Comparisons between the clinical outcomes of early and late enteral nutrition and mortality risk factors for pediatric burns

Abstract Introduction We aimed to determine the incidence of enteral feed intolerance (EFI), factors associated with intolerance, and to assess the influence of intolerance on key nutritional and clinical outcomes in critically ill patients. Methods We used data from The International Nutrition Survey database collected from 2007–2014. Included patients were mechanically ventilated critically ill adults who remained in the Intensive Care Unit for at least 72 hours and received some enteral nutrition during the first 12 days of their ICU stay. Data collected included nutritional prescription, adequacy, and clinical otucomes. We defined EFI as feeding is interrupted due to one of the following reasons: high gastric residual volumes (GRV), increased abdominal girth or abdominal distension, vomiting/emesis, diarrhea or subjective discomfort. Logistic regression controlling for covariates (year, region, sex, APACHE II score, admission type by primary diagnosis, BMI and baseline caloric and protein prescriptions) was used to determine risk factors for intolerance and its clinical significance. Results The current analysis included 15, 918 patients from 775 ICUs. Of these, 4, 036 (25.4%) had at least one episode of EFI. The rate rose from just below 1% on day 1 to a peak of 6% on day 4 and 5 and declined daily thereafter (See Figure). Factors predictive of EFI are shown in Table 1. Admission diagnosis was significantly predictive of EFI with patients with burn injuries showing the highest incidence. After controlling for the covariates,patients who had EFI received about 10% less EN adequacycompared to patients without of EFI (see Table 2). The mortality rate in EFI patients was 31% vs. 24% among patients who did not have EFI (OR=1.5 [95% CI, 1.4–1.6] p< 0.0001). Patients who had EFI had fewer ventilator free days, longer ICU lengths of stay, and longer time to discharge alive (all p< 0.0001) (See Table 2). Conclusions Intolerance occurs frequently during enteral nutrition in the critically ill and is associated with poorer nutritional and clinical outcomes. The identification, prevention, and optimal management in burn injured patients may improve nutrition delivery and clinical outcomes in this important “at risk” population. Applicability of Research to Practice To improve the nutrition therapy in burns patients.

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Mortality risk factors in war-related pediatric burns: A comparative study among two distinct populations

Burns ◽

10.1016/j.burns.2018.02.014 ◽

2018 ◽

Vol 44 (5) ◽

pp. 1210-1227 ◽

Cited By ~ 2

Author(s):

Sevgi Buyukbese Sarsu ◽

Aydin Budeyri

Keyword(s):

Risk Factors ◽

Comparative Study ◽

Mortality Risk ◽

Pediatric Burns

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Indications and practice of enteral nutrition

Orvosi Hetilap ◽

10.1556/oh.2014.30066 ◽

2014 ◽

Vol 155 (51) ◽

pp. 2028-2033 ◽

Cited By ~ 1

Author(s):

Judit Hallay ◽

Dániel Nagy ◽

Béla Fülesdi

Keyword(s):

Risk Factors ◽

Treatment Outcome ◽

Enteral Nutrition ◽

Hospital Stay ◽

Length Of Hospital Stay ◽

Nutrition Therapy ◽

Present Review ◽

Hospitalised Patients ◽

Impact On Treatment ◽

Efficacy Of Treatment

Malnutrition in hospitalised patients has a significant and disadvantageous impact on treatment outcome. If possible, enteral nutrition with an energy/protein-balanced nutrient should be preferred depending on the patient’s condition, type of illness and risk factors. The aim of the nutrition therapy is to increase the efficacy of treatment and shorten the length of hospital stay in order to ensure rapid rehabilitation. In the present review the authors summarize the most important clinical and practical aspects of enteral nutrition therapy. Orv. Hetil., 2014, 155(51), 2028–2033.

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Faculty Opinions recommendation of Mortality risk factors in chronic haemodialysis patients with infective endocarditis.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.13715.471210 ◽

2006 ◽

Author(s):

Ralph Corey

Keyword(s):

Risk Factors ◽

Infective Endocarditis ◽

Mortality Risk ◽

Chronic Haemodialysis

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Burden of Respiratory Syncytial Virus Disease and Mortality Risk Factors in Argentina

The Pediatric Infectious Disease Journal ◽

10.1097/inf.0000000000002271 ◽

2019 ◽

Vol 38 (6) ◽

pp. 589-594 ◽

Cited By ~ 3

Author(s):

Angela Gentile ◽

María Florencia Lucion ◽

María del Valle Juarez ◽

María Soledad Areso ◽

Julia Bakir ◽

...

Keyword(s):

Risk Factors ◽

Respiratory Syncytial Virus ◽

Mortality Risk ◽

Virus Disease ◽

Respiratory Syncytial Virus Disease ◽

Syncytial Virus

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Mortality Risk Factors in Chronic Renal Failure Patients after Coronary Artery Bypass Grafting

Renal Failure ◽

10.1080/08860220701573525 ◽

2007 ◽

Vol 29 (7) ◽

pp. 823-828 ◽

Cited By ~ 5

Author(s):

Beril Akman ◽

Ayse Bilgic ◽

Gulsah Sasak ◽

Siren Sezer ◽

Atilla Sezgin ◽

...

Keyword(s):

Risk Factors ◽

Renal Failure ◽

Coronary Artery ◽

Chronic Renal Failure ◽

Coronary Artery Bypass Grafting ◽

Coronary Artery Bypass ◽

Mortality Risk ◽

Artery Bypass ◽

Bypass Grafting ◽

Artery Bypass Grafting

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699 Sleep Health Traits and COVID-19: Mortality Risk from the UK Biobank

SLEEP ◽

10.1093/sleep/zsab072.697 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A273-A273

Author(s):

Xi Zheng ◽

Ma Cherrysse Ulsa ◽

Peng Li ◽

Lei Gao ◽

Kun Hu

Keyword(s):

Risk Factors ◽

Sleep Apnea ◽

Sleep Duration ◽

Sex Education ◽

Mortality Risk ◽

Self Report ◽

Severe Illness ◽

Uk Biobank ◽

Sleep Health ◽

The Uk

Abstract Introduction While there is emerging evidence for acute sleep disruption in the aftermath of coronavirus disease 2019 (COVID-19), it is unknown whether sleep traits contribute to mortality risk. In this study, we tested whether earlier-life sleep duration, chronotype, insomnia, napping or sleep apnea were associated with increased 30-day COVID-19 mortality. Methods We included 34,711 participants from the UK Biobank, who presented for COVID-19 testing between March and October 2020 (mean age at diagnosis: 69.4±8.3; range 50.2–84.6). Self-reported sleep duration (less than 6h/6-9h/more than 9h), chronotype (“morning”/”intermediate”/”evening”), daytime dozing (often/rarely), insomnia (often/rarely), napping (often/rarely) and presence of sleep apnea (ICD-10 or self-report) were obtained between 2006 and 2010. Multivariate logistic regression models were used to adjust for age, sex, education, socioeconomic status, and relevant risk factors (BMI, hypertension, diabetes, respiratory diseases, smoking, and alcohol). Results The mean time between sleep measures and COVID-19 testing was 11.6±0.9 years. Overall, 5,066 (14.6%) were positive. In those who were positive, 355 (7.0%) died within 30 days (median = 8) after diagnosis. Long sleepers (>9h vs. 6-9h) [20/103 (19.4%) vs. 300/4,573 (6.6%); OR 2.09, 95% 1.19–3.64, p=0.009), often daytime dozers (OR 1.68, 95% 1.04–2.72, p=0.03), and nappers (OR 1.52, 95% 1.04–2.23, p=0.03) were at greater odds of mortality. Prior diagnosis of sleep apnea also saw a two-fold increased odds (OR 2.07, 95% CI: 1.25–3.44 p=0.005). No associations were seen for short sleepers, chronotype or insomnia with COVID-19 mortality. Conclusion Data across all current waves of infection show that prior sleep traits/disturbances, in particular long sleep duration, daytime dozing, napping and sleep apnea, are associated with increased 30-day mortality after COVID-19, independent of health-related risk factors. While sleep health traits may reflect unmeasured poor health, further work is warranted to examine the exact underlying mechanisms, and to test whether sleep health optimization offers resilience to severe illness from COVID-19. Support (if any) NIH [T32GM007592 and R03AG067985 to L.G. RF1AG059867, RF1AG064312, to K.H.], the BrightFocus Foundation A2020886S to P.L. and the Foundation of Anesthesia Education and Research MRTG-02-15-2020 to L.G.

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INCIDENCE OF OBESITY, ACQUIRED CARDIOVASCULAR RISK FACTORS & ADVERSE CLINICAL OUTCOMES IN PATIENTS WITH REPAIREDTETRALOGY OFFALLOT(TOF)INCIDENCE OF OBESITY, ACQUIRED CARDIOVASCULAR RISK FACTORS & ADVERSE CLINICAL OUTCOMES IN PATIENTS WITH REPAIREDTETRALOGY OF FALLOT

Journal of the American College of Cardiology ◽

10.1016/s0735-1097(21)02952-1 ◽

2021 ◽

Vol 77 (18) ◽

pp. 1595

Author(s):

Justin M. Harrell ◽

Vincent Sorrell ◽

Andrew Leventhal ◽

Preeti Ramachandran ◽

Douglas Schneider

Keyword(s):

Risk Factors ◽

Cardiovascular Risk ◽

Cardiovascular Risk Factors ◽

Clinical Outcomes

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Risk factors and clinical outcomes associated with blood culture contamination

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2021.111 ◽

2021 ◽

pp. 1-7

Author(s):

Justin M. Klucher ◽

Kevin Davis ◽

Mrinmayee Lakkad ◽

Jacob T. Painter ◽

Ryan K. Dare

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Blood Culture ◽

Hospital Mortality ◽

Clinical Outcomes ◽

Tertiary Care ◽

Blood Cultures ◽

Hospital Charges ◽

Patient Specific ◽

Contaminated Blood

Abstract Objective: To determine patient-specific risk factors and clinical outcomes associated with contaminated blood cultures. Design: A single-center, retrospective case-control risk factor and clinical outcome analysis performed on inpatients with blood cultures collected in the emergency department, 2014–2018. Patients with contaminated blood cultures (cases) were compared to patients with negative blood cultures (controls). Setting: A 509-bed tertiary-care university hospital. Methods: Risk factors independently associated with blood-culture contamination were determined using multivariable logistic regression. The impacts of contamination on clinical outcomes were assessed using linear regression, logistic regression, and generalized linear model with γ log link. Results: Of 13,782 blood cultures, 1,504 (10.9%) true positives were excluded, leaving 1,012 (7.3%) cases and 11,266 (81.7%) controls. The following factors were independently associated with blood-culture contamination: increasing age (adjusted odds ratio [aOR], 1.01; 95% confidence interval [CI], 1.01–1.01), black race (aOR, 1.32; 95% CI, 1.15–1.51), increased body mass index (BMI; aOR, 1.01; 95% CI, 1.00–1.02), chronic obstructive pulmonary disease (aOR, 1.16; 95% CI, 1.02–1.33), paralysis (aOR 1.64; 95% CI, 1.26–2.14) and sepsis plus shock (aOR, 1.26; 95% CI, 1.07–1.49). After controlling for age, race, BMI, and sepsis, blood-culture contamination increased length of stay (LOS; β = 1.24 ± 0.24; P < .0001), length of antibiotic treatment (LOT; β = 1.01 ± 0.20; P < .001), hospital charges (β = 0.22 ± 0.03; P < .0001), acute kidney injury (AKI; aOR, 1.60; 95% CI, 1.40–1.83), echocardiogram orders (aOR, 1.51; 95% CI, 1.30–1.75) and in-hospital mortality (aOR, 1.69; 95% CI, 1.31–2.16). Conclusions: These unique risk factors identify high-risk individuals for blood-culture contamination. After controlling for confounders, contamination significantly increased LOS, LOT, hospital charges, AKI, echocardiograms, and in-hospital mortality.

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