (n.) | 2.4% (5) | iii.two% (5) | 0% (0) | 0.328 | 2 |
| CKD, % (north.) | 2.4% (5) | 3.2% (five) | 0% (0) | 0.328 | 2 |
| Malignancy, % (north.) | 1.four% (iii) | 1.3% (2) | 1.eight% (1) | 1.0 | 2 |
| BMI, kg/yard2 | 27.1 (24.7–31.0) | 27.9 (25.1–31.5) | 25.7 (24.2–30.4) | 0.025 | – |
| BMI category, % (northward.) | |||||
| Underweight | 1.nine% (4) | one.ix% (3) | 1.8% (1) | 0.10 | – |
| Normal weight | 27.7% (59) | 23.one% (36) | 40.4% (23)∗ | ||
| Overweight | twoscore.viii% (87) | 44.two% (69) | 31.half-dozen% (18) | ||
| Obesity | 29.half-dozen% (63) | 30.viii% (48) | 26.3% (fifteen) | ||
| Hyposmia, % (n.) | 38.1% (67) | 37.4% (49) | 40.0% (18) | 0.757 | 37b |
| Hypogeusia, % (n.) | 43.two% (76) | 45.0% (59) | 29.8% (17) | 0.396 | 37b |
| Fevera, % (n.) | 45.2% (xc) | l.0% (72) | 32.vii% (18) | 0.029 | 14 |
| SpOtwo, % | 95 (92–97) | 94 (91–96) | 97 (96–98) | <0.001 | 7 |
| PaO2/FiO2 ratio | 314 (270–360) | 300 (252–333) | 377 (342–420) | <0.001 | 28b |
| CRP, mg/dl | 49.iii (19.9–99.nine) | 62.4 (31.0–115.ii) | xiv.3 (4.8–46.ii) | <0.001 | 5 |
| LDH, U/Fifty | 328 (260–412) | 360 (281–430) | 256 (211–324) | <0.001 | 28b |
| Hb, thousand/dL | 14.1 (12.ix–15.two) | 14.i (12.eight–15.ii) | fourteen.05 (12.three–15.ii) | 0.82 | one |
| Lym, 109/50 | 1.0 (0.vii–1.3) | i.0 (0.seven–1.3) | i.2 (ane.0–1.half dozen) | <0.01 | 15 |
| Neu, ten9/Fifty | 4.ane (three.ii–six.2) | iv.5 (3.five–6.8) | 3.5 (two.6–4.4) | <0.001 | 25b |
| Plasma glucose (mg/dL) | 103 (93–114) | 106 (96–117) | 98 (87–110) | <0.01 | 5 |
| AST, U/L | 41 (29–56) | 44 (32–61) | 29 (23–46) | <0.001 | 2 |
| ALT, U/50 | 36 (23–54) | 38 (23–57) | 29 (21–49) | 0.059 | 2 |
| eGFR < 60 mL/min/1.73m2 | 27 (12.9) | 25 (16.iii) | 2 (three.6) | 0.015 | iv |
Median BMI upon initial access was 27.1 [24.7–31.0] kg/mii with approximately 70% of patients having overweight or obesity. Only four patients (2%) were underweight. Well-nigh patients (73%) had been hospitalised and subsequently discharged from a infirmary ward. Of these, 5 (iii.2%) had been admitted to ICU during the hospital stay. The proportion of males was significantly greater amid hospitalised patients (χii: 5.28, p = 0.022), who were also significantly older (Mann–Whitney'southward U: 6484, p < 0.001) and heavier (Mann–Whitney'south U: 5.338, p = 0.025) than those discharged from the ED and managed at home (Tabular array one). As expected, hospitalised patients had more severe disease upon presentation (Table one), being more than often febrile (χ2: 4.79, p = 0.029) and having a worse respiratory function (Mann–Whitney's U: 1345.v and 688.5 for SpO2 and PaOtwo/FiO2 ratio, respectively, p < 0.001 for both) and more altered biochemical markers of disease action (Mann–Whitney'due south U: 6733.5, 4952.5, 2874 and 4771.five for CRP, LDH, accented lymphocyte and neutrophil counts, respectively, p < 0.01 for all; Tabular array 1). Renal function was also worse in hospitalised patients, with a significantly greater proportion of subjects having CKD stage iii or worse (χ2: 5.94, p = 0.015; Table ane). In that location were significantly more normal-weight individuals in the grouping managed at home (χ2: 6.22, p = 0.013; Table i), whereas the proportion of those with overweight/obesity was higher among hospitalised patients (χ2: 5.86, p = 0.015 for overweight/obesity combined). Having overweight/obesity was associated with 2-fold increased run a risk of beingness admitted to infirmary compared with being under-/normal-weight (odds ratio [OR] 2.18, 95% confidence interval [CI] 1.15–4.13; p = 0.017). Notwithstanding, overweight/obesity was not associated with an increased risk of being admitted to ICU (p = 0.997).
Median time from discharge to the follow-up outpatient visit was 23 [[23], [24], [25], [26], [27], [28], [29], [30]] days (26.5 [23.0–33.2] and 22.0 [xix.0–28.0] days for hospitalised and non-hospitalised patients, respectively; Mann–Whitney'southward U: 3311.5, p < 0.001). Median length of stay (LoS) for hospitalised patients was 8.0 [five.iii–12.0] days. Median BMI at follow-up was 26.iii kg/grandii [23.56–thirty.0]. Median per centum weight alter from initial admission to follow-up was −2.3 [-5.6 – 0.0] % in the whole cohort. Based on the MNA screening tool, one-hundred sixteen (54.seven%) and 14 (6.half-dozen%) patients were at risk of malnutrition or malnourished, respectively. The proportion of patients hospitalised was significantly greater among those at hazard of malnutrition versus those with normal nutritional condition (82.8% vs. 61.0%, respectively; χ2: 11.77, p = 0.001), just not significantly different from that in malnourished patients (64.3%; χtwo: 0.055, p = 0.81), likely due to the relatively pocket-sized number of patients in this category. All patients admitted to ICU were in the group at hazard of malnutrition (four.3% of the total).
60-one patients (29% of the total, and 31% of hospitalised patients vs. 21% of patients managed at dwelling, χ2: 2.19, p = 0.14) had lost >5% of initial torso weight (median weight loss 6.5 [5.0–9.0] kg, or viii.one [6.1–ten.9]%), with a median reduction of 2.3 [1.7–3.ii] BMI points. The percentage of patients who lost >ten% of initial body weight was similar between hospitalised and not-hospitalised patients (9.6% vs. 5.3%, Fisher'south exact examination: p = 0.41).
In order to identify factors associated with weight loss, we compared patients who did (WL) or did non (nWL) lose weight. No difference was establish between the two groups with respect to age, sex, pre-existing comorbidities and most of the biochemical parameters upon access (Tabular array 2 ). CRP levels on admission (Mann–Whitney'due south U: 5155, p = 0.02) were significantly higher in the WL group, where a significantly greater proportion of patients with reduced renal function was also observed (χ2: 8.54, p = 0.003; Table 2). Median disease duration was longer in patients who lost weight (Mann–Whitney's U: 5443.5, p = 0.047, Fig. one A). Similarly, among hospitalised patients, those who lost weight had a significantly longer LoS (Mann–Whitney's U: 3400, p = 0.006; Fig. iB). No difference was institute in ambition VAS scores (55 [41–70] vs. 55 [40–78] mm in patients with or without weight loss, respectively; Isle of man–Whitney's U: 2059, p = 0.89) at the follow-upwardly visit.
Table 2
Comparison between patients with or without weight loss.
| Weight loss 28.6% (61) | No weight loss 71.iv% (152) | p value | Missing | |
|---|---|---|---|---|
| Age, yrs | 59.7 (51.0–69.0) | 57.5 (49.0–67.0) | 0.66 | – |
| Female, % (n.) | 34.4% (21) | 32.nine% (fifty) | 0.83 | – |
| Race, % (n.) | ||||
| White | 100% (61) | 96.7% (147) | 0.18 | – |
| Asian | 0% (0) | 1.3% (2) | ||
| Black | 0% (0) | 2.0% (3) | ||
| Hypertension, % (n.) | 36.7% (22) | 35.eight% (54) | 0.ninety | 2 |
| Coronary artery disease, % (n.) | 10.0% (6) | v.iii%(8) | 0.22 | ii |
| Diabetes mellitus, % (n.) | 10.0% (6) | 11.9% (xviii) | 0.69 | ii |
| COPD, % (due north.) | iii.3% (ii) | two.0% (3) | 0.62 | 2 |
| CKD, % (north.) | v.0% (3) | 1.4% (2) | 0.14 | 2 |
| Malignancy, % (north.) | one.7% (1) | 1.iii% (2) | 1.0 | 2 |
| BMI, kg/mii | 27.five (25.6–32.two) | 27.1 (24.iii–30.4) | 0.207 | – |
| BMI category, % (northward.) | ||||
| Underweight | 0% (0) | 2.6% (4) | 0.18 | – |
| Normal weight | 21.3% (thirteen) | xxx.3% (46) | ||
| Overweight | 47.5% (29) | 38.2% (58) | ||
| Obesity | 31.1% (19) | 28.9% (44) | ||
| Hyposmia, % (due north.) | forty.iv% (21) | 37.1% (46) | 0.68 | 37b |
| Hypogeusia, % (n.) | 46.2% (24) | 41.ix% (52) | 0.60 | 37b |
| Fevera, % (northward.) | 41.viii% (23) | 46.5% (67) | 0.55 | 14 |
| SpOii, % | 95 (91–96) | 95 (93–97) | 0.09 | 7 |
| PaO2/FiO2 ratio | 307 (273–347) | 324 (265–367) | 0.56 | 28b |
| CRP, mg/dl | 62.9 (29.0–129.5) | 48.seven (16.1–96.3) | 0.02 | v |
| Summit CRP, mg/dL | 104.ii (57.0–184.6) | 62.9 (41.3–144.5) | 0.05 | six |
| LDH, U/L | 340 (275–459) | 325 (254–401) | 0.sixteen | 28b |
| Hb, g/dL | 14.0 (12.7–15.iii) | 14.ii (13.0–15.two) | 0.47 | 1 |
| Lym, 109/L | 0.7 (1.0–i.3) | 0.8 (1.0–1.iii) | 0.71 | fifteen |
| Neu, 109/Fifty | 4.5 (3.4–7.1) | 3.9 (2.9–vi.0) | 0.09 | 25 |
| Plasma glucose (mg/dL) | 104 (91–124) | 103 (94–113) | 0.501 | five |
| AST, U/Fifty | 43 (30–64) | 39 (28–55) | 0.34 | ii |
| ALT, U/L | 39 (23–57) | 34 (23–53) | 0.49 | 2 |
| eGFR < 60 mL/min/1.73m2 | 14 (23.7) | 13 (8.seven) | 0.003 | 4 |
| Hospitalisation, % (north.) | 80.3% (49) | 70.iv% (107) | 0.139 | – |
| ICU, % (northward.) | 8.2% (5) | – | – | – |
Disease duration (every bit estimated by the time from diagnosis to negative swab, all patients [A]) and length of stay (hospitalised patients [B]) in patients who did not lose weight and those who lost weight.
At multivariate logistic regression analysis including the whole cohort, only illness elapsing was identified as an independent predictor of weight loss (OR 1.05 [ane.01–ane.10]; Wald 5.29, p = 0.022) (Supplementary Table 1). At multivariate logistic regression analysis including merely hospitalised patients, LoS was the just independent predictor of weight loss (OR 1.07; CI 95% [1.00–1.xiii]; Wald iv.57, p = 0.03) (Supplementary Table 2).
4. Discussion
This is the offset study to assess the impact of COVID-19 on body weight and nutritional status in COVID-xix survivors either managed at habitation or as inpatients. We found that weight loss and hazard of malnutrition were highly prevalent in COVID-19 patients evaluated subsequently clinical remission. Nearly xxx% of patients lost more than five per cent of baseline body weight, and more than than half were at run a risk of malnutrition.
It is noteworthy that then many patients, independent of hospitalisation, had a weight loss >5%, i.e. the threshold used to diagnose cancer cachexia [fourteen]. Every bit suggested by the European Order of Enteral and Parenteral Nutrition (ESPEN), prevention, diagnosis and treatment of malnutrition should be considered in the management of COVID-19 patients to improve both brusk- and long-term prognosis [8]. However, the few studies bachelor so far have focused on hospitalised patients and selected populations, such as elderly or critically sick patients [15,16]. Our study expands the knowledge of the impact of COVID-19 on nutritional status to a broader population, with a wide range of ages and disease severity, spanning from patients with mild disease managed at dwelling house to inpatients with severe disease admitted to the ICU. We searched the literature for data on weight loss and malnutrition in like diseases (i.e. Middle Due east respiratory syndrome [MERS] and SARS), but could not find any published data for comparison with our findings. Well-nigh published data on the effects of acute diseases on nutritional status relate to critically ill patients. The inflammatory nature of COVID-nineteen and the global spread of the affliction provide a unique opportunity to study the furnishings of acute inflammatory illness of a wide range of severity on torso weight and nutritional status.
Several mechanisms may contribute to weight loss and malnutrition in COVID-19 patients. When comparison patients with or without weight loss, we found that those who lost weight had greater systemic inflammation (baseline CRP and, in hospitalised patients, peak CRP values), worse renal office (proportion of patients with an eGFR < lx mL/min/1.73 thousand2), and longer disease elapsing. Acute systemic inflammation securely affects several metabolic [17] and hypothalamic [18] pathways contributing to anorexia and decreased nutrient intake likewise as elevation of resting energy expenditure and increased muscle catabolism [xix]. Of annotation, acute inflammatory events can trigger persistent neuroinflammatory responses in vulnerable individuals, which may perpetuate inflammation and wasting fifty-fifty after the acute stage [18,xx]. Impaired renal function is an important risk factor for malnutrition, the prevalence of poly peptide-free energy wasting increasing with declining eGFR [21]. At multivariate analyses only illness duration and - in hospitalised patients - length of stay were significant independent predictors of weight loss, reflecting the importance of illness severity and inflammation to weight loss. In our cohort of COVID-19 patients, weight loss occurred in a relatively short fourth dimension (median disease elapsing: 32 [[27], [28], [29], [thirty], [31], [32], [33], [34], [35], [36], [37], [38], [39], [forty], [41]] days). This is consistent with previous studies showing that fifty-fifty brusque periods of bed balance induce marked reductions in muscle protein synthesis resulting in loss of skeletal muscle mass, both in middle-aged and elderly individuals [[22], [23], [24]]. Furthermore, malnutrition is strongly associated with loss of muscle mass and strength in both customs-dwelling and hospitalised individuals [25]. Although we did non measure trunk composition, it is likely that the weight loss observed in our cohort of COVID-19 patients was, at least in part, due to loss of lean body mass caused by bed rest or musculus disuse, both in hospitalised and non-hospitalised patients. This could negatively impact time to full recovery and patients' health status. It has been reported that patients with ARDS showroom an of import weight loss at hospital discharge, approximately 18% of their baseline body weight, mainly due to lean body mass loss [26]. Regain of body weight in the following year is mainly due to an increment in fat mass [27], which may bear negative implications for cardiovascular adventure and functional status. These might exist particularly relevant to COVID-nineteen patients, given the high prevalence of overweight and obesity reported hither and in other studies [28,29]. Our findings support an association between obesity and run a risk of hospital admission [30] but challenge the association between BMI and critical illness, consistent with recent data on patients hospitalised with COVID-xix in New York Metropolis [29]. Previous studies demonstrated that obesity is associated with increased take a chance of ARDS, merely lower risk of mortality [31]. This "obesity paradox" has also been observed in patients with obesity hospitalised for pneumonia in a non-ICU setting [32]. Pre-conditioning induced past the low-grade chronic inflammation associated with obesity has been postulated as a protective machinery against further insults to the lungs [33]. Increased availability of nutritional reserves protecting obese subjects against hypercatabolism is another possible explanation. This hypothesis is supported by the observation that early enteral nutrition in the ICU minimises or even abolishes the survival disadvantage for under- and normal-weight patients as compared with those in higher BMI categories [34] and by the finding that recent weight loss has a negative impact on mortality even in not-critically ill overweight and obese inpatients [35]. This suggests that weight loss should non exist allowed in the hospital setting, even in patients with obesity. The fact that patients with overweight/obesity lost a significant amount of weight and developed or were at take chances for malnutrition supports the ESPEN recommendation that individuals with obesity should exist screened for malnutrition and receive nutritional counselling, as malnutrition is defined non just by depression body mass but besides by unhealthy body composition and skeletal muscle mass [eight]. Sarcopenic obesity, i.e. the coexistence of excess fat mass and sarcopenia, is a prevalent and oftentimes underrecognized complication of obesity that may associate with worse clinical outcomes [36].
Other factors that were not specifically assessed but may have contributed to weight loss and risk of malnutrition in our cohort are medical treatments and mechanical ventilation in hospitalised patients [37,38]. Emotions such as fear and sadness may reduce the desire or motivation to swallow [39]. In patients managed at domicile, confinement may limit the access to food and/or the variety of food choices [xl] which, as in a fell bicycle, is a source of frustration, anxiety and acrimony [41], besides having direct implications for nutrition. Surprisingly, nosotros institute no association between alterations in smell and taste, which are known to increase malnutrition risk in cancer patients [42] and are highly prevalent in COVID-xix [10].
Finally, information technology is noteworthy that patients who lost weight in our cohort had not yet returned at the initial body weight at the follow-up visit (a median of 23 [[23], [24], [25], [26], [27], [28], [29], [30]] days since discharge). This highlights the need for nutritional evaluation and counselling/intervention not just at diagnosis or for hospitalised patients, merely also for those managed at dwelling and at follow-upwards, with a conscientious reassessment to monitor weight changes and nutritional status.
Our findings should exist interpreted in light of the limits of the report design. Patients evaluated in our study were COVID-19 survivors. We did not include patients with worse outcomes, i.e. those who died or were nonetheless hospitalised. It is plausible that the incidence and prevalence of weight loss and the risk of malnutrition amid COVID-nineteen patients are even greater than reported hither, reflecting a heavier nutritional burden. Further limits of our study are the post-hoc nature of our analysis and the use of patient-reported weight upon admission. Large accomplice studies suggest that self-reported weight is slightly underestimated [43,44]. Information technology is possible that we underestimated baseline BMI and the corporeality of weight lost. We did non assess body weight at hospital discharge nor body composition. During a fourth dimension of unprecedented workload for healthcare professionals, and given the restrictions imposed by the demand of isolating patients to prevent viral spread, the assessment of body weight and trunk composition was unfeasible. For the aforementioned reason, some baseline data were non recorded and were missing for the analyses. Information on taste and/or odour disturbances was missing for 17.4% of patients because the neurological assessment during which these symptoms were investigated was introduced one week after the get-go of the outpatient follow-up clinic. About all patients with sense of taste and/or smell disturbances at COVID-19 onset reported full recovery of symptoms, merely this information was not systematically recorded. A farther limitation is the lack of echo biochemical assessment at the follow-upwardly visit. This is because the follow-up evaluation at our Institution comprises a full general medical assessment including anthropometric measurements and the MNA screening. Patients with specific needs are referred to nutrition professionals for further assessment, and laboratory testing is requested based on individual clinical needs. At this fourth dimension, we were not able to assess the recovery charge per unit of nutritional status in COVID-19 survivors. Some patients reported partial regain of lost weight prior to the clinic visit, but most of them were unable to provide detailed data on weight changes. These information were not sufficient nor reliable for inclusion in the assay. The main scope of this first study was to depict the incidence of unintentional weight loss and malnutrition in COVID-19 survivors. Subsequent assessments of body weight and nutritional status including biochemical parameters will assist fill up this research gap. Further questions that remain open are • what nutritional screening strategies should be implemented for patients managed at domicile? • what kind of nutritional support/counselling should be provided in the outpatient and inpatient setting, and for the transition phase? • what are the consequences of COVID-19-associated weight loss on patient recovery? • what are the effects of COVID-19-associated weight loss on body composition?
In decision, we report, for the first fourth dimension to our knowledge, a very high incidence of weight loss and risk of malnutrition amongst COVID-nineteen survivors, independent of hospitalisation. The association of unintentional weight loss with worse clinical outcomes has long been recognised [[45], [46], [47]]. Implementing nutritional management strategies is crucial for hospitalised patients, especially those in the ICU or with older historic period and polymorbidity [8,48]. Still, our findings support the notion that even individuals managing or recovering from COVID-19 symptoms at home should receive counselling on how to maintain an acceptable intake of calories, poly peptide, and fluids [49]. Strategies such equally using remote nutritional screening tools recently developed for primary practise [50] should be implemented to improve the nutritional management of patients managed at home.
Funding sources
This inquiry did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. CC is supported by the European Foundation for the Study of Diabetes Mentorship Program 2019.
Argument of authorship
Conceptualization: LDF, CC, PRQ; Information curation: LDF, RDL, MDA, VS, CC; Formal analysis: LDF, CC; Investigation: LDF, RDL, CC; Methodology: LDF, CC, PRQ; Project administration: CC; Supervision: CC; Validation: RM, AS, PRQ, CC; Visualization: LDF, RDL, MDA, VS, RM, Equally, PRQ, CC; Writing - original typhoon: LDF, CC; Writing - review & editing: LDF, RDL, MDA, VS, RM, AS, PRQ, CC.
Conflict of interest
The authors have no competing interests to declare.
Footnotes
Appendix A. Supplementary data
The following are the Supplementary data to this commodity:
Supplementary Fig. 1
Study flow-chart.
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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7598735/
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