Kris M Mogensen

Ms. Kris M Mogensen


Research Focus & Metrics

Academic Career Length

26Years (2001-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 September 2018 in Journal of Parenteral and Enteral Nutrition
Verified
Journal Article
Open access
PDF file
GJGordon L. Jensen
Gordon L. Jensen
TCTommy Cederholm
Tommy Cederholm
MCMaria Isabel T D Correia
Maria Isabel T D Correia
Maria Cristina GonzalezMaria Cristina Gonzalez
Maria Cristina Gonzalez
RFRyoji Fukushima
Ryoji Fukushima
AGAndre Van Gossum
Andre Van Gossum
Background: This initiative aims to build a global consensus around core diagnostic criteria for malnutrition in adults in clinical settings.Methods: The Global Leadership Initiative on Malnutrition (GLIM) was convened by several of the major global clinical nutrition societies. Empirical consensus was reached through a series of face‐to‐face meetings, telephone conferences, and e‐mail communications.Results: A 2‐step approach for the malnutrition diagnosis was selected, that is, first screening to identify at risk status by the use of any validated screening tool, and second, assessment for diagnosis and grading the severity of malnutrition. The malnutrition criteria for consideration were retrieved from existing approaches for screening and assessment. Potential criteria were subjected to a ballot among GLIM participants that selected 3 phenotypic criteria (non‐volitional weight loss, low body mass index, and reduced muscle mass) and 2 etiologic criteria (reduced food intake or assimilation, and inflammation or disease burden). To diagnose malnutrition at least 1 phenotypic criterion and 1 etiologic criterion should be present. Phenotypic metrics for grading severity are proposed. It is recommended that the etiologic criteria be used to guide intervention and anticipated outcomes. The recommended approach supports classification of malnutrition into four etiology‐related diagnosis categories.Conclusions: A consensus scheme for diagnosing malnutrition in adults in clinical settings on a global scale is proposed. Next steps are to secure endorsements from leading nutrition professional societies, to identify overlaps with syndromes like cachexia and sarcopenia, and to promote dissemination, validation studies, and feedback. The construct should be re‐considered every 3–5 years.

30 October 2020 in Nutrition in Clinical Practice
Verified
Journal Article
Closed access
PDF file
DEDavid C. Evans
David C. Evans
MCMark R. Corkins
Mark R. Corkins
AMAinsley Malone
Ainsley Malone
SMSarah Miller
Sarah Miller
KMKris M Mogensen
Kris M Mogensen
TCthe ASPEN Malnutrition Committee
the ASPEN Malnutrition Committee

23 December 2018 in Nutrition in Clinical Practice
Verified
Journal Article
Closed access
PDF file
KSKavita Sharma
Kavita Sharma
KMKris M Mogensen
Kris M Mogensen
MRMalcolm K. Robinson
Malcolm K. Robinson

1 December 2015 in Critical Care Medicine
Verified
Journal Article
Closed access
KMKris M Mogensen
Kris M Mogensen
MRMalcolm K. Robinson
Malcolm K. Robinson
JCJonathan D. Casey
Jonathan D. Casey
NGNicole S. Gunasekera
Nicole S. Gunasekera
TMTakuhiro Moromizato
Takuhiro Moromizato
Kenneth B. ChristopherKenneth B. Christopher
Kenneth B. Christopher
The association between nutritional status and mortality in critically ill patients is unclear based on the current literature. To clarify this relation, we analyzed the association between nutrition and mortality in a large population of critically ill patients and hypothesized that mortality would be impacted by nutritional status. Retrospective observational study. Single academic medical center. Six thousand five hundred eighteen adults treated in medical and surgical ICUs between 2004 and 2011. None. All cohort patients received a formal, in-person, standardized evaluation by a registered dietitian. The exposure of interest, malnutrition, was categorized as nonspecific malnutrition, protein-energy malnutrition, or well nourished and determined by data related to anthropometric measurements, biochemical indicators, clinical signs of malnutrition, malnutrition risk factors, and metabolic stress. The primary outcome was all-cause 30-day mortality determined by the Social Security Death Master File. Associations between nutrition groups and mortality were estimated by bivariable and multivariable logistic regression models. Adjusted odds ratios were estimated with inclusion of covariate terms thought to plausibly interact with both nutrition status and mortality. We used propensity score matching on baseline characteristics to reduce residual confounding of the nutrition status category assignment. In the cohort, nonspecific malnutrition was present in 56%, protein-energy malnutrition was present in 12%, and 32% were well nourished. The 30-day and 90-day mortality rates for the cohort were 19.1% and 26.6%, respectively. Nutritional status is a significant predictor of 30-day mortality following adjustment for age, gender, race, medical versus surgical patient type, Deyo-Charlson index, acute organ failure, vasopressor use, and sepsis: nonspecific malnutrition 30-day mortality odds ratio, 1.17 (95% CI, 1.01-1.37); protein-energy malnutrition 30-day mortality odds ratio, 2.10 (95% CI, 1.70-2.59), all relative to patients without malnutrition. In the matched cohort, the adjusted odds of 30-day mortality in the group of propensity score-matched patients with protein-energy malnutrition was two-fold greater than that of patients without malnutrition. In a large population of critically ill adults, an association exists between nutrition status and mortality.

1 January 2015 in Critical Care Medicine
Verified
Journal Article
Closed access
MRMalcolm K. Robinson
Malcolm K. Robinson
KMKris M Mogensen
Kris M Mogensen
JCJonathan D. Casey
Jonathan D. Casey
CMCaitlin K. McKane
Caitlin K. McKane
TMTakuhiro Moromizato
Takuhiro Moromizato
Kenneth B. ChristopherKenneth B. Christopher
Kenneth B. Christopher
The association between obesity and mortality in critically ill patients is unclear based on the current literature. To clarify this relationship, we analyzed the association between obesity and mortality in a large population of critically ill patients and hypothesized that mortality would be impacted by nutritional status. We performed a single-center observational study of 6,518 adult patients treated in medical and surgical ICUs between 2004 and 2011. All patients received a formal, in-person, and standardized evaluation by a registered dietitian. Body mass index was determined at the time of dietitian consultation from the estimated dry weight or hospital admission weight and categorized a priori as less than 18.5 kg/m (underweight), 18.5-24.9 kg/m (normal/referent), 25-29.9 kg/m (overweight), 30-39.9 kg/m (obesity class I and II), and more than or equal to 40.0 kg/m (obesity class III). Malnutrition diagnoses were categorized as nonspecific malnutrition, protein-energy malnutrition, or well nourished. The primary outcome was all-cause 30-day mortality determined by the Social Security Death Master File. Associations between body mass index groups and mortality were estimated by bivariable and multivariable logistic regression models. Adjusted odds ratios were estimated with inclusion of covariate terms thought to plausibly interact with both body mass index and mortality. We utilized propensity score matching on baseline characteristics and nutrition status to reduce residual confounding of the body mass index category assignment. In the cohort, 5% were underweight, 36% were normal weight, 31% were overweight, 23% had class I/II obesity, and 5% had class III obesity. Nonspecific malnutrition was present in 56%, protein-energy malnutrition was present in 12%, and 32% were well nourished. The 30-day and 90-day mortality rate for the cohort was 19.1 and 26.6%, respectively. Obesity is a significant predictor of improved 30-day mortality following adjustment for age, gender, race, medical versus surgical patient type, Deyo-Charlson index, acute organ failure, vasopressor use, and sepsis: underweight odds ratio 30-day mortality is 1.09 (95% CI, 0.80-1.48), overweight 30-day mortality odds ratio is 0.93 (95% CI, 0.80-1.09), class I/II obesity 30-day mortality odds ratio is 0.80 (95% CI, 0.67-0.96), and class III obesity 30-day mortality odds ratio is 0.69 (95% CI, 0.49-0.97), all relative to patients with body mass index 18.5-24.9 kg/m. Importantly, there is confounding of the obesity-mortality association on the basis of malnutrition. Adjustment for only nutrition status attenuates the obesity-30-day mortality association: underweight odds ratio is 0.74 (95% CI, 0.54-1.00), overweight odds ratio is 1.05 (95% CI, 0.90-1.23), class I/II obesity odds ratio is 0.96 (95% CI, 0.81-1.15), and class III obesity odds ratio is 0.81 (95% CI, 0.59-1.12), all relative to patients with body mass index 18.5-24.9 kg/m. In a subset of patients with body mass index more than or equal to 30.0 kg/m (n = 1,799), those with either nonspecific or protein-energy malnutrition have increased mortality relative to well-nourished patients with body mass index more than or equal to 30.0 kg/m: odds ratio of 90-day mortality is 1.67 (95% CI, 1.29-2.15; p < 0.0001), fully adjusted. In a cohort of propensity score matched patients (n = 3,554), the body mass index-mortality association was not statistically significant, likely from matching on nutrition status. In a large population of critically ill adults, the association between improved mortality and obesity is confounded by malnutrition status. Critically ill obese patients with malnutrition have worse outcomes than obese patients without malnutrition.

29 November 2023 in Clinical Nutrition
Verified
Journal Article
Open access
TCTommy Cederholm
Tommy Cederholm
GJGordon L. Jensen
Gordon L. Jensen
MBMaría D. Ballesteros-Pomar
María D. Ballesteros-Pomar
RBRenee Blaauw
Renee Blaauw
MCMaria Isabel T D Correia
Maria Isabel T D Correia
CCCharlene Compher
Charlene Compher
The Global Leadership Initiative on Malnutrition (GLIM) approach to malnutrition diagnosis is based on assessment of three phenotypic (weight loss, low body mass index, and reduced skeletal muscle mass) and two etiologic (reduced food intake/assimilation and disease burden/inflammation) criteria, with diagnosis confirmed by fulfillment of any combination of at least one phenotypic and at least one etiologic criterion. The original GLIM description provided limited guidance regarding assessment of inflammation and this has been a factor impeding further implementation of the GLIM criteria. We now seek to provide practical guidance for assessment of inflammation in support of the etiologic criterion for inflammation. A GLIM-constituted working group with 36 participants developed consensus-based guidance through a modified-Delphi review. A multi-round review and revision process served to develop seven guidance statements. The final round of review was highly favorable with 99 % overall "agree" or "strongly agree" responses. The presence of acute or chronic disease, infection or injury that is usually associated with inflammatory activity may be used to fulfill the GLIM disease burden/inflammation criterion, without the need for laboratory confirmation. However, we recommend that recognition of underlying medical conditions commonly associated with inflammation be supported by C-reactive protein (CRP) measurements when the contribution of inflammatory components is uncertain. Interpretation of CRP requires that consideration be given to the method, reference values, and units (mg/dL or mg/L) for the clinical laboratory that is being used. Confirmation of inflammation should be guided by clinical judgement based upon underlying diagnosis or condition, clinical signs, or CRP.