Investig Clin Urol.  2016 May;57(3):196-201. 10.4111/icu.2016.57.3.196.

Electronic nutritional intake assessment in patients with urolithiasis: A decision impact analysis

Affiliations
  • 1Meharry Medical College, Nashville, TN, USA.
  • 2Division of Urologic Surgery, Washington University School of Medicine, St. Louis, MO, USA. parkam@wudosis.wustl.edu
  • 3Washington University School of Medicine, Center for Biomedical Informatics, St. Louis, MO, USA.
  • 4Urology Academic Practice, Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Abstract

PURPOSE
To evaluate a physician's impression of a urinary stone patient's dietary intake and whether it was dependent on the medium through which the nutritional data were obtained. Furthermore, we sought to determine if using an electronic food frequency questionnaire (FFQ) impacted dietary recommendations for these patients.
MATERIALS AND METHODS
Seventy-six patients attended the Stone Clinic over a period of 6 weeks. Seventy-five gave consent for enrollment in our study. Patients completed an office-based interview with a fellowship-trained endourologist, and a FFQ administered on an iPad. The FFQ assessed intake of various dietary components related to stone development, such as oxalate and calcium. The urologists were blinded to the identity of patients' FFQ results. Based on the office-based interview and the FFQ results, the urologists provided separate assessments of the impact of nutrition and hydration on the patient's stone disease (nutrition impact score and hydration impact score, respectively) and treatment recommendations. Multivariate logistic regressions were used to compare pre-FFQ data to post-FFQ data.
RESULTS
Higher FFQ scores for sodium (odds ratio [OR], 1.02; p=0.02) and fluids (OR, 1.03, p=0.04) were associated with a higher nutritional impact score. None of the FFQ parameters impacted hydration impact score. A higher FFQ score for oxalate (OR, 1.07; p=0.02) was associated with the addition of at least one treatment recommendation.
CONCLUSIONS
Information derived from a FFQ can yield a significant impact on a physician's assessment of stone risks and decision for management of stone disease.

Keyword

Clinical decision support systems; Nutrition assessment; Surveys and questionnaires; Urolithiasis

MeSH Terms

Aged
*Decision Support Systems, Clinical
Diet/*adverse effects
Diet Records
Female
Humans
Interviews as Topic
Male
Middle Aged
*Nutrition Assessment
Surveys and Questionnaires
Urolithiasis/diet therapy/*etiology

Figure

  • Fig. 1 Survey completed by the urologists. The survey was completed twice for each patient: the first based on the data obtained during an office-based interview, and the second based on the results of the food frequency questionnaire.

  • Fig. 2 Sample questions from the food frequency questionnaire.


Reference

1. De SK, Liu X, Monga M. Changing trends in the American diet and the rising prevalence of kidney stones. Urology. 2014; 84:1030–1033. PMID: 25201150.
Article
2. Scales CD Jr, Smith AC, Hanley JM, Saigal CS. Urologic Diseases in America Project. Prevalence of kidney stones in the United States. Eur Urol. 2012; 62:160–165. PMID: 22498635.
Article
3. Curhan GC, Willett WC, Knight EL, Stampfer MJ. Dietary factors and the risk of incident kidney stones in younger women: Nurses' Health Study II. Arch Intern Med. 2004; 164:885–891. PMID: 15111375.
4. Curhan GC, Willett WC, Rimm EB, Stampfer MJ. A prospective study of dietary calcium and other nutrients and the risk of symptomatic kidney stones. N Engl J Med. 1993; 328:833–838. PMID: 8441427.
Article
5. Delvecchio FC, Preminger GM. Medical management of stone disease. Curr Opin Urol. 2003; 13:229–233. PMID: 12692447.
Article
6. Fellstrom B, Danielson BG, Karlstrom B, Lithell H, Ljunghall S, Vessby B. Dietary habits in renal stone patients compared with healthy subjects. Br J Urol. 1989; 63:575–580. PMID: 2752249.
7. Parivar F, Low RK, Stoller ML. The influence of diet on urinary stone disease. J Urol. 1996; 155:432–440. PMID: 8558629.
Article
8. Siener R. Impact of dietary habits on stone incidence. Urol Res. 2006; 34:131–133. PMID: 16404621.
Article
9. Wertheim ML, Nakada SY, Penniston KL. Current practice patterns of urologists providing nutrition recommendations to patients with kidney stones. J Endourol. 2014; 28:1127–1131. PMID: 24846196.
Article
10. Baer HJ, Blum RE, Rockett HR, Leppert J, Gardner JD, Suitor CW, et al. Use of a food frequency questionnaire in American Indian and Caucasian pregnant women: a validation study. BMC Public Health. 2005; 5:135. PMID: 16356183.
Article
11. Blum RE, Wei EK, Rockett HR, Langeliers JD, Leppert J, Gardner JD, et al. Validation of a food frequency questionnaire in Native American and Caucasian children 1 to 5 years of age. Matern Child Health J. 1999; 3:167–172. PMID: 10746756.
12. Rockett HR, Breitenbach M, Frazier AL, Witschi J, Wolf AM, Field AE, et al. Validation of a youth/adolescent food frequency questionnaire. Prev Med. 1997; 26:808–816. PMID: 9388792.
Article
13. Wei EK, Gardner J, Field AE, Rosner BA, Colditz GA, Suitor CW. Validity of a food frequency questionnaire in assessing nutrient intakes of low-income pregnant women. Matern Child Health J. 1999; 3:241–246. PMID: 10791365.
14. Ljunghall S, Danielson BG. A prospective study of renal stone recurrences. Br J Urol. 1984; 56:122–124. PMID: 6498430.
Article
15. Pearle MS, Calhoun EA, Curhan GC. Urologic Diseases of America Project. Urologic diseases in America project: urolithiasis. J Urol. 2005; 173:848–857. PMID: 15711292.
Article
16. Penniston KL, Nakada SY. Diet and alternative therapies in the management of stone disease. Urol Clin North Am. 2013; 40:31–46. PMID: 23177633.
Article
17. Kubena KS. Accuracy in dietary assessment: on the road to good science. J Am Diet Assoc. 2000; 100:775–776. PMID: 10916514.
18. Hunt DL, Haynes RB, Hanna SE, Smith K. Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review. JAMA. 1998; 280:1339–1346. PMID: 9794315.
19. Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005; 293:1223–1238. PMID: 15755945.
20. Kaushal R, Shojania KG, Bates DW. Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Arch Intern Med. 2003; 163:1409–1416. PMID: 12824090.
21. Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. 2005; 330:765. PMID: 15767266.
Article
22. Afzal M, Hussain M, Ali T, Hussain J, Khan WA, Lee S, et al. Knowledge-based query construction using the CDSS knowledge base for efficient evidence retrieval. Sensors (Basel). 2015; 15:21294–21314. PMID: 26343669.
Article
23. Trinchieri A. Development of a rapid food screener to assess the potential renal acid load of diet in renal stone formers (LAKE score). Arch Ital Urol Androl. 2012; 84:36–38. PMID: 22649959.
24. Trinchieri A. A rapid food screener ranks potential renal acid load of renal stone formers similarly to a diet history questionnaire. Urolithiasis. 2013; 41:3–7. PMID: 23532416.
Article
Full Text Links
  • ICU
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr