MBD - Glucose/Hb1AC Report - HD PDF

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ASSIG ASSIGNMENT NMENT COVER SHEET Science Faculty SUBJECT NUMBER & NAME

91344 Medical and Diagnostic Biochemistry (Autumn 2020)

NAME OF STUDENT (PRINT CLEARLY - SURNAME, FIRST NAME)

STUDENT ID NUMBER STUDENT EMAIL

@student.uts.edu.au

STUDENT CON CONTACT TACT NUMBER NAME OF TUTOR

Dr Janet Lawandi

DUE DATE

By: 23:59hrs on Thursday 23 rd April 2020

ASSESSMENT ITEM NUMBER/TITLE

Glucose Report

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Version 1. April 2020

Date: 23 / 04 / 20

Investigation of the quality control to aid in the diagnosis of patients with Diabetes Mellitus Introduction Diabetes is a serious, long term health condition that will have an extensive implication on their lives and wellbeing of individuals, families, and societies worldwide. It is also known to be one of the top ten causes of death in adults, as cumulatively there is an estimated cause of four million deaths globally in 2017 (Saeedi et al., 2019). Due to its extensive global impact, there is an urge to find effective methods to detect, control and manage Diabetes Mellitus (DM). With the regular screening of DM, logical treatment decisions are able to intervene with increasing glycaemic levels (hyperglycaemia). Hyperglycaemia poses a critical threat due to the lack of insulin production, consequently decreasing glucose absorption (Jellinger, 2007). Thus, there is an increasing amount of glucose that can collectively damage vessels that supply blood to vital organs (Jellinger, 2007). Symptoms that are relative to hyperglycaemia include ketoacidosis, lactic acidosis, and hyperosmolar non-ketotic coma. Thus, it is important to stress the careful monitoring of diabetes mellitus and how it is able to affect the body.

As diabetes can be described holistically as suffering from hyperglycaemia, there are 3 main types of diabetes, Type 1 Diabetes Mellitus (T1DM), Type 2 Diabetes Mellitus (T2DM), and Gestational Diabetes Mellitus (GDM) that can be differentiated by their aetiology. T1DM is a chronic autoimmune disease where there is a loss of pancreatic islet  cells due to the infiltration of autoreactive T cells (Al-Tu'ma et al., 2019). Some symptoms associated with T1DM include polyuria, polydipsia, and polyphagia (AlTu'ma et al., 2019). In addition, T2DM is a progressive condition as due to the disruption of normal glucose homeostasis as it is able to impair  cell’s glucose responsiveness (Ikwuobe et al., 2016). Thus, the increased blood glucose levels is able to interact with excess fatty acids which are a feature of obesity (Ikwuobe et al., 2016). This interaction causes additional damage to cell function which eventually leads to full-blown diabetes. Another form of diabetes includes Gestational Diabetes Mellitus (GDM) which is characterised by glucose intolerance that emerges during pregnancy. Carbohydrate intolerance and abnormal fatty acid metabolism are linked to underlying disturbances (Qiu et al., 2014). Therefore, due to the lack of insulin secretion, there is an increased amount of glucose in cells. As a result, muscles, liver, and adipose tissues are unable to use glucose as a source of fuel.

Due to the high levels of glucose observed in diabetic patients, this will eventually lead to serious complications of an individual’s quality of life. This is inclusive of potentially life-threatening conditions that will affect organs. This is represented in the following as almost a quarter of diabetic patients suffer from chronic kidney disease, diabetic neuropathy, eye damage and foot problems (Trikkalinou et al., 2017). In addition, mental wellbeing should not be overshadowed as it is able to hinder an individual’s emotional and social capabilities (Trikkalinou et al., 2017). However, early detection of diabetes

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especially T2DM and GDM can be prevented utilising treatment regimens such as a balanced diet and being physically active (Trikkalinou et al., 2017). Collectively, without proper detection and monitoring of diabetes in a patient, it eventually leads to a decrease in quality of life due to bodily complications. Consequently, it is important to stress the idea of monitoring in order to control diabetes.

As monitoring glucose levels play a major role in determining whether the individual has diabetes, there are a variety of chemical and biochemical methods that aids in this detection. One-way glucose levels can be monitored is through the Glucose Oxidase / Peroxidase Aminophenazone (GOD/PAP) assay. This is achieved by glucose oxidising via GOD to gluconic acid and hydrogen peroxide with POD which reacts with chloro-4-phenol and PAP to form a red-violet quinonimine (Huggett & Nixon, 1957). The redviolet quinonimine colour change depicts the endpoint of the calibrator, as due to Beer’s Law, absorbance is proportional to the concentration. Furthermore, recently WHO recommended glycated haemoglobin (HbA1c) testing as an alternative diagnostic tool for the indication of glycaemic control (WHO. 2011). This antigen-antibody assay involves lysed red blood cells along with copies of the immunoreactive portion of HbA1c and specific monoclonal antibodies (Du et al., 2018). As a result, the agglutination of these two reactions is measured. With stringent quality controls performed prior for the assurance of accurate results, WHO recommends that a HbA1c of 6.5% as an end point for the diagnosis of diabetes (WHO. 2011). With the utilisation of quality controls alongside Westgard rules, we are able to differentiate between poor and precise conducted experiments (Huang et al., 2018). Poorly conducted experimental results that are out of 2 standard deviations are flagged and rejected as inaccurate results, hence another controlled run must be performed (Huang et al., 2018). Consequently, quality control is a major factor in determining the accuracy of the end results in order to diagnose a patient.

In this experimental design, we aim to investigate the principles of quality controls in both the GOD/PAP and HbA1c assays that aids in the determination of the diagnosis of two patients, NB and RM. GOD/ PAP method is able to measure the blood glucose levels as a short-term indicator. In conjunction, the HbA1c assay is indicative of glycaemic control. It is hypothesised that good experimental techniques have been utilised as quality controls are in system which results in an accurate diagnosis of patient NB and RM.

Materials and Methods Two patients (NB and RM) is utilised in this experimental study. Quality controls are to be completed, tabulated and plotted to form a Levey - Jennings Graph to indicate whether controls (C1, C2, C3) are satisfactory in accordance with Westgard laws. Analysis of glucose in blood/serum was performed utilising the Glucose Oxidase / Peroxidase Amino phenazone where a red-violet quinonimine is observed at a spectral peak of 505 nm. Analysis of blood glucose is also performed using glycated haemoglobin (Hb1Ac) as reported as a % to the total haemoglobin. Two separated assays are conducted; (i) HbA1c and (ii) total Haemoglobin with prior lysis of red blood cells. Stable ketoamine is

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measured by utilising a latex agglutination inhibition assay with an increase in absorbance at 700nm overtime. Total Hb assay is performed on lysed red blood cells with non-ionic detergent. There were no significant changes in methodology as the experiment was not conducted personally.

Results Table 1: A non-fasting, Patient NB test results whom is a healthy 35 year old who is suffering from weight loss and low urine volumes, but was consistently thirsty. Sample analysis

Result

Reference Range

Units

[Urea]

41

2.5-6.6

mmol/L

[Na2+]

142

132-144

mmol/L

[K+]

6.7

3.3-4.7

mmol/L

[Total CO2]

12.1

24-30

mmol/L

Glucose*

4.775

11.1 diabetic

mmol/L

%Hb A1c#

5.57%

4-6%, nondiabetics; 6-8%

%

controlled diabetics Urine volume (24 210

800-2000

ml

hr) *All analysis performed on patient plasma except *Glucose on serum and #HbA1c on whole EDTA blood

Patient NB portrayed significant signs of high concentrations of urea of 41 mmol/L and potassium with reference ranges of 2.5 – 6.6 mmol/L and 3.3-4.7 respectively. In the contrary, NB reported to have low urine volumes in which was evident in the test results of 210 mL, way under the range. NB also indicated to have low levels of carbon dioxide of 12.1mmol/L. Patient portrayed a normal blood glucose range of 4.775 mmol/L and a nondiabetic outcome of 5.57%.

Table 2: Patient RM, 30year old was found drowsy incorporative. It was notified that he has been taking large quantities of fluid and has a progressive weight loss with abdominal pain. Sample analysis

Result

Reference Range

Units

[Urea]

7.6

2.5-6.6

mmol/L

[Na2+]

128

132-144

mmol/L

[K+]

6.8

3.3-4.7

mmol/L

[Total CO2]

8.1

24-30

mmol/L

Glucose*

13.77

11.1 diabetic

mmol/L

%Hb A1c#

14.58%

4-6%, nondiabetics; 6-8%

%

controlled diabetics Urine volume (24 2500

800-2000

ml

hr) *All analysis performed on patient plasma except *Glucose on serum and #HbA1c on whole EDTA blood

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Patient RM indicated abnormally high levels of urea and potassium of 7.6 mmol/L and 6.8mmol/L respectively, which is outside the normal reference ranges. However, RM did see a decrease in sodium and carbon dioxide levels of 128mmol/L and 8.1 mmol/L respectively. It was logged that RM initial to testing, he had been taking large quantities of fluid which is observant in the high urine volume of 2500mL. A great indicator of diabetics can be mirrored through the blood glucose. Patient’s blood glucose is evidently higher than 11.1 and recorded 13.77mmol/L, hence RM is diabetic. In conjunction, his glycated haemoglobin percentage is abnormally high of 14.58% which is indicative of an uncontrolled diabetes regime.

Table 3: Quality Control for Blood Glucose testing where Control 2 (C2) signifies normal levels, whereas Control 3 (C3) is utilised for high levels. Test

mmol/L

CAL3 (= S1)

16.1

C2 MEAN

6.58

C2 ±2SD

0.99

C2 Range*

5.59 – 7.57

C3 MEAN

15.9

C3 ±2SD

2.4

C3 Range*

13.5 – 18.3

*Range is Control Mean ±2SD

Quality controls results depict that both controlled variables of C2 (6.83mmol/L) and C3 (17.28 mmol/L) lies in between the required 2 standard deviation range. Repetition of controls generated a standard deviation ranging from 0.99 mmol/L to 2.4 mmol/L which is in a reasonable small range.

Table 4: Validation for %HbA1c level assay where Control 1 (C1) depicts low levels and Control 2 depicts normal Control

Target (%)*

Range (%)*

HbA1c

T.Hb (g/dL)

%HbA1c

(g/dL) C1

5.95

4.76-7.14

0.77

12.74

6.04%

C2

12.5

10.0-15.0

1.48

11.05

13.39%

* Control Data provided with reagent information sheets

Quality control for total Hb performed with results portrays that both C1 (13.1 ± 2.6) and C2 (12.6 ± 2.5) ranges are within the 2-standard deviation of the calibrator level of 18.86 mmol/L. It is further observed that % C1 (6.04%) and C2 (13.99%) fall will within their respective control ranges of 4.76%-7.14% and 10.0%-15.0% respectively.

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Discussion In this following experiment, we conducted various different assays to determine the concentration of blood glucose and Haemoglobin Alc to monitor the glucose status and the glycaemic control of diabetes in a patient respectively. Collectively the data collated was run against quality controls for the assurance that results are in a reliable range in which we can reject the null hypothesis. In this instance, quality control values for blood glucose levels testing fell in-between the range of 6.58 ± 0.99 of Control 2 (C2) , 6.83 mmol/L and Control 3 (C3) of 17.28 mmol/L. [Table 3]. Thus, we are avidly able to accept the ongoing values as reliable as they have been repeated with the use of an accurate calibrator. C2 and C3 (excluding C1) were utilised in the experimental design to represent whether the measurement of blood glucose is in the normal range (C2) or a higher range (C3). However, C1 was neglected in the quality control run as it represents individuals who are severely hypoglycaemic. This is reflected upon the results of both patients results as NB portrayed a normal level of glucose of 4.775 mmol/L while RM is suffering from diabetes with a high level of glucose of 13.77 mmol/L [Table 1 and 2].

In addition, glycated haemoglobin was also utilised as a diabetes mellitus indicator for monitoring the glycaemic control of diabetes. This is depicted through the percentage of HbA1c (%HbA1c) where if a result lies between the reference range of 4 - 6%, it presents that a patient is currently not suffering from diabetes as evident with patient NB whom had a %HbA1c of 4.775% [Table 1]. In the contrary, Patient RM has an %HbA1c above 8% of 14.58% [Table 2] which is representative of an uncontrolled diabetes due to the low amounts of insulin stimulated in the blood (Mba et al., 2019). Quality controls were also performed alongside with the assays where %HbA1c to ensure that the results provided are sufficiently precise and accurate. This is observed in table 4 where Control 1 (C1) of 6.04% and C2 of 13.39% falls in between their respective range, hence we reject the null and accept as accurate results. Therefore, as controls were in their relative reference ranges, we are able to utilise the results and determine the %HbA1c as NB is a nondiabetic while RM indicated an uncontrolled diabetic patient outcome. As Quality controls (QC) are a great indication of whether the results gained are accurate, laboratories must demonstrate that a system has been implemented instead of a series of uncoordinated activities (Howanitz et al., 1997). This system is inclusive of (1) understanding the analytical error; (2) quality control materials; (3) a set of rules that specify action of the outcome where it becomes a deciding factor whether to the run is deemed as in control (Kazmierczak, 2003). However, if a control is deemed unacceptable, it is required to ensure that these defined procedures are returned to a normalised (acceptable) state (Kazmierczak, 2003). This is system is reflected upon this experimental design where there were no flagged controls, thus allowing the experiment to follow through and measure the necessary blood glucose levels and %HbA1c to determine the diagnosis of the patient. Another factor contributing to the precision of the acquired results is determined by the standard deviation. Table 3 portrays a minor standard deviation ranging from 0.99 mmol/L – 2.4 mmol/L which is indicative that technical techniques (e.g. pipetting) were completed meticulously throughout the replications that were

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performed. Consequently, as the above controls are deemed as satisfactory in the control range, results are proven to be accurate.

Although patient NB and RM can be diagnosed as normal and uncontrolled diabetic individuals respectively by both GOD/PAP and HbA1c assays, there are a few limitations with this conclusion. As Hb1Ac acts as an indicator for nondiabetics (4.0 – 5.6%), prediabetes (5.7% - 6.4%) and diabetic (>6.4%), it poses as a limitation for individuals who are suffering from haemoglobin disturbances. In order to accommodate for individuals suffering from haemoglobin malignancies such as anemia, C1 was inclusive in the HbA1c quality control. However, a study conducted by Sherwani et al indicated that some HbA1c levels are compromised as a false “good”, thus this will pose a disadvantage towards anaemic individuals as further testing such as family studies will be required (Sherwani et al., 2016). Another factor contributing towards abnormally high levels of %HbA1c is with the immoderate use of vitamin B, C and E supplements and high levels of cholesterol, liver and kidney disease (Sherwani et al., 2016). In addition, it should be noted that patient NB is currently suffering from kidney damages due to abnormally high amount of urea, low carbon dioxide and low urine [table 1]. Thus, further testing should be completed to ensure that kidney damages have unsuccessfully impacted the result and ongoing monitoring should be continued as a common risk factor for chronic kidney disease is inclusive of diabetes (Vassalotti et al., 2007). Without an in-depth knowledge of a patient’s medical background, we are unable to consider these factors before the test as seen in both patients’ NB and RM. Hence, the knowledge of a patient’s medical background plays a contributing factor in determining a diagnosis, thus further testing will be required.

Another possible blood glucose diagnostic tool is the Connecting-peptide (C-peptide) test. C-peptides are a substance that is produced in the pancreas with equimolar amounts to insulin and is widely used to measure pancreatic  cell function. In addition, it can act as a great insulin secretion marker in clinical practices to differentiate between T1DM and T2DM detect insulin deficiency and determine diabetes prognosis (Yin et al., 2017). Recently, C-peptide testing has proven to be a new preferable insulin guide to -cell function. This is due to its slower half-life than insulin which allows for a more stable testing window of a fluctuating -cell response (Szypowska et al., 2018). Also, the measurement of C-peptides avoids any dang...