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Healthcare-associated infections are associated with insufficient dietary intake: an observational cross-sectional study.

Thibault R, Makhlouf AM, Kossovsky MP, Iavindrasana J, Chikhi M, Meyer R, Pittet D, Zingg W, Pichard C - PLoS ONE (2015)

Bottom Line: Patients with HCAI were more likely identified with decreased energy intake (i.e. ≤ 70% of predicted energy needs) (30.3% vs. 14.5%, P = 0.002).Measured energy intake ≤ 70% of predicted energy needs (odds ratio: 2.26; 95% CI: 1.24 to 4.11, P = 0.008) and moderate severity of the disease (odds ratio: 3.38; 95% CI: 1.49 to 7.68, P = 0.004) were associated with HCAI in the multivariate analysis.Measured energy intake ≤ 70% of predicted energy needs is associated with HCAI in hospitalised patients.

View Article: PubMed Central - PubMed

Affiliation: Nutrition Unit, Geneva University Hospital, Geneva, Switzerland.

ABSTRACT

Background: Indicators to predict healthcare-associated infections (HCAI) are scarce. Malnutrition is known to be associated with adverse outcomes in healthcare but its identification is time-consuming and rarely done in daily practice. This cross-sectional study assessed the association between dietary intake, nutritional risk, and the prevalence of HCAI, in a general hospital population.

Methods and findings: Dietary intake was assessed by dedicated dieticians on one day for all hospitalized patients receiving three meals per day. Nutritional risk was assessed using Nutritional Risk Screening (NRS)-2002, and defined as a NRS score ≥ 3. Energy needs were calculated using 110% of Harris-Benedict formula. HCAIs were diagnosed based on the Center for Disease Control criteria and their association with nutritional risk and measured energy intake was done using a multivariate logistic regression analysis. From 1689 hospitalised patients, 1024 and 1091 were eligible for the measurement of energy intake and nutritional risk, respectively. The prevalence of HCAI was 6.8%, and 30.1% of patients were at nutritional risk. Patients with HCAI were more likely identified with decreased energy intake (i.e. ≤ 70% of predicted energy needs) (30.3% vs. 14.5%, P = 0.002). The proportion of patients at nutritional risk was not significantly different between patients with and without HCAI (35.6% vs.29.7%, P = 0.28), respectively. Measured energy intake ≤ 70% of predicted energy needs (odds ratio: 2.26; 95% CI: 1.24 to 4.11, P = 0.008) and moderate severity of the disease (odds ratio: 3.38; 95% CI: 1.49 to 7.68, P = 0.004) were associated with HCAI in the multivariate analysis.

Conclusion: Measured energy intake ≤ 70% of predicted energy needs is associated with HCAI in hospitalised patients. This suggests that insufficient dietary intake could be a risk factor of HCAI, without excluding reverse causality. Randomized trials are needed to assess whether improving energy intake in patients identified with decreased dietary intake could be a novel strategy for HCAI prevention.

No MeSH data available.


Related in: MedlinePlus

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Mentions: The Geneva University Hospital is the largest University-affiliated primary and tertiary referral centre in Switzerland. All types of care are represented: medicine, surgery, rehabilitation, psychiatry, and long term facility. The study was performed on one single day on adult patients of all departments, except the intensive care unit, between September 27th and November 20th 2012. All hospitalised patients were eligible. Exclusion criteria were end-of-life care, exclusive tube feeding or parenteral nutrition, and missed meals due to fasting for medical reasons, death, or transfer, admission and discharge from the ward (Fig 1). As a routine procedure at the Geneva University Hospital, patients select their menus which are served on individual trays three times a day. The assessment of dietary intake was standardized and performed by a team of 109 well-trained dieticians. All dieticians, including students of the Geneva Dietetic School were trained before the assessment with the same teachers (AMM, MC, CP). For at-bed measurement of dietary intake, all students were supervised by qualified dieticians who received the same information regarding the methodology of dietary intake. Dietary intake was calculated by analysing the differences between consumed and provided meals, snacks, oral nutritional supplements, supplemental tube feeding and parenteral nutrition. The energy from dietary intake was calculated for each meal using the dietary service software Winrest (FSI, Noisy-le-Grand, France) for which a training was done. The predicted energy needs were calculated as previously shown [17,18], according to the current ESPEN recommendations [19,20]. Energy needs were calculated with the Harris-Benedict formula increased by 10% to cover increased needs due to hospitalization and disease (e.g. stress, fever, digestive or renal losses). Predicted protein needs were calculated as 1.2 or 1.0 g/kg/day for patients < 65 or ≥ 65 years respectively. [19,20]


Healthcare-associated infections are associated with insufficient dietary intake: an observational cross-sectional study.

Thibault R, Makhlouf AM, Kossovsky MP, Iavindrasana J, Chikhi M, Meyer R, Pittet D, Zingg W, Pichard C - PLoS ONE (2015)

Study flow chart.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4414575&req=5

pone.0123695.g001: Study flow chart.
Mentions: The Geneva University Hospital is the largest University-affiliated primary and tertiary referral centre in Switzerland. All types of care are represented: medicine, surgery, rehabilitation, psychiatry, and long term facility. The study was performed on one single day on adult patients of all departments, except the intensive care unit, between September 27th and November 20th 2012. All hospitalised patients were eligible. Exclusion criteria were end-of-life care, exclusive tube feeding or parenteral nutrition, and missed meals due to fasting for medical reasons, death, or transfer, admission and discharge from the ward (Fig 1). As a routine procedure at the Geneva University Hospital, patients select their menus which are served on individual trays three times a day. The assessment of dietary intake was standardized and performed by a team of 109 well-trained dieticians. All dieticians, including students of the Geneva Dietetic School were trained before the assessment with the same teachers (AMM, MC, CP). For at-bed measurement of dietary intake, all students were supervised by qualified dieticians who received the same information regarding the methodology of dietary intake. Dietary intake was calculated by analysing the differences between consumed and provided meals, snacks, oral nutritional supplements, supplemental tube feeding and parenteral nutrition. The energy from dietary intake was calculated for each meal using the dietary service software Winrest (FSI, Noisy-le-Grand, France) for which a training was done. The predicted energy needs were calculated as previously shown [17,18], according to the current ESPEN recommendations [19,20]. Energy needs were calculated with the Harris-Benedict formula increased by 10% to cover increased needs due to hospitalization and disease (e.g. stress, fever, digestive or renal losses). Predicted protein needs were calculated as 1.2 or 1.0 g/kg/day for patients < 65 or ≥ 65 years respectively. [19,20]

Bottom Line: Patients with HCAI were more likely identified with decreased energy intake (i.e. ≤ 70% of predicted energy needs) (30.3% vs. 14.5%, P = 0.002).Measured energy intake ≤ 70% of predicted energy needs (odds ratio: 2.26; 95% CI: 1.24 to 4.11, P = 0.008) and moderate severity of the disease (odds ratio: 3.38; 95% CI: 1.49 to 7.68, P = 0.004) were associated with HCAI in the multivariate analysis.Measured energy intake ≤ 70% of predicted energy needs is associated with HCAI in hospitalised patients.

View Article: PubMed Central - PubMed

Affiliation: Nutrition Unit, Geneva University Hospital, Geneva, Switzerland.

ABSTRACT

Background: Indicators to predict healthcare-associated infections (HCAI) are scarce. Malnutrition is known to be associated with adverse outcomes in healthcare but its identification is time-consuming and rarely done in daily practice. This cross-sectional study assessed the association between dietary intake, nutritional risk, and the prevalence of HCAI, in a general hospital population.

Methods and findings: Dietary intake was assessed by dedicated dieticians on one day for all hospitalized patients receiving three meals per day. Nutritional risk was assessed using Nutritional Risk Screening (NRS)-2002, and defined as a NRS score ≥ 3. Energy needs were calculated using 110% of Harris-Benedict formula. HCAIs were diagnosed based on the Center for Disease Control criteria and their association with nutritional risk and measured energy intake was done using a multivariate logistic regression analysis. From 1689 hospitalised patients, 1024 and 1091 were eligible for the measurement of energy intake and nutritional risk, respectively. The prevalence of HCAI was 6.8%, and 30.1% of patients were at nutritional risk. Patients with HCAI were more likely identified with decreased energy intake (i.e. ≤ 70% of predicted energy needs) (30.3% vs. 14.5%, P = 0.002). The proportion of patients at nutritional risk was not significantly different between patients with and without HCAI (35.6% vs.29.7%, P = 0.28), respectively. Measured energy intake ≤ 70% of predicted energy needs (odds ratio: 2.26; 95% CI: 1.24 to 4.11, P = 0.008) and moderate severity of the disease (odds ratio: 3.38; 95% CI: 1.49 to 7.68, P = 0.004) were associated with HCAI in the multivariate analysis.

Conclusion: Measured energy intake ≤ 70% of predicted energy needs is associated with HCAI in hospitalised patients. This suggests that insufficient dietary intake could be a risk factor of HCAI, without excluding reverse causality. Randomized trials are needed to assess whether improving energy intake in patients identified with decreased dietary intake could be a novel strategy for HCAI prevention.

No MeSH data available.


Related in: MedlinePlus