[en] Glycaemic control (GC) in intensive care unit is challenging due to significant inter- and intra-patient variability,
leading to increased risk of hypoglycaemia. Recent work showed higher insulin resistance in female preterm
neonates. This study aims to determine if there are differences in inter- and intra-patient metabolic variability
between sexes in adults, to gain in insight into any differences in metabolic response to injury. Any significant
difference would suggest GC and randomised trial design should consider sex differences to personalise care.
Methods
Insulin sensitivity (SI) levels and variability are identified from retrospective clinical data for men and women.
Data are divided using 6-h blocks to capture metabolic evolution over time. In total, 91 male and 54 female
patient GC episodes of minimum 24 h are analysed. Hypothesis testing is used to determine whether
differences are significant (P < 0.05), and equivalence testing is used to assess whether these differences can
be considered equivalent at a clinical level. Data are assessed for the raw cohort and in 100 Monte Carlo
simulations analyses where the number of men and women are equal.
Results
Demographic data between females and males were all similar, including GC outcomes (safety from
hypoglycaemia and high (> 50%) time in target band). Females had consistently significantly lower SI levels than
males, and this difference was not clinically equivalent. However, metabolic variability between sexes was never
significantly different and always clinically equivalent. Thus, inter-patient variability was significantly different
between males and females, but intra-patient variability was equivalent.
Conclusion
Given equivalent intra-patient variability and significantly greater insulin resistance, females can receive the
same benefit from safe, effective GC as males, but may require higher insulin doses to achieve the same
glycaemia. Clinical trials should consider sex differences in protocol design and outcome analyses.
Research Center/Unit :
GIGA - In silico Medicine
Disciplines :
Anesthesia & intensive care Endocrinology, metabolism & nutrition Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Uyttendaele, Vincent ; Université de Liège - ULiège > In silico-Model-based therapeutics, Critical Care Basic Sc.
Chase, J. Geoffrey
Knopp, Jennifer L.
Gottlieb, Rebecca
Shaw, Geoffrey M.
Desaive, Thomas ; Université de Liège - ULiège > Département d'astrophys., géophysique et océanographie (AGO) > Thermodynamique des phénomènes irréversibles
Language :
English
Title :
Insulin sensitivity in critically ill patients: are women more insulin resistant?
scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.
Bibliography
McCowen KC, Malhotra A, Bistrian BR. Stress-induced hyperglycemia. Crit Care Clin. 2001;17:107–24. DOI: 10.1016/S0749-0704(05)70154-8
Ali NA, O’Brien JM, Dungan K, Phillips G, Marsh CB, Lemeshow S, Connors AF, Preiser JC. Glucose variability and mortality in patients with sepsis. Crit Care Med. 2008;36:2316–21. DOI: 10.1097/CCM.0b013e3181810378
Capes SE, Hunt D, Malmberg K, Gerstein HC. Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic overview. Lancet. 2000;355:773–8. DOI: 10.1016/S0140-6736(99)08415-9
Van den Berghe G, Wouters P, Weekers F, Verwaest C, Bruyninckx F, Schetz M, Vlasselaers D, Ferdinande P, Lauwers P, Bouillon R. Intensive insulin therapy in critically ill patients. N Engl J Med. 2001;345:1359–67. DOI: 10.1056/NEJMoa011300
Krinsley JS. Effect of an intensive glucose management protocol on the mortality of critically ill adult patients. Mayo Clin Proc. 2004;79:992–1000. DOI: 10.4065/79.8.992
Chase JG, Shaw G, Le Compte A, Lonergan T, Willacy M, Wong XW, Lin J, Lotz T, Lee D, Hann C. Implementation and evaluation of the SPRINT protocol for tight glycaemic control in critically ill patients: a clinical practice change. Crit Care. 2008;12:R49. DOI: 10.1186/cc6868
Reed CC, Stewart RM, Sherman M, Myers JG, Corneille MG, Larson N, Gerhardt S, Beadle R, Gamboa C, Dent D, et al. Intensive insulin protocol improves glucose control and is associated with a reduction in intensive care unit mortality. J Am Coll Surg. 2007;204:1048–54 (Discussion 1054-1045). DOI: 10.1016/j.jamcollsurg.2006.12.047
Finfer S, Chittock DR, Su SY, Blair D, Foster D, Dhingra V, Bellomo R, Cook D, Dodek P, Henderson WR, et al. Intensive versus conventional glucose control in critically ill patients. N Engl J Med. 2009;360:1283–97. DOI: 10.1056/NEJMoa0810625
Preiser JC, Devos P, Ruiz-Santana S, Melot C, Annane D, Groeneveld J, Iapichino G, Leverve X, Nitenberg G, Singer P, et al. A prospective randomised multi-centre controlled trial on tight glucose control by intensive insulin therapy in adult intensive care units: the Glucontrol study. Intensive Care Med. 2009;35:1738–48. DOI: 10.1007/s00134-009-1585-2
Brunkhorst FM, Engel C, Bloos F, Meier-Hellmann A, Ragaller M, Weiler N, Moerer O, Gruendling M, Oppert M, Grond S, et al. Intensive insulin therapy and pentastarch resuscitation in severe sepsis. N Engl J Med. 2008;358:125–39. DOI: 10.1056/NEJMoa070716
Marik PE, Preiser JC. Toward understanding tight glycemic control in the ICU: a systematic review and metaanalysis. Chest. 2010;137:544–51. DOI: 10.1378/chest.09-1737
Griesdale DE, de Souza RJ, van Dam RM, Heyland DK, Cook DJ, Malhotra A, Dhaliwal R, Henderson WR, Chittock DR, Finfer S, Talmor D. Intensive insulin therapy and mortality among critically ill patients: a meta-analysis including NICE-SUGAR study data. CMAJ. 2009;180:821–7. DOI: 10.1503/cmaj.090206
Wiener RS, Wiener DC, Larson RJ. Benefits and risks of tight glucose control in critically ill adults: a meta-analysis. JAMA. 2008;300:933–44. DOI: 10.1001/jama.300.8.933
Arabi YM, Dabbagh OC, Tamim HM, Al-Shimemeri AA, Memish ZA, Haddad SH. Intensive versus conventional insulin therapy: a randomized controlled trial in medical and surgical critically ill patients. Crit Care Med. 2008;36:3190–7. DOI: 10.1097/CCM.0b013e31818f21aa
Rosa C, Donado JH, Restrepo AH, Quintero AM, Gonzalez LG, Saldarriaga NE. Strict glycaemic control in patients hospitalised in a mixed medical and surgical intensive care unit: a randomised clinical trial. Crit Care. 2008;12:R120. DOI: 10.1186/cc7017
Suhaimi F, Le Compte A, Preiser JC, Shaw GM, Massion P, Radermecker R, Pretty CG, Lin J, Desaive T, Chase JG. What makes tight glycemic control tight? The impact of variability and nutrition in two clinical studies. J Diabetes Sci Technol. 2010;4:284–98. DOI: 10.1177/193229681000400208
Waeschle RM, Moerer O, Hilgers R, Herrmann P, Neumann P, Quintel M. The impact of the severity of sepsis on the risk of hypoglycaemia and glycaemic variability. Crit Care. 2008;12:R129. DOI: 10.1186/cc7097
Finfer S, Liu B, Chittock DR, Norton R, Myburgh JA, McArthur C, Mitchell I, Foster D, Dhingra V, Henderson WR, et al. Hypoglycemia and risk of death in critically ill patients. N Engl J Med. 2012;367:1108–18. DOI: 10.1056/NEJMoa1204942
Krinsley JS, Schultz MJ, Spronk PE, Harmsen RE, Braam HF, Sluijs JP. Mild hypoglycemia is independently associated with increased mortality in the critically ill. Crit Care. 2011;15:P397. DOI: 10.1186/cc9817
Egi M, Bellomo R, Stachowski E, French CJ, Hart GK, Taori G, Hegarty C, Bailey M. Hypoglycemia and outcome in critically ill patients. Mayo Clin Proc. 2010;85:217–24. DOI: 10.4065/mcp.2009.0394
Vanhorebeek I, Gunst J, Van den Berghe G. Critical Care management of stress-induced hyperglycemia. Curr Diab Rep. 2018;18:17. DOI: 10.1007/s11892-018-0988-2
Chase JG, Dickson J. Traversing the valley of glycemic control despair. Crit Care. 2017;21:212. DOI: 10.1186/s13054-017-1824-9
Uyttendaele V, Knopp JL, Shaw GM, Desaive T, Chase JG. Is intensive insulin therapy the scapegoat for or cause of hypoglycaemia and poor outcome? IFAC J Syst Control. 2019;9:100063. DOI: 10.1016/j.ifacsc.2019.100063
Bagshaw SM, Bellomo R, Jacka MJ, Egi M, Hart GK, George C. The impact of early hypoglycemia and blood glucose variability on outcome in critical illness. Crit Care. 2009;13:R91. DOI: 10.1186/cc7921
Chase JG, Preiser JC, Dickson JL, Pironet A, Chiew YS, Pretty CG, Shaw GM, Benyo B, Moeller K, Safaei S, et al. Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them. Biomed Eng Online. 2018;17:24. DOI: 10.1186/s12938-018-0455-y
Egi M, Bellomo R, Stachowski E, French CJ, Hart G. Variability of blood glucose concentration and short-term mortality in critically ill patients. Anesthesiology. 2006;105:244–52. DOI: 10.1097/00000542-200608000-00006
Krinsley JS. Glycemic variability: a strong independent predictor of mortality in critically ill patients. Crit Care Med. 2008;36:3008–13. DOI: 10.1097/CCM.0b013e31818b38d2
Le Compte AJ, Pretty CG, Lin J, Shaw GM, Lynn A, Chase JG. Impact of variation in patient response on model-based control of glycaemia in critically ill patients. Comput Methods Programs Biomed. 2013;109:211–9. DOI: 10.1016/j.cmpb.2011.08.007
Kauffmann RM, Hayes RM, Buske BD, Norris PR, Campion TR, Dortch M. Increasing blood glucose variability heralds hypoglycemia in the critically ill. J Surg Res. 2011;170:257–64. DOI: 10.1016/j.jss.2011.03.008
Chase JG, Le Compte AJ, Suhaimi F, Shaw GM, Lynn A, Lin J, Pretty CG, Razak N, Parente JD, Hann CE, et al. Tight glycemic control in critical care–the leading role of insulin sensitivity and patient variability: a review and model-based analysis. Comput Methods Programs Biomed. 2011;102:156–71. DOI: 10.1016/j.cmpb.2010.11.006
Chase JG, Desaive T, Bohe J, Cnop M, De Block C, Gunst J, Hovorka R, Kalfon P, Krinsley J, Renard E, Preiser JC. Improving glycemic control in critically ill patients: personalized care to mimic the endocrine pancreas. Crit Care. 2018;22:182. DOI: 10.1186/s13054-018-2110-1
Chase JG, Le Compte AJ, Preiser JC, Shaw GM, Penning S, Desaive T. Physiological modeling, tight glycemic control, and the ICU clinician: what are models and how can they affect practice? Ann Intensive Care. 2011;1:11. DOI: 10.1186/2110-5820-1-11
Chase JG, Benyo B, Desaive T. Glycemic control in the intensive care unit: a control systems perspective. Annual Reviews in Control. 2019;48:359–68. DOI: 10.1016/j.arcontrol.2019.03.007
Stewart KW, Pretty CG, Tomlinson H, Thomas FL, Homlok J, Noemi SN, Illyes A, Shaw GM, Benyo B, Chase JG. Safety, efficacy and clinical generalization of the STAR protocol: a retrospective analysis. Ann Intensive Care. 2016;6:24. DOI: 10.1186/s13613-016-0125-9
Mesotten D, Dubois J, Van Herpe T, van Hooijdonk RT, Wouters R, Coart D, Wouters P, Van Assche A, Veraghtert G, De Moor B, et al. Software-guided versus nurse-directed blood glucose control in critically ill patients: the LOGIC-2 multicenter randomized controlled clinical trial. Crit Care. 2017;21:212. DOI: 10.1186/s13054-017-1799-6
Van Herpe T, Mesotten D, Wouters PJ, Herbots J, Voets E, Buyens J, De Moor B, Van den Berghe G. LOGIC-insulin algorithm-guided versus nurse-directed blood glucose control during critical illness: the LOGIC-1 single-center, randomized, controlled clinical trial. Diabetes Care. 2013;36:188–94. DOI: 10.2337/dc12-0584
Hovorka R, Kremen J, Blaha J, Matias M, Anderlova K, Bosanska L, Roubicek T, Wilinska ME, Chassin LJ, Svacina S, Haluzik M. Blood glucose control by a model predictive control algorithm with variable sampling rate versus a routine glucose management protocol in cardiac surgery patients: a randomized controlled trial. J Clin Endocrinol Metab. 2007;92:2960–4. DOI: 10.1210/jc.2007-0434
Stewart KW, Chase JG, Pretty CG, Shaw GM. Nutrition delivery of a model-based ICU glycaemic control system. Ann Intensive Care. 2018;8:4. DOI: 10.1186/s13613-017-0351-9
Chase JG, Pretty CG, Pfeifer L, Shaw GM, Preiser JC, Le Compte AJ, Lin J, Hewett D, Moorhead KT, Desaive T. Organ failure and tight glycemic control in the SPRINT study. Crit Care. 2010;14:R154. DOI: 10.1186/cc9224
Dickson JL, Chase JG, Gunn CA, Pretty C, Lynn A, Alsweiler J. Gender and glycaemia: insulin sensitivity and secretion in premature neonates. IFAC Proceedings Volumes. 2014;47:10168–73. DOI: 10.3182/20140824-6-ZA-1003.00212
Dickson JL, Alsweiler J, Gunn CA, Pretty CG, Chase JG. A C-Peptide-based model of pancreatic insulin secretion in extremely preterm neonates in intensive care. J Diabetes Sci Technol. 2015;10:111–8. DOI: 10.1177/1932296815596175
Dickson JL, Chase JG, Pretty CG, Gunn CA, Alsweiler JM. Hyperglycaemic preterm babies have sex differences in insulin secretion. Neonatology. 2015;108:93–8. DOI: 10.1159/000381206
Kwiatkowski K, Coe K, Bailar JC, Swanson GM. Inclusion of minorities and women in cancer clinical trials, a decade later: Have we improved? Cancer. 2013;119:2956–63. DOI: 10.1002/cncr.28168
Schiebinger L. Women’s health and clinical trials. J Clin Invest. 2003;112:973–7.
Sherman LA, Temple R, Merkatz RB. Women in clinical trials: an FDA perspective. Science. 1995;269:793–5. DOI: 10.1126/science.7638593
Ruiz Cantero MT, Angeles Pardo M. European Medicines Agency policies for clinical trials leave women unprotected. J Epidemiol Community Health. 2006;60:911–3. DOI: 10.1136/jech.2006.048769
Office UGA: Women’s health: FDA needs to ensure more study of gender differences in prescription drug testing. 1992:39; 39.
Merkatz RB, Temple R, Subel S, Feiden K, Kessler DA. Women in clinical trials of new drugs. A change in food and drug administration policy. The working group on women in clinical trials. N Engl J Med. 1993;329:292–6. DOI: 10.1056/NEJM199307223290429
Jackson G. Pain and Prejudice. Australia: Allen and Unwin; 2019.
Evans A, Le Compte A, Tan CS, Ward L, Steel J, Pretty CG, Penning S, Suhaimi F, Shaw GM, Desaive T, Chase JG. Stochastic targeted (STAR) glycemic control: design, safety, and performance. J Diabetes Sci Technol. 2012;6:102–15. DOI: 10.1177/193229681200600113
Fisk LM, Le Compte AJ, Shaw GM, Penning S, Desaive T, Chase JG. STAR development and protocol comparison. IEEE Trans Biomed Eng. 2012;59:3357–64. DOI: 10.1109/TBME.2012.2214384
Lin J, Razak NN, Pretty CG, Le Compte A, Docherty P, Parente JD, Shaw GM, Hann CE, Geoffrey Chase J. A physiological Intensive Control Insulin-Nutrition-Glucose (ICING) model validated in critically ill patients. Comput Methods Programs Biomed. 2011;102:192–205. DOI: 10.1016/j.cmpb.2010.12.008
Docherty PD, Chase JG, David T. Characterisation of the iterative integral parameter identification method. Med Biol Eng Comput. 2012;50:127–34. DOI: 10.1007/s11517-011-0851-y
Dickson JL, Stewart KW, Pretty CG, Flechet M, Desaive T, Penning S, Lambermont BC, Benyo B, Shaw GM, Chase JG. Generalisability of a virtual trials method for glycaemic control in intensive care. IEEE Transact Biomed Eng. 2017;65:1543–53. DOI: 10.1109/TBME.2017.2686432
Langouche L, Vander Perre S, Wouters PJ, D’Hoore A, Hansen TK, Van den Berghe G. Effect of intensive insulin therapy on insulin sensitivity in the critically ill. J Clin Endocrinol Metab. 2007;92:3890–7. DOI: 10.1210/jc.2007-0813
Pretty CG, Le Compte AJ, Chase JG, Shaw GM, Preiser JC, Penning S, Desaive T. Variability of insulin sensitivity during the first 4 days of critical illness: implications for tight glycemic control. Ann Intensive Care. 2012;2:17. DOI: 10.1186/2110-5820-2-17
Lin J, Lee D, Chase JG, Shaw GM, Le Compte A, Lotz T, Wong J, Lonergan T, Hann CE. Stochastic modelling of insulin sensitivity and adaptive glycemic control for critical care. Comput Methods Programs Biomed. 2008;89:141–52. DOI: 10.1016/j.cmpb.2007.04.006
Le Compte AJ, Lee DS, Chase JG, Lin J, Lynn A, Shaw GM. Blood glucose prediction using stochastic modeling in neonatal intensive care. IEEE Trans Biomed Eng. 2010;57:509–18. DOI: 10.1109/TBME.2009.2035517
Lin J, Lee D, Chase JG, Shaw GM, Hann CE, Lotz T, Wong J. Stochastic modelling of insulin sensitivity variability in critical care. Biomed Signal Process Control. 2006;1:229–42. DOI: 10.1016/j.bspc.2006.09.003
Motulsky H. Intuitive biostatistics: a nonmathematical guide to statistical thinking. New York: Oxford University Press; 2014.
Motulsky H. Common misconceptions about data analysis and statistics. Br J Pharmacol. 2015;172:200–5. DOI: 10.1111/bph.12884
Fethney J. Statistical and clinical significance, and how to use confidence intervals to help interpret both. Aust Crit Care. 2010;23:93–7. DOI: 10.1016/j.aucc.2010.03.001
Krinsley JS, Preiser JC. Time in blood glucose range 70 to 140 mg/dl >80% is strongly associated with increased survival in non-diabetic critically ill adults. Crit Care. 2015;19:179. DOI: 10.1186/s13054-015-0908-7
Penning S, Chase JG, Preiser JC, Pretty CG, Signal M, Melot C, Desaive T. Does the achievement of an intermediate glycemic target reduce organ failure and mortality? A post hoc analysis of the Glucontrol trial. J Crit Care. 2014;29:374–9. DOI: 10.1016/j.jcrc.2014.01.013
Signal M, Le Compte A, Shaw GM, Chase JG. Glycemic levels in critically ill patients: are normoglycemia and low variability associated with improved outcomes? J Diabetes Sci Technol. 2012;6:1030–7. DOI: 10.1177/193229681200600506
Cerra FB, Benitez MR, Blackburn GL, Irwin RS, Jeejeebhoy K, Katz DP, Pingleton SK, Pomposelli J, Rombeau JL, Shronts E, et al. Applied nutrition in ICU patients. A consensus statement of the American College of Chest Physicians. Chest. 1997;111:769–78. DOI: 10.1378/chest.111.3.769
Stewart KW, Chase JG, Pretty CG, Shaw GM. Nutrition delivery, workload and performance in a model-based ICU glycaemic control system. Comput Methods Programs Biomed. 2018;166:9–18. DOI: 10.1016/j.cmpb.2018.09.005
Lotz TF, Chase JG, McAuley KA, Lee DS, Lin J, Hann CE, Mann JI. Transient and steady-state euglycemic clamp validation of a model for glycemic control and insulin sensitivity testing. Diabetes Technol Ther. 2006;8:338–46. DOI: 10.1089/dia.2006.8.338
McAuley KA, Berkeley JE, Docherty PD, Lotz TF, Te Morenga LA, Shaw GM, Williams SM, Chase JG, Mann JI. The dynamic insulin sensitivity and secretion test–a novel measure of insulin sensitivity. Metabolism. 2011;60:1748–56. DOI: 10.1016/j.metabol.2011.05.009
Docherty PD, Chase JG, Lotz TF, Hann CE, Shaw GM, Berkeley JE. Independent cohort cross-validation of the real-time DISTq estimation of insulin sensitivity. Comput Methods Programs Biomed. 2011;102:94–104. DOI: 10.1016/j.cmpb.2010.08.002
Lheureux O, Preiser JC. Year in review 2013: Critical Care–metabolism. Crit Care. 2014;18:571. DOI: 10.1186/s13054-014-0571-4
Preiser JC, Ichai C, Orban JC, Groeneveld AB. Metabolic response to the stress of critical illness. Br J Anaesth. 2014;113:945–54. DOI: 10.1093/bja/aeu187
Losser MR, Damoisel C, Payen D. Bench-to-bedside review: Glucose and stress conditions in the intensive care unit. Crit Care. 2010;14:231. DOI: 10.1186/cc9100
Nechas E, Foley F. Unequal treatment: what you don’t know about how women are mistreated by the medical community. New York: Simon & Schuste; 1994.
Flanagan DE, Holt RI, Owens PC, Cockington RJ, Moore VM, Robinson JS, Godsland IF, Phillips DI. Gender differences in the insulin-like growth factor axis response to a glucose load. Acta Physiol. 2006;187:371–8. DOI: 10.1111/j.1748-1716.2006.01581.x
Geer EB, Shen W. Gender differences in insulin resistance, body composition, and energy balance. Gend Med. 2009;6(Suppl 1):60–75. DOI: 10.1016/j.genm.2009.02.002
Soeters MR, Sauerwein HP, Groener JE, Aerts JM, Ackermans MT, Glatz JF, Fliers E, Serlie MJ. Gender-related differences in the metabolic response to fasting. J Clin Endocrinol Metab. 2007;92:3646–52. DOI: 10.1210/jc.2007-0552
Ter Horst KW, Gilijamse PW, de Weijer BA, Kilicarslan M, Ackermans MT, Nederveen AJ, Nieuwdorp M, Romijn JA, Serlie MJ. Sexual Dimorphism in hepatic, adipose tissue, and peripheral tissue insulin sensitivity in obese humans. Front Endocrinol. 2015;6:182.
Basu R, Dalla Man C, Campioni M, Basu A, Klee G, Toffolo G, Cobelli C, Rizza RA. Effects of age and sex on postprandial glucose metabolism: differences in glucose turnover, insulin secretion, insulin action, and hepatic insulin extraction. Diabetes. 2006;55:2001–14. DOI: 10.2337/db05-1692
Varlamov O, Bethea CL, Roberts CT Jr. Sex-specific differences in lipid and glucose metabolism. Front Endocrinol. 2014;5:241.
Pietropaoli AP, Glance LG, Oakes D, Fisher SG. Gender differences in mortality in patients with severe sepsis or septic shock. Gend Med. 2010;7:422–37. DOI: 10.1016/j.genm.2010.09.005
Valentin A, Jordan B, Lang T, Hiesmayr M, Metnitz PG. Gender-related differences in intensive care: a multiple-center cohort study of therapeutic interventions and outcome in critically ill patients. Crit Care Med. 2003;31:1901–7. DOI: 10.1097/01.CCM.0000069347.78151.50
Eachempati SR, Hydo L, Barie PS. Gender-based differences in outcome in patients with sepsis. Arch Surg. 1999;134:1342–7. DOI: 10.1001/archsurg.134.12.1342
Epstein SK, Vuong V. Lack of influence of gender on outcomes of mechanically ventilated medical ICU patients. Chest. 1999;116:732–9. DOI: 10.1378/chest.116.3.732
Reinikainen M, Niskanen M, Uusaro A, Ruokonen E. Impact of gender on treatment and outcome of ICU patients. Acta Anaesthesiol Scand. 2005;49:984–90. DOI: 10.1111/j.1399-6576.2005.00759.x
Schroder J, Kahlke V, Staubach KH, Zabel P, Stuber F. Gender differences in human sepsis. Arch Surg. 1998;133:1200–5. DOI: 10.1001/archsurg.133.11.1200
Lotz TF, Chase JG, McAuley KA, Shaw GM, Docherty PD, Berkeley JE, Williams SM, Hann CE, Mann JI. Design and clinical pilot testing of the model-based dynamic insulin sensitivity and secretion test (DISST). J Diabetes Sci Technol. 2010;4:1408–23. DOI: 10.1177/193229681000400616
Dickson JL, LeCompte AJ, Floyd RP, Chase JG, Lynn A, Shaw GM. Development and optimisation of stochastic targeted (STAR) glycaemic control for pre-term infants in neonatal intensive care. Biomed Signal Process Control. 2013;8:215–21. DOI: 10.1016/j.bspc.2012.08.002
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