Nur Jihan Mohd Zukhi
@usm.my
Advanced Medical and Dental Institute
Universiti Sains Malaysia
Scopus Publications
Scopus Publications
Farhah Muhammad, Fatanah M. Suhaimi, Zulfakar Mohd Mazlan, Ummu Kulthum Jamaludin, Normy Norfiza Abdul Razak, Syatirah Mat Zin, and Nur Jihan Mohd Zukhi
IEEE
One of the most common causes of death for hospitalized patients is sepsis. Acute kidney injury (AKI) brought on by sepsis is associated with worse outcomes. To avoid a worse prognosis, assessing and quickly identifying the function of the static kidney while determining AKI is essential. However, compared to analyzing vital signs that can be obtained at the bedside, urine output takes much longer to obtain. This investigation aims to: (i) identify the relationship between urine output and vital signs in determining SOFA between sepsis AKI and sepsis non-AKI; and (ii) assess the performance of predictive models of vital signs and urine output on both cohorts. This is a retrospective study on 30 sepsis AKI and 30 sepsis non-AKI patients admitted to the Intensive Care Units of Hospital U niversiti Sains Malaysia (HUSM). Data collected include age, gender, heart rate, respiratory rate, diastolic blood pressure, systolic blood pressure, mean arterial pressure, Glasgow Coma Scale, temperature, and urine output. The data included patients older than 18 years old and admitted to the ICU for more than 24 hours. Statistical analysis was performed using Matlab software. The results indicated that sepsis AKI and sepsis non-AKI were significantly different for urine output (p-value < 0.05). The performance of the multiple regression model on sepsis AKI using vital signs and urine output was better compared to the model with only vital signs as a predictor, with 3.53 on the root mean square error (RMSE) and 0.376 for the coefficient of determination (R2). However, the model of sepsis non-AKI presented similar performance for both sets of these predictors. Vital signs require slightly less time than vital signs with urine output to identify the Sequential Organ Failure Assessment (SOFA) and prevent delays in sepsis treatment, even though vital signs and urine output can improve the prognosis.
Jihan Zukhi, Fatanah M. Suhaimi, Mohd Zulfakar Mazlan, Farhah Muhammad, Mastura M. Sopian, Ummu K. Jamaludin, and Normy Razak
IEEE
Insulin infusion therapy implementing a sliding scale is mainly used in Malaysia's ICU to control blood glucose (BG) levels. However, the sliding scale is a one-size-fits-all protocol, which may cause hypoglycemia events when trying to control hyperglycemia among ICU patients. Hence, this study evaluates two newly developed protocols with potential variables of insulin sensitivity (SI), a fraction of inspired oxygen (FiO 2), and mean arterial pressure (MAP) to improve current insulin infusion therapy with personalized protocols and reduce the hypoglycemia event. Eighty-one diabetes mellitus patients who stayed in the ICU and received insulin infusion therapy were selected for this study. Two new protocols were developed, and the BG target was to be controlled within 8.0-10.0 mmol/L. Protocol A includes BG and SI, while Protocol B includes BG, SI, FiO2, and MAP. The outcomes from these protocols were compared with the performance of the clinical protocol. Protocol A resulted in 0.01 % of severe hypoglycemia events (BG < 2.2 mmol/L). Additionally, protocol A reduced severe hypoglycemia by 0.03% compared to the current protocol. Meanwhile, Protocol B had a similar percentage measurement of severe hypoglycemia events to the clinical protocol (0.04 %). Both protocols were able to control the blood glucose level within the target range with higher percentages of 28.45% and 28.22%, respectively, compared to the current clinical protocol (25.30%). Nevertheless, Protocol A and Protocol B had hyperglycemia events (BG > 10.0 mmol/L) slightly higher than clinical protocol, with percentage differences of 1.13% and 2.85%, respectively. This is because the insulin rate applied in both protocols was lower than the clinical protocol. The median insulin rate for Protocol A and Protocol B was the same, which was 1.2 U/hr, while the clinical protocol was 1.5 U/hr. The BG outcomes including median BG per-patient, percentage of severe hypoglycemia, hypoglycemia, hyperglycemia, and the BG within the target range, from Protocol A and Protocol B were not significantly different from the clinical protocol, with a p-value > 0.05. The potential variables introduced in the new protocols are able to reduce severe hypoglycemia events. However, they could not reduce the hyperglycemia events as both protocols provided lower insulin doses than the clinical protocol. Developing a personalized protocol is crucial, and more trials with large numbers of subjects are needed to properly design tight glycemic control for managing BG levels.
J. Zukhi, F. Suhaimi, Mohd Zulfakar Mazlan, Ummu K. Jamaludin, Normy N. Razak and Nizuwan Azman
Insulin infusion protocol based on the sliding scale is the standard protocol implemented in Malaysia's Intensive Care Unit (ICU) for controlling the patient's glycemic level. However, patients have a different dynamic and sensitivity toward insulin infusion, which needs close monitoring. The objective of this study is to compare the performance of two sliding scale-based glycemic control protocols (Protocols X and Y) on two different cohorts (cohorts A and B). Insulin sensitivity and patient variability of the patients were modelled using retrospective data, and an established glucose-insulin model. The sliding scale-based was further compared with a model-based glycemic control, Stochastic TARgeted (STAR) to investigate the patient variability and dynamic factors. The results obtained from this study showed that cohort A had more dynamics metabolism with lower mean of insulin sensitivity (50.0 L/mU.min) than cohort B. Protocol X had highest blood glucose (BG) measurements within their target range (6.0-10.0 mmol/L). However, there is no significant mean difference ($\\mathrm{p} > 0.05$) in BG level between Protocol X and Protocol Y. The median Acute Physiology and Chronic Health II (APACHE II) score showed the cohort A (26) had more severe patients than cohort B (20) that possibly not responding well towards the insulin therapy. The findings of this study show that the sliding scale-based results in a better BG level than the model-based. Nevertheless, patient variability and dynamics play an essential role in achieving a blood glucose target.
Fatanah M Suhaimi, Syatirah Mat Zin, Seniz Ertugrul, Mohd Zulfakar Mazlan, and Nur Jihan M Zukhi
IEEE
Type II diabetes mellitus (T2DM) is one of severe and common chronic disease, affecting almost all populations in many countries. T2DM and its complications constitute a major worldwide public health problem and associated with high rates of diabetes-related morbidity and mortality. In this study, a retrospective clinical data was collected from three patients receiving insulin therapy in the ICU of HUSM. The autoregressive moving average with exogenous (ARMAX) model structure techniques were used to generate a model converter that best describes the glucose and insulin relationship of the subject. Several combinations of model order were tested and simulated on the subjects. The best model fit criterion and the corresponding time-delay were identified. The estimated peak value was also compared to the real peak value. The finding shows that different patient can be represented with different model structure and different time-delay. However, there is a need to categorize the patients according to their appropriate model structure, particularly on the time-delay unit. Additional clinical parameter and a more extensive data set may be required to ensure the structure of the model precisely describe the glucose-insulin interaction of the patient.
Jihan Zukhi, Fatanah M. Suhaimi, Mohd Zulfakar Mazlan, Ummu K. Jamaludin, Normy Razak, and Mastura Mohd Sopian
Elsevier BV
Abstract Insulin infusion protocol is the standard protocol that has been practiced in Malaysia’s intensive care unit (ICU) for controlling the hyperglycemia. Multiple sliding scale method of the insulin infusion protocol may drive conflict in selecting an appropriate scale to be applied to the patient. The objective of this paper is to analyse the blood glucose outcome of eight sliding scales insulin infusion protocol adopted in the Universiti Sains Malaysia Hospital (HUSM). A retrospective data of 78 ICU patients of HUSM were fitted using a validated glucose-insulin system to identify insulin sensitivity profiles of the patients. Then, these SI profiles were simulated on various scale protocols. The results obtained from this study showed that among eight scales, Scale 4 had the highest percentage of BG within the HUSM’s target of 6.0–10.0 mmol/L. Scale 1 had the highest percentage of BG for the BG measurement more than 10.0 mmol/L while Scale 8 had the highest percentage of BG measurement of less than 6.0 mmol/L. However, none of the scale shown better performance than the current clinical practice. Furthermore, all of the eight scales had a more substantial number of BG measurement compared to the clinical. This study shows that Scale 2 and Scale 3 result in a similar outcome. Similarly, Scale 5 is almost the same as Scale 6. Thus, at least two sets of scale can be combined to reduce the number of scales. The reduction of scales consequently avoid confusion and helps the clinician in selecting the appropriate scale to be applied to the patients. From this study, it can be concluded that the HUSM protocol is a combination of scales. The scales may be shifted from one to another scale depending on patient condition and clinician judgement. A proper guideline for the scale shifting seems necessary to allow optimum glycemic management in the ICU.
J. Zukhi, D. Yusob, A. A. Tajuddin, and R. Zainon
Springer Singapore
D. Yusob, J. Zukhi, A. A. Tajuddin, and R. Zainon
Springer Singapore
Diana Yusob, Jihan Zukhi, Abd Aziz Tajuddin, and Rafidah Zainon
IOP Publishing
Noorfatin Aida B. Amin, J Zukhi, N. A. Kabir, and R. Zainon
IOP Publishing
J Zukhi, D Yusob, A A Tajuddin, L Vuanghao, and R Zainon
IOP Publishing
Norain Yusoff, Jihan Zukhi, Awatif Rusli, and Rafidah Zainon
IOP Publishing