Hinke Kruizenga

Dr. Hinke Kruizenga


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

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

Representative Publications

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1 June 2021 in Clinical Nutrition ESPEN
Verified
Journal Article
Open access
NWNicolette Wierdsma
Nicolette Wierdsma
HKHinke Kruizenga
Hinke Kruizenga
LKLotte Aml. Konings
Lotte Aml. Konings
DKDaphne Krebbers
Daphne Krebbers
JJJolein Rmc. Jorissen
Jolein Rmc. Jorissen
PWPeter Jm. Weijs
Peter Jm. Weijs
Patients with COVID-19 infection presents with a broad clinical spectrum of symptoms and complications. As a consequence nutritional requirements are not met, resulting in weight- and muscle loss, and malnutrition. The aim of the present study is to delineate nutritional complaints, the (course of the) nutritional status and risk of sarcopenia of COVID-19 patients, during hospitalisation and after discharge. In this prospective observational study in 407 hospital admitted COVID-19 patients in four university and peripheral hospitals, data were collected during dietetic consultations. Presence of nutrition related complaints (decreased appetite, loss of smell, changed taste, loss of taste, chewing and swallowing problems, nausea, vomiting, feeling of being full, stool frequency and consistency, gastric retention, need for help with food intake due to weakness and shortness of breath and nutritional status (weight loss, BMI, risk of sarcopenia with SARC-F ≥4 points) before, during hospital stay and after discharge were, where possible, collected. Included patients were most men (69%), median age of 64.8 ± 12.4 years, 60% were admitted to ICU at any time point during hospitalisation with a median LOS of 15 days and an in-hospital mortality rate of 21%. The most commonly reported complaints were: decreased appetite (58%), feeling of being full (49%) and shortness of breath (43%). One in three patients experienced changed taste, loss of taste and/or loss of smell. Prior to hospital admission, 67% of the patients was overweight (BMI >25 kg/m2), 35% of the patients was characterised as malnourished, mainly caused by considerable weight loss. Serious acute weight loss (>5 kg) was showed in 22% of the patents during the hospital stay; most of these patients (85%) were admitted to the ICU at any point in time. A high risk of sarcopenia (SARC-F ≥ 4 points) was scored in 73% of the patients during hospital admission. In conclusion, one in five hospital admitted COVID-19 patients suffered from serious acute weight loss and 73% had a high risk of sarcopenia. Moreover, almost all patients had one or more nutritional complaints. Of these complaints, decreased appetite, feeling of being full, shortness of breath and changed taste and loss of taste were the most predominant nutrition related complaints. These symptoms have serious repercussions on nutritional status. Although nutritional complaints persisted a long time after discharge, only a small group of patients received dietetic treatment after hospital discharge in recovery phase. Clinicians should consider the risks of acute malnutrition and sarcopenia in COVID-19 patients and investigate multidisciplinary treatment including dietetics during hospital stay and after discharge.

19 January 2022 in Clinical Nutrition ESPEN
Verified
Journal Article
Open access
IDIngeborg M. Dekker
Ingeborg M. Dekker
NRNatascha M. van Rijssen
Natascha M. van Rijssen
AVAmely Verreijen
Amely Verreijen
PWPeter Jm. Weijs
Peter Jm. Weijs
WBW.B. (Elsbeth) de Boer
W.B. (Elsbeth) de Boer
HKHinke Kruizenga
Hinke Kruizenga
In dietary practice, it is common to estimate protein requirements on actual bodyweight, but corrected bodyweight (in cases with BMI <20 kg/m2 and BMI ≥30 kg/m2) and fat free mass (FFM) are also used. Large differences on individual level are noticed in protein requirements using these different approaches. To continue this discussion, the answer is sought in a large population to the following question: Will choosing actual bodyweight, corrected bodyweight or FFM to calculate protein requirements result in clinically relevant differences? This retrospective database study, used data from healthy persons ≥55 years of age and in- and outpatients ≥18 years of age. FFM was measured by air displacement plethysmography technology or bioelectrical impedance analysis. Protein requirements were calculated as 1) 1.2 g (g) per kilogram (kg) actual bodyweight or 2) corrected bodyweight or 3) 1.5 g per kg FFM. To compare these three approaches, the approach in which protein requirement is based on FFM, was used as reference method. Bland-Altman plots with limits of agreement were used to determine differences, analyses were performed for both populations separately and stratified by BMI category and gender. In total 2291 subjects were included. In the population with relatively healthy persons (n = 506, ≥55 years of age) mean weight is 86.5 ± 18.2 kg, FFM is 51 ± 12 kg and in the population with adult in- and outpatients (n = 1785, ≥18 years of age) mean weight is 72.5 ± 18.4 kg, FFM is 51 ± 11 kg. Clinically relevant differences were found in protein requirement between actual bodyweight and FFM in most of the participants with overweight, obesity or severe obesity (78-100%). Using corrected bodyweight, an overestimation in 48-92% of the participants with underweight, healthy weight and overweight is found. Only in the Amsterdam UMC population, protein requirement is underestimated when using the approach of corrected bodyweight in participants with severe obesity. The three approaches in estimation of protein requirement show large differences. In the majority of the population protein requirement based on FFM is lower compared to actual or corrected bodyweight. Correction of bodyweight reduces the differences, but remain unacceptably large. It is yet unknown which method is the best for estimation of protein requirement. Since differences vary by gender due to differences in body composition, it seems more accurate to estimate protein requirement based on FFM. Therefore, we would like to advocate for more frequent measurement of FFM to determine protein requirements, especially when a deviating body composition is to be expected, for instance in elderly and persons with overweight, obesity or severe obesity.

17 December 2023 in Nutrients
Verified
Journal Article
Open access
PDF file
CDCarliene van Dronkelaar
Carliene van Dronkelaar
MTMichael Tieland
Michael Tieland
TCTommy Cederholm
Tommy Cederholm
EREsmee M. Reijnierse
Esmee M. Reijnierse
PWPeter J.M. Weijs
Peter J.M. Weijs
HKHinke Kruizenga
Hinke Kruizenga
This study evaluates the concurrent validity of five malnutrition screening tools to identify older hospitalized patients against the Global Leadership Initiative on Malnutrition (GLIM) diagnostic criteria as limited evidence is available. The screening tools Short Nutritional Assessment Questionnaire (SNAQ), Malnutrition Universal Screening Tool (MUST), Malnutrition Screening Tool (MST), Mini Nutritional Assessment—Short Form (MNA-SF), and the Patient-Generated Subjective Global Assessment—Short Form (PG-SGA-SF) with cut-offs for both malnutrition (conservative) and moderate malnutrition or risk of malnutrition (liberal) were used. The concurrent validity was determined by the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the level of agreement by Cohen’s kappa. In total, 356 patients were included in the analyses (median age 70 y (IQR 63–77); 54% male). The prevalence of malnutrition according to the GLIM criteria without prior screening was 42%. The conservative cut-offs showed a low-to-moderate sensitivity (32–68%) and moderate-to-high specificity (61–98%). The PPV and NPV ranged from 59 to 94% and 67–86%, respectively. The Cohen’s kappa showed poor agreement (k = 0.21–0.59). The liberal cut-offs displayed a moderate-to-high sensitivity (66–89%) and a low-to-high specificity (46–95%). The agreement was fair to good (k = 0.33–0.75). The currently used screening tools vary in their capacity to identify hospitalized older patients with malnutrition. The screening process in the GLIM framework requires further consideration.

30 January 2024 in Nutrients
Verified
Journal Article
Open access
PDF file
MGManon de Geus
Manon de Geus
MDManouk Dam
Manouk Dam
WVWesley Visser
Wesley Visser
KIKarin J. R. Ipema
Karin J. R. Ipema
AEAnneke M. E. de Mik-Van Egmond
Anneke M. E. de Mik-Van Egmond
HKHinke Kruizenga
Hinke Kruizenga
Combined nutrition and exercise interventions potentially improve protein-energy wasting/malnutrition-related outcomes in patients with chronic kidney disease (CKD). The aim was to systematically review the effect of combined interventions on nutritional status, muscle strength, physical performance and QoL. MEDLINE, Cochrane, Embase, Web of Science and Google Scholar were searched for studies up to the date of July 2023. Methodological quality was appraised with the Cochrane risk-of-bias tool. Ten randomized controlled trials (nine publications) were included (334 patients). No differences were observed in body mass index, lean body mass or leg strength. An improvement was found in the six-minute walk test (6-MWT) (n = 3, MD 27.2, 95%CI [7 to 48], p = 0.008), but not in the timed up-and-go test. No effect was found on QoL. A positive impact on 6-MWT was observed, but no improvements were detected in nutritional status, muscle strength or QoL. Concerns about reliability and generalizability arise due to limited statistical power and study heterogeneity of the studies included.

20 October 2023 in JMIR Public Health and Surveillance
Verified
Journal Article
Open access
ASAnne Slotegraaf
Anne Slotegraaf
MGMarissa H G Gerards
Marissa H G Gerards
AVArie C Verburg
Arie C Verburg
MSMarian A.E. de van der Schueren
Marian A.E. de van der Schueren
HKHinke Kruizenga
Hinke Kruizenga
DCDutch Consortium Allied Healthcare COVID-19
Dutch Consortium Allied Healthcare COVID-19
Background: Patients recovering from COVID-19 often experience persistent problems in their daily activities related to limitations in physical, nutritional, cognitive, and mental functioning. To date, it is unknown what treatment is needed to support patients in their recovery from COVID-19. Objective: This study aimed to evaluate the primary allied health care of patients recovering from COVID-19 at 6-month follow-up and to explore which baseline characteristics are associated with changes in the scores of outcomes between baseline and 6-month follow-up. Methods: This Dutch nationwide prospective cohort study evaluated the recovery of patients receiving primary allied health care (ie, dietitians, exercise therapists, occupational therapists, physical therapists, and speech and language therapists) after COVID-19. All treatments offered by primary allied health professionals in daily practice were part of usual care. Patient-reported outcome measures on participation, health-related quality of life, fatigue, physical functioning, and psychological well-being were assessed at baseline and at 3- and 6-month follow-up. Linear mixed model analyses were used to evaluate recovery over time, and uni- and multivariable linear regression analyses were used to examine the association between baseline characteristics and recovery. Results: A total of 1451 adult patients recovering from COVID-19 and receiving treatment from 1 or more primary allied health professionals were included. For participation (Utrecht Scale for Evaluation of Rehabilitation—Participation range 0-100), estimated mean differences of at least 2.3 points were observed at all time points. For the health-related quality of life (EuroQol Visual Analog Scale, range 0-100), the mean increase was 12.3 (95% CI 11.1-13.6) points at 6 months. Significant improvements were found for fatigue (Fatigue Severity Scale, range 1-7): the mean decrease was –0.7 (95% CI –0.8 to –0.6) points at 6 months. However, severe fatigue was reported by 742/929 (79.9%) patients after 6 months. For physical functioning (Patient-Reported Outcomes Measurement Information System—Physical Function Short Form 10b, range 13.8-61.3), the mean increase was 5.9 (95% CI 5.9-6.4) points at 6 months. Mean differences of –0.8 (95% CI –1.0 to –0.5) points for anxiety (Hospital Anxiety and Depression Scale range 0-21) and –1.6 (95% CI –1.8 to –1.3) points for depression were found after 6 months. A worse baseline score, hospital admission, and male sex were associated with greater improvement between baseline and 6-month follow-up, whereas age, the BMI, comorbidities, and smoking status were not associated with mean changes in any outcome measures. Conclusions: Patients recovering from COVID-19 who receive primary allied health care make progress in recovery but still experience many limitations in their daily activities after 6 months. Our findings provide reference values to health care providers and health care policy makers regarding what to expect from the recovery of patients who receive health care from 1 or more primary allied health professionals. Trial Registration: ClinicalTrials.gov NCT04735744; https://tinyurl.com/3vf337pn International Registered Report Identifier (IRRID): RR2-10.2340/jrm.v54.2506

1 August 2021 in Clinical Nutrition ESPEN
Verified
Journal Article
Open access
MDManouk Dam
Manouk Dam
EHEva Anne Hartman
Eva Anne Hartman
HKHinke Kruizenga
Hinke Kruizenga
BJBrigit C. van Jaarsveld
Brigit C. van Jaarsveld
PWPeter J.M. Weijs
Peter J.M. Weijs
Sufficient protein intake is of great importance in hemodialysis (HD) patients, especially for maintaining muscle mass. Daily protein needs are generally estimated using bodyweight (BW), in which individual differences in body composition are not accounted for. As body protein mass is best represented by fat free mass (FFM), there is a rationale to apply FFM instead of BW. The agreement between both estimations is unclear. Therefore, the aim of this study is to compare protein needs based on either FFM or BW in HD patients. Protein needs were estimated in 115 HD patients by three different equations; FFM, BW and BW adjusted for low or high BMI. FFM was measured by multi-frequency bioelectrical impedance spectroscopy and considered the reference method. Estimations of FFM x 1.5 g/kg and FFM x 1.9 g/kg were compared with (adjusted)BW x 1.2 and x 1.5, respectively. Differences were assessed with repeated measures ANOVA and Bland-Altman plots. Mean protein needs estimated by (adjusted)BW were higher compared to those based on FFM, across all BMI categories (P < 0.01) and most explicitly in obese patients. In females with BMI >30, protein needs were 69 ± 17.4 g/day higher based on BW and 45 ± 9.3 g/day higher based on BMI adjusted BW, compared to FFM. In males with BMI >30, protein needs were 51 ± 20.4 g/day and 23 ± 20.9 g/day higher compared to FFM, respectively. Our data show large differences and possible overestimations of protein needs when comparing BW to FFM. We emphasize the importance of more research and discussion on this topic.