References April 24 - issue 188

UP FRONT – The Editor’s Welcome

  1. https://decrypt.co/resources/a-brief-history-of-artificial-intelligence-ai-from-turing-to-iot
  2. https://www.ibm.com/topics/artificial-intelligence
  3. https://www.europarl.europa.eu/topics/en/article/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence
  4. https://lordslibrary.parliament.uk/artificial-intelligence-development-risks-and-regulation/#heading-11

MYTH BUSTING WITH MADI - CARBOHYDRATES ARE ‘FATTENING’…

  1. Gardner et al (2018). Effect of Low-Fat vs Low-Carbohydrate Diet on 12-Month Weight Loss in Overweight Adults and the Association With Genotype Pattern or Insulin Secretion: The DIETFITS Randomized Clinical Trial. JAMA. 319(7):667-679.
  2. Yang et al (2022). The effects of low-fat, high-carbohydrate diets vs. low-carbohydrate, high-fat diets on weight, blood pressure, serum liquids and blood glucose: a systematic review and meta-analysis. Eur J Clin Nutr. 76(1):16-27.
  3. Santangelo et al (2023). The Influence of Ketogenic Diet on Gut Microbiota: Potential Benefits, Risks and Indications. Nutrients. 15(17):3680.
  4. Kanter (2018). High-Quality Carbohydrates and Physical Performance: Expert Panel Report. Nutr Today. 53(1):35-39.
  5. Wang et al (2015). Association between sugar-sweetened beverages and type 2 diabetes: A meta-analysis. J Diabetes Investig. 6(3):360-6.
  6. Hosseini et al (2022). Dietary carbohydrate and the risk of type 2 diabetes: an updated systematic review and dose-response meta-analysis of prospective cohort studies. Sci Rep. 12(1):2491.
  7. Scientific Advisory Committee on Nutrition (2015). Carbohydrates and Health. Available at: https://assets.publishing.service.gov.uk/media/5a7f7cc3ed915d74e622ac2a/SACN_Carbohydrates_and_Health.pdf

METABOLICALLY HEALTHY OBESITY: IS IT REALLY HEALTHY? by Laura Kaar

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  4. Daniel S, Soleymani T, Garvey WT. A complications-based clinical staging of obesity to guide treatment modality and intensity. Curr Opin Endocrinol Diabetes Obes. 2013 Oct;20(5):377-88. doi: 10.1097/01.med.0000433067.01671.f5. PMID: 23974764; PMCID: PMC4139285
  5. Kivimäki M, Strandberg T, Pentti J, Nyberg ST, Frank P, Jokela M, Ervasti J, Suominen SB, Vahtera J, Sipilä PN, Lindbohm JV, Ferrie JE. Body-mass index and risk of obesity-related complex multimorbidity: an observational multicohort study. Lancet Diabetes Endocrinol. 2022 Apr;10(4):253-263
  6. Guh DP, Zhang W, Bansback N et al. The incidence of co-morbidities related to obesity and overweight: A systematic review and meta-analysis. BMC Public Health 9, 88 (2009)
  7. PI-SUNYER, F. XAVIER. Comorbidities of overweight and obesity: current evidence and research issues. Medicine & Science in Sports & Exercise 31(11):p S602, November 1999
  8. Adult obesity and type 2 diabetes (publishing.service.gov.uk)
  9. Obesity and Cancer | CDC
  10. Obesity and Cancer Fact Sheet - NCI
  11. Apovian CM. Obesity: definition, comorbidities, causes, and burden. Am J Manag Care. 2016 Jun;22(7 Suppl):s176-85. PMID: 27356115
  12. Karelis AD. Metabolically healthy but obese individuals. Lancet (London, England). 2008 Oct 11;372(9646):1281-3 
  13. Matthias Blüher, Metabolically Healthy Obesity, Endocrine Reviews, Volume 41, Issue 3, June 2020, https://doi.org/10.1210/endrev/bnaa004
  14. Velho S, Paccaud F, Waeber G, Vollenweider P, Marques-Vidal P. Metabolically healthy obesity: different prevalences using different criteria. Eur J Clin Nutr. 2010 Oct;64(10):1043-51. doi: 10.1038/ejcn.2010.114. Epub 2010 Jul 14. PMID: 20628408
  15. Eckel N, Meidtner K, Kalle-Uhlmann T, Stefan N, Schulze MB. Metabolically healthy obesity and cardiovascular events: A systematic review and meta-analysis. European Journal of Preventive Cardiology. 2016;23(9):956-966
  16. Federico Soriguer, Carolina Gutiérrez-Repiso, Elehazara Rubio-Martín, Eduardo García-Fuentes, María Cruz Almaraz, Natalia Colomo, Isabel Esteva de Antonio, María Soledad Ruiz de Adana, Felipe Javier Chaves, Sonsoles Morcillo, Sergio Valdés, Gemma Rojo-Martínez, Metabolically Healthy but Obese, a Matter of Time? Findings From the Prospective Pizarra Study, The Journal of Clinical Endocrinology & Metabolism, Volume 98, Issue 6, 1 June 2013, Pages 2318–2325
  17. Mongraw-Chaffin M, Foster MC, Anderson CAM, Burke GL, Haq N, Kalyani RR, Ouyang P, Sibley CT, Tracy R, Woodward M, Vaidya D. Metabolically Healthy Obesity, Transition to Metabolic Syndrome, and Cardiovascular Risk. J Am Coll Cardiol. 2018 May 1;71(17):1857-1865
  18. Smith GI, Mittendorfer B, Klein S. Metabolically healthy obesity: facts and fantasies. J Clin Invest. 2019 Oct 1;129(10):3978-3989. doi: 10.1172/JCI129186. PMID: 31524630; PMCID: PMC6763224
  19. Ortega FB, Cadenas-Sanchez C, Migueles JH, Labayen I, Ruiz JR, Sui X, Blair SN, Martínez-Vizcaino V, Lavie CJ. Role of Physical Activity and Fitness in the Characterization and Prognosis of the Metabolically Healthy Obesity Phenotype: A Systematic Review and Meta-analysis. Prog Cardiovasc Dis. 2018 Jul-Aug;61(2):190-205. doi: 10.1016/j.pcad.2018.07.008. Epub 2018 Jul 6. PMID: 30122522
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OMEGA-3 SUPPLEMENTS: FAD OR FUNDAMENTAL FOR HEALTH? By Shazia Faisal

  1. De Filippis AP, Sperling L. Understanding omega-3s. Am. Heart J. 2006;151:564–570. Doi: 10.1016/j.ahj.2005.03.051. [PubMed]
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  3. SACN Advice on Fish Consumption - GOV.UK (www.gov.uk)
  4. Omega-3 (bda.uk.com)
  5. Bradberry JC, Hilleman DE. Overview of omega-3 Fatty Acid therapies. P T. 2013 Nov;38(11):681-91. PMID: 24391388; PMCID: PMC3875260
  6. Djuricic I, Calder PC. Beneficial Outcomes of Omega-6 and Omega-3 Polyunsaturated Fatty Acids on Human Health: An Update for 2021. Nutrients. 2021 Jul 15;13(7):2421. doi: 10.3390/nu13072421. PMID: 34371930; PMCID: PMC8308533
  7. Simopoulos AP. Omega-3 fatty acids in inflammation and autoimmune diseases. J Am Coll Nutr. 2002 Dec;21(6):495-505. doi: 10.1080/07315724.2002.10719248. PMID: 12480795
  8. Gioxari A, Kaliora AC, Marantidou F, Panagiotakos DP. Intake of ω-3 polyunsaturated fatty acids in patients with rheumatoid arthritis: A systematic review and meta-analysis. Nutrition. 2018 Jan;45:114-124.e4. doi: 10.1016/j.nut.2017.06.023. Epub 2017 Jul 8. PMID: 28965775
  9. Cordingley DM, Cornish SM. Omega-3 Fatty Acids for the Management of Osteoarthritis: A Narrative Review. Nutrients. 2022 Aug 16;14(16):3362. doi: 10.3390/nu14163362. PMID: 36014868; PMCID: PMC9413343
  10. Abdelhamid AS, Brown TJ, Brainard JS, Biswas P, Thorpe GC, Moore HJ, Deane KH, Summerbell CD, Worthington HV, Song F, Hooper L. Omega-3 fatty acids for the primary and secondary prevention of cardiovascular disease. Cochrane Database Syst Rev. 2020 Feb 29;3(3):CD003177. doi: 10.1002/14651858.CD003177.pub5. PMID: 32114706; PMCID: PMC7049091
  11. Balta I, Stef L, Pet I, Iancu T, Stef D, Corcionivoschi N. Essential Fatty Acids as Biomedicines in Cardiac Health. Biomedicines. 2021 Oct 14;9(10):1466. doi: 10.3390/biomedicines9101466. PMID: 34680583; PMCID: PMC8533423
  12. Mohebi-Nejad A, Bikdeli B. Omega-3 supplements and cardiovascular diseases. Tanaffos. 2014;13(1):6-14. PMID: 25191488; PMCID: PMC4153275
  13. Adili R, Hawley M, Holinstat M. Regulation of platelet function and thrombosis by omega-3 and omega-6 polyunsaturated fatty acids. Prostaglandins Other Lipid Mediat. 2018 Nov;139:10-18. doi: 10.1016/j.prostaglandins.2018.09.005. Epub 2018 Sep 25. PMID: 30266534; PMCID: PMC6242736
  14. Kander T, Lindblom E, Schött U. Dose-response effects of omega-3 on platelet aggregation: an observational study. J Int Med Res. 2018 Dec;46(12):5074-5082. doi: 10.1177/0300060518789817. Epub 2013
  15. Welty FK. Omega-3 fatty acids and cognitive function. Curr Opin Lipidol. 2023 Feb 1;34(1):12-21. doi: 10.1097/MOL.0000000000000862. Epub 2022 Nov 25. PMID: 36637075
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AI IN HEALTHCARE: ENHANCING PRACTICE WITH TECHNOLOGY by Mike Sweeney

  1. Sun H, Zhang K, Lan W, Gu Q, Jiang G, Yang X, Qin W, Han D. An AI Dietitian for Type 2 Diabetes Mellitus Management Based on Large Language and Image Recognition Models: Preclinical Concept Validation Study. J Med Internet Res. 2023 Nov 9;25:e51300. doi: 10.2196/51300. PMID: 37943581; PMCID: PMC10667983.
  2. Friederichs H, Friederichs WJ, März M. ChatGPT in medical school: how successful is AI in progress testing? Med Educ Online. 2023 Dec;28(1):2220920. doi: 10.1080/10872981.2023.2220920. PMID: 37307503; PMCID: PMC10262795.
  3. Jung, M, Lim C, Lee, C, Kim, S, Kim, J. Human dietitians Vs artificial intelligence: which diet design do you prefer for your children? The Journal of Allergy and Clinical Immunology. 2021 Feb 147;2:AB117. doi: 10.1016/j.jaci.2020.12.430
  4. Ayers JW, Poliak A, Dredze M, et al. Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum. JAMA Intern Med. 2023;183(6):589–596. doi:10.1001/jamainternmed.2023.1838
  5. Daniel Kirk, Elise van Eijnatten, Guido Camps, "Comparison of Answers between ChatGPT and Human Dieticians to Common Nutrition Questions", Journal of Nutrition and Metabolism, vol. 2023, Article ID 5548684, 9 pages, 2023. https://doi.org/10.1155/2023/5548684
  6. Liesbet Van Bulck, Philip Moons, What if your patient switches from Dr. Google to Dr. ChatGPT? A vignette-based survey of the trustworthiness, value, and danger of ChatGPT-generated responses to health questions, European Journal of Cardiovascular Nursing, Volume 23, Issue 1, January 2024, Pages 95–98, https://doi.org/10.1093/eurjcn/zvad038
  7. Ponzo, V.; Goitre, I.; Favaro, E.; Merlo, F.D.; Mancino, M.V.; Riso, S.; Bo, S. Is ChatGPT an Effective Tool for Providing Dietary Advice? Nutrients 2024, 16, 469. https://doi.org/10.3390/nu16040469
  8. Department of Health and Social Care. (2019, August 8). Health Secretary announces £250 million investment in artificial intelligence. GOV.UK. https://www.gov.uk/government/news/health-secretary-announces-250-million-investment-in-artificial-intelligence
  9. Department of Health and Social Care. (2023, June 22). £21 million to roll out artificial intelligence across the NHS. GOV.UK. https://www.gov.uk/government/news/21-million-to-roll-out-artificial-intelligence-across-the-nhs

ARTIFICIAL INTELLIGENCE IN DIETETICS: THE POTENTIAL FOR PROGRESS by Harriet Drennan

  1. Ferrario, P., and Gedrich, K. (2024). “Machine learning and personalized nutrition: a promising liaison?” European Journal of Clinical Nutrition 78 (1), 74-76
  2. Wilson-Barnes, S., Gymnopoulos, L. P., Dimitropoulos, K., Solachidis, V., Rouskas, K., Russell, D., and Hart, K. (2021). “PeRsOnalised nutriTion for hEalthy livINg: The PROTEIN project”. Nutrition Bulletin, 46 (1), 77-87
  3. Lloyd-Price, J., Langille, M. G., and Huttenhower, C. (2022). “Machine learning approaches to diet personalization in the era of microbiome research”. Gut Microbes, 13 (4), 1-17
  4. Karkan, T., Gundogdu, A., Alagozlu, H., Ekmen, N., Ozgul, S., Hora, M., Beyazgul, D, and Nalbantoglu, U. (2022) “Artificial Intelligence based personalized diet: A pilot clinical study for IBS”. Gut Microbes (14), 1
  5. Vulpoi, R. A., Luca, M., Ciobanu, A., Olteanu, A., Bărboi, O., Iov, D.-E., Nichita, L., Ciortescu, I., Prelipcean, C. C., Ștefănescu, G., Mihai, C., and Drug, V. L. (2023). “The Potential Use of Artificial Intelligence in Irritable Bowel Syndrome Management”. Diagnostics, 13 (21), 3336
  6. Apple (2024) Apple Watch [online] available from https://www.apple.com/uk/watch/?afid=p238%7CsYGtK3C9J-dc_mtid_20925xua42643_pcrid_685468386623_pgrid_153845013296_pexid__&cid=wwa-uk-kwgo-watch--slid--productid--Brand-AppleWatch– [22/1/24]
  7. Fitbit (2024) Fitbit App [online] https://www.fitbit.com/global/uk/products/whats-new?utm_medium=sem&utm_source=google&utm_campaign=UK_PF_ROAS&gad_source=1&gclid=Cj0KCQiAwbitBhDIARIsABfFYIIlDuDt57xyRM9lK05wForfoaa05XFToPDzlLqQC8S0tNqS4t1JekEaAvAPEALw_wcB&gclsrc=aw.ds [22/1/24]
  8. Garmin (2024) Smartwatches [online] available from <https://www.garmin.com/en-GB/c/wearables-smartwatches/> [22/1/24]
  9. App Advice (2024) Mango Health [online] available from <https://appadvice.com/app/mango-health/560657279> [17th January 2024]
  10. Nomura, A., Noguchi, M., Kometani, M., Furukawa, K., and Yoneda, Y. (2021) “Artificial Intelligence in Current Diabetes Management and Prediction”. Current Diabetes Reports, (21), 61
  11. Lehmann, V., Zueger, T., Maritsch, M., Kraus, M., Albrecht, C., Bérubé, C., Feuerriegel, S., Wortmann, F., Kowatsch, T., Styger, N., Lagger, S., Laimer, M., Fleisch, E., & Stettler, C. (2023). Machine learning for non-invasive sensing of hypoglycaemia while driving in people with diabetes. Diabetes Obes Metab, 25(6), 1668-1676
  12. Chou, C., Hsu, D., and Chou, C. (2023) “Predicting the Onset of Diabetes with Machine Learning Methods” JPM, (13) 406
  13. Cubillos, G., Monckeberg, M., Plaza, A., Morgan, M., Estevez, P., Choolani, M., et al. (2023) “Development of machine learning models to predict gestational diabetes risk in the first half of pregnancy” BMC Pregnancy Childbirth, (23) 469
  14. Kee, O., Harun, H., Mustafa, N., Abdul Murad, N., Chin, S., Jaafar, R et al. (2023) “Cardiovascular complications in a diabetes prediction model using machine learning: a systematic review”. Cardiovascular Diabetology, (22) 13
  15. Shah, N., Li, Y., Wu, F., Wang, L., Zhou, D., Sun, F., and Wang, Y. (2023). “Prediction of pre-diabetes using artificial intelligence: a prospective cohort study”. PLOS Medicine, 20 (8), 285-561
  16. Tsichlaki, S., Koumakis, L., and Tsiknakis, M. (2022) “Type 1 Diabetes Hypoglycemia Prediction Algorithms: Systematic Review”. JMIR Diabetes, (7), 34699
  17. Mohsen, F., Al-Absi, H., Yousri, N., Hajj, N., and Shah, Z. (2023) "A scoping review of artificial intelligence-based methods for diabetes risk prediction". Digital Medicine (6), 197
  18. Matusheski, N., Caffrey, A., Christensen, L., Mezgec, S., Surendran, S., and Hjorth, M. (2021) “Diets, nutrients, genes and the microbiome: recent advances in personalised nutrition.” British Journal of Nutrition (126), 1489-1497
  19. Mezgec, S., and Koroušić, S. (2017) “NutriNet: A Deep Learning Food and Drink Image Recognition System for Dietary Assessment” Nutrients, 9, 657
  20. Anthimopoulos, M., Dehais, J., Shevchik, S., Ransford, B.H., Duke, D., Diem, P., and Mougiakakou, S. (2015) “Computer vision-based carbohydrate estimation for type 1 patients with diabetes using smartphones”. Journal of Diabetes Science and Technology (9), 507–515
  21. Vasiloglou, M., Mougiakakou, S., Aubry, E., Bokelmann, A., Fricker, R., and Gomes, F. (2018) “ A Comparative Study on Carbohydrate Estimation: GoCARB vs. Dietitians” Nutrients, (10), 741
  22. Mouloudj, K., Oanh, V., Bouarar, A., Bouarar, A., Asanza, D., and Srivastava, M. (2024) "Adopting Artificial Intelligence in Healthcare: A Narrative Review". In: The Use of Artificial Intelligence in Digital Marketing: Competitive Strategies and Tactics. IGI Global
  23. Char, D., Shah, N., and Magnuson, M. (2020). “Algorithmic bias in healthcare: a call for fairness in machine learning”. The Lancet Digital Health, 2(4), 268-270.
  24. Wachter, S., Mittelstadt, B., and Floridi, L. (2023). “Transparency and explainability in artificial intelligence for healthcare: towards trust and responsible implementation”. JAMA Network Open, 6 (6), 230-5846
  25. Woolford, S. J., Resnicow, K., Davis, M., Nichols, L., Wasserman, R., Harris, D., & Baranowski, T. (2022). “Cost-effectiveness of a motivational interviewing obesity intervention versus usual care in pediatric primary care offices”. Obesity, 30 (11), 2265-2274

GENERATIVE ARTIFICIAL INTELLIGENCE: HOW TO USE IT AND WHAT TO LOOK OUT FOR by Aliya Porter

  1. Association for Nutrition (2021) UKVRN Standards of Ethics, Conduct and Performance. Accessed at https://www.associationfornutrition.org/wp-content/uploads/2020/06/AfN-Standards-Ethics-Conduct-Performance.pdf on 3rd January 2024
  2. British Dietetic Association (2017) Code of Professional Conduct. Accessed at https://www.bda.uk.com/static/ef8656c5-320e-4d8d-b5c7ff7c82519d47/Code-of-Conduct.pdf on 3rd January 2024
  3. Russell Group (2023) New principles on the use of AI in education. Accessed at https://russellgroup.ac.uk/news/new-principles-on-use-of-ai-in-education/ on 3rd January 2024
  4. St Mary’s University Twickenham London (2023) Accessed at https://www.stmarys.ac.uk/policies/ai.aspx on 3rd January 2024
  5. Swansea University (2023) Policy on the use of Artificial Intelligence (AI) in student assessment. Accessed at https://myuni.swansea.ac.uk/academic-life/academic-regulations/aqs-policies/policy-on-the-use-of-artificial-intelligence-ai-in-student-assessment on 3rd January 2024
  6. Cancer Research UK (2023) Guidance for researchers on the use of regenerative AI. Accessed at https://www.cancerresearchuk.org/sites/default/files/cancer_research_uk_guidance_for_researchers_on_the_use_of_generative_ai.pdf on 3rd January 2024
  7. Amazon (2023) AWS Responsible AI Policy. Accessed at https://aws.amazon.com/machine-learning/responsible-ai/policy/ on 3rd January 2024
  8. HM Government (2021) National AI Strategy. Accessed at https://assets.publishing.service.gov.uk/media/614db4d1e90e077a2cbdf3c4/National_AI_Strategy_-_PDF_version.pdf on 3rd January 2024
  9. HM Government (2023) A pro-innovation approach to AI regulation. Accessed at https://www.gov.uk/government/publications/ai-regulation-a-pro-innovation-approach

KETOGENIC DIET THERAPY: MORE THAN JUST EPILEPSY by Mike Sweeney

  1. Zhu H, Bi D, Zhang Y, Kong C, Du J, Wu X, Wei Q, Qin H. Ketogenic diet for human diseases: the underlying mechanisms and potential for clinical implementations. Signal Transduct Target Ther. 2022 Jan 17;7(1):11. doi: 10.1038/s41392-021-00831-w. PMID: 35034957; PMCID: PMC8761750
  2. Wheless JW (2008). History of the ketogenic diet. Epilepsia, 49: 35. https://doi.org/10.1111/j.1528-1167.2008.01821.x
  3. Martin-McGill KJ, Bresnahan R, Levy RG, Cooper PN. Ketogenic diets for drug-resistant epilepsy. Cochrane Database Syst Rev. 2020 Jun 24;6(6):CD001903. doi: 10.1002/14651858.CD001903.pub5. PMID: 32588435; PMCID: PMC7387249
  4. Olson CA, Vuong HE, Yano JM, Liang QY, Nusbaum DJ, Hsiao EY. The Gut Microbiota Mediates the Anti-Seizure Effects of the Ketogenic Diet. Cell. 2018 Jun 14;173(7):1728-1741.e13. doi: 10.1016/j.cell.2018.04.027. Epub 2018 May 24. Erratum in: Cell. 2018 Jul 12;174(2):497. PMID: 29804833; PMCID: PMC6003870
  5. Hussain TA, Mathew TC, Dashti AA, Asfar S, Al-Zaid N, Dashti HM. Effect of low-calorie versus low-carbohydrate ketogenic diet in type 2 diabetes. Nutrition. 2012 Oct;28(10):1016-21. doi: 10.1016/j.nut.2012.01.016. Epub 2012 Jun 5. PMID: 22673594
  6. Mohamed Rafiullah, Mohthash Musambil, Satish Kumar David, Effect of a very low-carbohydrate ketogenic diet vs recommended diets in patients with type 2 diabetes: a meta-analysis, Nutrition Reviews, Volume 80, Issue 3, March 2022, Pages 488-502, https://doi.org/10.1093/nutrit/nuab040
  7. Ge L, Sadeghirad B, Ball GDC, da Costa BR, Hitchcock CL, Svendrovski A et al. Comparison of dietary macronutrient patterns of 14 popular named dietary programmes for weight and cardiovascular risk factor reduction in adults: systematic review and network meta-analysis of randomised trials BMJ 2020; 369 :m696 doi:10.1136/bmj.m696
  8. Veldhorst M, Smeets A, Soenen S, Hochstenbach-Waelen A, Hursel R, Diepvens K, Lejeune M, Luscombe-Marsh N, Westerterp-Plantenga M. Protein-induced satiety: effects and mechanisms of different proteins. Physiol Behav. 2008 May 23;94(2):300-7. doi: 10.1016/j.physbeh.2008.01.003. Epub 2008 Jan 12. PMID: 18282589
  9. Johnstone AM, Horgan GW, Murison SD, Bremner DM, Lobley GE. Effects of a high-protein ketogenic diet on hunger, appetite, and weight loss in obese men feeding ad libitum. Am J Clin Nutr. 2008 Jan;87(1):44-55. doi: 10.1093/ajcn/87.1.44. PMID: 18175736
  10. Mansour A, Mirahmad M, Mohajeri-Tehrani MR et al. Risk factors for insulin resistance related to polycystic ovarian syndrome in Iranian population. Sci Rep 13, 10269 (2023). https://doi.org/10.1038/s41598-023-37513-2
  11. Mavropoulos JC, Yancy WS, Hepburn J et al. The effects of a low-carbohydrate, ketogenic diet on the polycystic ovary syndrome: A pilot study. Nutr Metab (Lond) 2, 35 (2005). https://doi.org/10.1186/1743-7075-2-35
  12. Gower BA, Chandler-Laney PC, Ovalle F, Goree LL, Azziz R, Desmond RA, Granger WM, Goss AM, Bates GW. Favourable metabolic effects of a eucaloric lower-carbohydrate diet in women with PCOS. Clin Endocrinol (Oxf). 2013 Oct;79(4):550-7. doi: 10.1111/cen.12175. Epub 2013 May 20. PMID: 23444983; PMCID: PMC4111472
  13. Nuss P. Anxiety disorders and GABA neurotransmission: a disturbance of modulation. Neuropsychiatr Dis Treat. 2015 Jan 17;11:165-75. doi: 10.2147/NDT.S58841. PMID: 25653526; PMCID: PMC4303399
  14. IJff DM, Postulart D, Lambrechts DAJE, Majoie MHJM, de Kinderen RJA, Hendriksen JGM, Evers SMAA, Aldenkamp AP. Cognitive and behavioural impact of the ketogenic diet in children and adolescents with refractory epilepsy: A randomised controlled trial. Epilepsy Behav. 2016 Jul;60:153-157. doi: 10.1016/j.yebeh.2016.04.033. Epub 2016 May 18. PMID: 27206235
  15. Bostock EC, Kirkby KC, Taylor BV. The Current Status of the Ketogenic Diet in Psychiatry. Front Psychiatry. 2017 Mar 20;8:43. doi: 10.3389/fpsyt.2017.00043. PMID: 28373848; PMCID: PMC5357645
  16. Campbell IH, Campbell H. Ketosis and bipolar disorder: controlled analytic study of online reports. BJPsych Open. 2019 Jul 4;5(4):e58. doi: 10.1192/bjo.2019.49. PMID: 31530294; PMCID: PMC6620566
  17. Danan A, Westman EC, Saslow LR, Ede G. The Ketogenic Diet for Refractory Mental Illness: A Retrospective Analysis of 31 Inpatients. Front Psychiatry. 2022 Jul 6;13:951376. doi: 10.3389/fpsyt.2022.951376. PMID: 35873236; PMCID: PMC9299263
  18. Lexchin J, Bero LA, Djulbegovic B, Clark O. Pharmaceutical industry sponsorship and research outcome and quality: systematic review. BMJ. 2003 May 31;326(7400):1167-70. doi: 10.1136/bmj.326.7400.1167. PMID: 12775614; PMCID: PMC156458

CMPA MANAGEMENT: A BRIEF GUIDE by Barira Saad, RD

  1. https://gpifn.files.wordpress.com/2019/10/imap_patient_factsheet_original.pdf
  2. https://www.allergyuk.org/resources/cows-milk-free-diet-information-for-babies-and-children/
  3. https://gpifn.files.wordpress.com/2019/10/imap_final_ladder-may_2017_original.pdf
  4. https://gpifn.files.wordpress.com/2019/10/imap-recipes_final_original.pdf
  5. https://learndietetics.com/cows-milk-protein-allergy-guide/
  6. https://www.alderhey.nhs.uk/conditions/patient-information-leaflets/cows-milk-protein-allergy-delayed/
  7. https://infantandtoddlerforum.org/media/upload/pdf-downloads/suitable-milks-for-cows-milk-allergy_1.pdf
  8. https://www.nutricia.co.uk/hcp/where-we-specialise/cows-milk-allergy/cmpa-weaning.html#accordion-dd7ab5c412-item-4f22812aed
  9. https://www.alderhey.nhs.uk/conditions/patient-information-leaflets/cows-milk-protein-allergy-delayed/
  10. https://cks.nice.org.uk/topics/cows-milk-allergy-in-children/management/suspected-cows-milk-allergy/

WILTSHIRE FARM FOODS DIETITIANS - FROM HOSPITAL TO HOME: NUTRITIONAL CARE PLANS by Sophia Cornelius

  1. Kumar A, Sinha P. How to manage a MFFD patient in the acute hospital settings? Postgraduate Medical Journal. 2020 Nov 12;98(1156):153–4. doi:10.1136/postgradmedj-2020-139187
  2. Ng DH, Koh FH, Yeong HE, Huey TC, Chue KM, Foo FJ, et al. Nutrition care after hospital discharge in Singapore: Evidence-based best-practice recommendations. Nutrients. 2023 Oct 24;15(21):4492. doi:10.3390/nu15214492
  3. Hestevik CH, Molin M, Debesay J, Bergland A, Bye A. Older patients’ and their family caregivers’ perceptions of food, meals and nutritional care in the transition between hospital and home care: A qualitative study. BMC Nutrition. 2020 Mar 18;6(1). doi:10.1186/s40795-020-00335-w
  4. Yu D. Loneliness and malnutrition [Internet]. 2020 [cited 2024 Feb 23]. Available from: https://www.bda.uk.com/resource/loneliness-and-malnutrition.html#:~:text=Loneliness%20is%20a%20significant%20risk%20factor%20of%20malnutrition,index%20compared%20with%20those%20living%20with%20their%20family.

TRANSITIONING A PATIENT FROM HOSPITAL TO HOME by Clara Carr

  1. 1 Transition Between Inpatient Hospital Settings and Community or Care Home Settings for adults with social care needs. NICE guidelines [NG27] 2015.

DYSPHAGIA MANAGEMENT IN HOSPITAL by Katy Stuart

  1. Speyer, R, Sandekkbraten, A, Rosseland, I and Moore, J. (2022.) Dysphagia Care and Management in Rehabilitation: A National Survey J Clin Med. Oct; 11(19): 5730. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9571108/
  2. Cichero, J. (2013). Thickening agents used for dysphagia management: effect on bioavailability of water, medication and feelings of satiety. Nutrition Journal vol 12:54. https://nutritionj.biomedcentral.com/articles/10.1186/1475-2891-12-54#
  3. (2023). Dysphagia (swallowing problems). https://www.nhs.uk/conditions/swallowing-problems-dysphagia/
  4. Research Outreach. (2020.) Thickeners: The evidence for their appropriate use in dysphagia management. https://researchoutreach.org/articles/thickeners-evidence-appropriate-use-dysphagia-management/
  5. Scottish Acquired Brain Injury Network. (2023) A Team Approach to Dysphagia Management. https://www.acquiredbraininjury-education.scot.nhs.uk/impact-of-abi/swallowing-problems/management-of-dysphagia/a-team-approach/
  6. Holdoway, A, Smith, A. (2019.) Dysphagia A HEALTHCARE PROFESSIONAL FACT SHEET. https://www.malnutritionpathway.co.uk/dysphagia.pdf
  7. Davies, S. (2002.) An interdisciplinary approach to the management of dysphagia. Nursing Times. https://www.nursingtimes.net/archive/an-interdisciplinary-approach-to-the-management-of-dysphagia-01-09-2002/
  8. Royal College of Physicians. (2016.) Stroke guidelines. https://www.rcplondon.ac.uk/guidelines-policy/stroke-guidelines-2016
  9. (2023) Dysphagia and thickeners. https://www.cqc.org.uk/guidance-providers/adult-social-care/dysphagia-thickeners
  10. Raheem, D, Carrascosa, C, Ramos, F, Saraiva, A and Raposo, A. (2021.) Texture-Modified Food for Dysphagic Patients: A Comprehensive Review. Int J Environ Res Public Health. 2021 May; 18(10): 5125. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8150365/
  11. Rudd, C. Dysphagia and the use of thickeners. (2017.) NHS Sheffield, CCG. https://www.sheffieldccg.nhs.uk/Downloads/Our%20strategy/Care%20Home%20Resources/Dysphagia%20and%20the%20use%20of%20thickeners.pdf
  12. NHS Frimley. (2022.) Guidance for Prescribing Thickeners for Adults with Dysphagia. https://www.frimley.icb.nhs.uk/policies-and-documents/medicines-optimisation/prescribing-guidelines-1/nutrition-and-blood/1049-guidance-for-prescribing-thickeners-for-adults-with-dysphagia/file
  13. NHS Hertford and West Sussex Integrated Care Board. (2022.) Healthcare professional guide: Thickeners & thickening ONS. https://hertsandwestessex.icb.nhs.uk/downloads/file/265/thickeners-and-thickened-ons-guidance
  14. International Dysphagia Diet Standardisation Initiative. (2019.) The IDDSI Framework. https://iddsi.org/framework/
  15. Rosenberg, H. Aging Care. (2023.) Swallowing Disorders: Tips for Using Food and Beverage Thickeners. https://www.agingcare.com/articles/swallowing-disorders-tips-for-using-food-and-beverage-thickeners-208048.htm
  16. Salle, J, Tchalla, A, Thirion, R, Offret, Dussaulx, A, Trivin, F, Gayot, C, Fayemendy, P, Jésus, P, Bonhomme, C, Hazart, E,  Baudry, C  & Desport, J. (2021) Efficacy of a Ready-to-Drink Gelled Water and of a Thickening Powder in Patients with Oropharyngeal Dysphagia: a Crossover Randomized Study. Medicine. Vol 3: 2244–2250. https://link.springer.com/article/10.1007/s42399-021-00828-0
  17. Science of Cooking. (2024.) Food Thickening Agents. https://www.scienceofcooking.com/food-thickening-agents.html
  18. Penney, B. (2014.) Use of fluid thickener to reduce dysphagia risk. Nursing Times https://www.nursingtimes.net/clinical-archive/respiratory-clinical-archive/use-of-fluid-thickener-to-reduce-dysphagia-risk-14-03-2014/
  19. Uk. (2021.) Polyethylene glycol (PEG) laxatives and starch-based thickeners: potential interactive effect when mixed, leading to an increased risk of aspiration. https://www.gov.uk/drug-safety-update/polyethylene-glycol-peg-laxatives-and-starch-based-thickeners-potential-interactive-effect-when-mixed-leading-to-an-increased-risk-of-aspiration
  20. Duncan, D, Larson, K, Rosen, R. (2019.) Clinical aspects of thickeners for pediatric gastroesophageal reflux and oropharyngeal dysphagia. Curr Gastroenterol. May 16; 21(7): 30.
  21. Specialist Pharmacy Service. (2021) Using thickeners of different types for patients with swallowing difficulties. https://www.sps.nhs.uk/articles/using-thickeners-of-different-types-for-patients-with-swallowing-difficulties/
  22. Done, M. (2021) Safety concerns over parallel imports of thickeners and thickened ONS. https://www.linkedin.com/pulse/safety-concerns-over-parallel-imports-thickeners-thickened-done/
  23. Royal College of Speech and Language Therapists. (2018.) Dietetic Supplements IDDSI Dysphagia Compliance Tested Reference List. https://www.rcslt.org/members/clinical-guidance/dysphagia/thickened-fluids/?search-query=supplements&page=0#search-open
  24. Fresenius Kabi (2020.) IDDSI Framework and Fresubin® Oral Nutritional Supplements (ONS). https://ggcmedicines.org.uk/media/1ftfgd3g/fresubin-ons-iddsi-levels-oct-2020-final-2.pdf
  25. NHS Greater Glasgow and Clyde. (2022.) Suitable Oral Nutritional Supplements for Adult Patients Who Require Thickened Fluids in a Homely Setting – a Guide For Staff. https://ggcmedicines.org.uk/media/cjcnpsxp/ons-a-guide-for-staff-2211.pdf

THE LAST WORD with Fareeha Jay, RD

  1. Ge L, Sadeghirad B, Ball GDC, da Costa BR, Hitchcock CL, Svendrovski A, Kiflen R, Quadri K, Kwon HY, Karamouzian M, Adams-Webber T, Ahmed W Damanhoury S, Zeraatkar D, Nikolakopoulou A, Tsuyuki RT, Tian J, Yang K, Guyatt GH, Johnston BC. Comparison of dietary macronutrient patterns of 14 popular named dietary programmes for weight and cardiovascular risk factor reduction in adults: systematic review and network meta-analysis of randomised trials. BMJ 2020 Apr 1;369:m696. doi: 10.1136/bmj.m696. Erratum in: BMJ. 2020 Aug 5;370:m3095. PMID: 32238384; PMCID: PMC7190064
  2. Hall KD, Kahan S. Maintenance of Lost Weight, and Long-Term Management of Obesity. Med Clin North Am. 2018 Jan;102(1):183-197. doi: 10.1016/j.mcna.2017.08.012. PMID: 29156185; PMCID: PMC5764193
  3. Sarwer DB, Polonsky HM. The Psychosocial Burden of Obesity. Endocrinol Metab Clin North Am. 2016 Sep;45(3):677-88. doi: 10.1016/j.ecl.2016.04.016. PMID: 27519139; PMCID: PMC6052856
  4. Contreras RE, Schriever SC, Pfluger PT. Physiological and Epigenetic Features of Yoyo Dieting and Weight Control. Front Genet. 2019 Dec 11;10:1015. doi: 10.3389/fgene.2019.01015. PMID: 31921275; PMCID: PMC6917653
  5. Tahreem A, Rakha A, Rabail R, Nazir A, Socol CT, Maerescu CM, Aadil RM. Fad Diets: Facts and Fiction. Front Nutr. 2022 Jul 5; 9:960922. doi: 10.3389/fnut.2022.960922. PMID: 35866077; PMCID: PMC9294402
  6. Memon AN, Gowda AS, Rallabhandi B, Bidika E, Fayyaz H, Salib M, Cancarevic I. Have Our Attempts to Curb Obesity Done More Harm Than Good? Cureus. 2020 Sep 6;12(9): e10275. doi: 10.7759/cureus.10275. PMID: 33042711; PMCID: PMC7538029
  7. Robert Dent, Ruth McPherson, Mary-Ellen Harper, Factors affecting weight loss variability in obesity, Metabolism,https://doi.org/10.1016/j.metabol.2020.154388
  8. Eikey EV. Effects of diet and fitness apps on eating disorder behaviours: qualitative study. BJPsych Open. 2021 Sep 24;7(5): e176. doi: 10.1192/bjo.2021.1011. PMCID: PMC8485346
  9. Lesser LI, Thompson CA, Luft HS. Association Between Monetary Deposits and Weight Loss in Online Commitment Contracts. Am J Health Promot. 2018 Jan;32(1):198-204. doi: 10.1177/0890117116661157. Epub 2016 Aug 8. PMID: 27502832; PMCID: PMC5316505