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1.
Ugeskr Laeger ; 181(50)2019 Dec 09.
Artigo em Dinamarquês | MEDLINE | ID: mdl-31908262

RESUMO

In this case report, data are presented from a patient, who suffered from a severe subarachnoid haemorrhage and was admitted to the neuro-intensive care unit, where the use of cerebral microdialysis (CMD) allowed the detection of a severe mismatch between cerebral and systemic glucose levels and compromised cerebral metabolism despite systemic glucose values within the normal range. The established CMD monitoring allowed subsequent titration of insulin respecting acceptable cerebral and systemic glucose levels.


Assuntos
Hipoglicemia , Hemorragia Subaracnóidea , Glucose/líquido cefalorraquidiano , Humanos , Hipoglicemia/etiologia , Insulina , Unidades de Terapia Intensiva , Microdiálise , Hemorragia Subaracnóidea/complicações
2.
J Clin Monit Comput ; 26(4): 319-28, 2012 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-22581038

RESUMO

Assessment of glycemic control with model-based decision support ("Glucosafe") in neurotrauma intensive care patients in an ongoing randomized controlled trial with a blood glucose (BG) target of 5-8 mmol/L. Assessment of BG prediction accuracy of the model and assessment of the effect that two potential model extensions would have on prediction accuracy in this trial. In the intervention group insulin infusion rates and nutrition are varied based on Glucosafe's decision support. In the control group, the caloric target is 25-30 kcal/kg per day and insulin is regulated according to department rules. BG concentrations, insulin infusion rates, and feed rates are compared from the data of 12 consecutive patients. BG measurements are predicted retrospectively and the mean relative prediction error is calculated using (1) the current model from the trial, (2) the current model modified by using a BG-dependent variable endogenous insulin appearance rate, (3) the current model modified by a patient-specific carbohydrate absorption factor. BG control was improved by Glucosafe. 76 % of BG measurements in Glucosafe patients were in the 5-8 mmol/L band (Controls: 51 %). BG means (log-normal) ± SD were 7.0 ± 1.19 mmol/L in Glucosafe patients compared to 8.0 ± 1.24 mmol/L in controls (P = 0.05). Mean caloric intake was 93.5 ± 15 % of resting energy expenditure in Glucosafe patients (Controls: 129 ± 29 %). The BG-dependent variable insulin appearance rate had no measurable effect on prediction accuracy. The patient-specific carbohydrate absorption factor improved prediction accuracy significantly (P = 0.001). Glucosafe advice reduces hyperglycemia in neurotrauma intensive care patients. Further parameterization can improve model prediction accuracy.


Assuntos
Glicemia/metabolismo , Sistemas de Apoio a Decisões Clínicas , Quimioterapia Assistida por Computador/métodos , Ingestão de Alimentos , Hipoglicemia/tratamento farmacológico , Hipoglicemia/metabolismo , Insulina/administração & dosagem , Idoso , Simulação por Computador , Feminino , Humanos , Hipoglicemiantes/administração & dosagem , Masculino , Pessoa de Meia-Idade , Modelos Biológicos , Projetos Piloto , Sensibilidade e Especificidade , Resultado do Tratamento
3.
J Crit Care ; 25(1): 97-104, 2010 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-19926251

RESUMO

PURPOSE: "Glucosafe' is a new model-based decision support system for glycemic control in critical care. Safety and achievement of glycemic goals using the system are tested prospectively. METHODS: Four penalty functions were developed to balance regimens of nutrition and insulin therapy against model-predicted glycemic outcome. The system advises the regimen where the penalty sum is minimal. An interactive interface allows advice alterations. Ten hyperglycemic patients (median Acute Physiology and Chronic Health Evaluation II, 12.5; interquartile range, 7.5-16.3) from a neuro and trauma intensive care unit were included for pilot testing using Glucosafe for 12 to 14 hours. Glycemic outcomes were compared to the 24-hour intervals before and after intervention. RESULTS: Hypoglycemia (blood glucose [BG] <3.5 mmol/L) was not observed. Mean log-normal BG +/- standard deviation was reduced from 8.6 +/- 2.4 mmol/L preintervention to 7.0 +/- 1.1 mmol/L during the intervention. Nine patients reached the 4.4- to 6.1-mmol/L band after a mean 5 hours. At 5 hours intervention, mean log-normal BG was 6.7 mmol/L, 40% of measurements were in the 4.4- to 6.1-mmol/L band, and 84% were in the 4.4- to 7.75-mmol/L band. CONCLUSIONS: Safety was demonstrated with the developed penalty functions. The low BG variance achieved may permit minor adjustments of the penalty function values to reduce average BG if desired.


Assuntos
Cuidados Críticos/métodos , Sistemas de Apoio a Decisões Clínicas , Hipoglicemia/prevenção & controle , Adulto , Idoso , Idoso de 80 Anos ou mais , Glicemia/análise , Desenho de Equipamento , Segurança de Equipamentos , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Projetos Piloto , Estudos Prospectivos , Resultado do Tratamento , Interface Usuário-Computador
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