|Year : 2018 | Volume
| Issue : 3 | Page : 350-355
Thyroid dysfunction in patients with metabolic syndrome in medical ICU of Zagazig university hospitals
Osama A Khalil1, Mohamed Awad1, Fayrouz O Selim1, Ayman M.E.M Sadek1, Mohamed S Fawzy2
1 Internal Medicine Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
2 Medical Biochemistry Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
|Date of Submission||25-Feb-2018|
|Date of Acceptance||21-Mar-2018|
|Date of Web Publication||07-Jan-2019|
Dr. Ayman M.E.M Sadek
Shoubak Basta, Zagazig, Sharkia province, 44519
Source of Support: None, Conflict of Interest: None
Context Thyroid hormones are responsible for different metabolic processes. Hormonal imbalance is a suggested risk factor for metabolic syndrome (MS) development.
Aim We aimed to explore the frequency of undiagnosed thyroid dysfunction (TD) among patients with MS in medical ICU and its relation to each component of MS, morbidity, and mortality.
Settings and design We carried out a cross-sectional cohort study on patients who were admitted to medical ICU of Zagazig University Hospitals.
Patients and methods Of 941 medical ICU patients admitted over 6 months, 106 patients had MS. We measured thyroid stimulating hormone (TSH), free T3, and free T4 for those patients within 48 h of admission and acute physiology and chronic health evaluation II score calculation within 24 h of admission, and then we followed them up for short-term in-hospital mortality.
Results The frequency of TD in patients with MS was seen in 32 of 106 patients (90.6% of them were hypothyroid). We found an increased relative risk (RR) of 1.92-fold owing to the female sex. Logistic regression analysis revealed that obesity, hypertension, and hypercholesterolemia were the factors most associated with TD (P<0.001), with an increased RR by 1.25-, 1.45-, and 1.37-fold, respectively. Acute physiology and chronic health evaluation II score and mortality RR increased by 1.05 and 1.26-fold, respectively.
Conclusion MS in women may carry a high risk for TD, especially hypothyroidism, with poor medical ICU prognosis.
Keywords: ICU, metabolic syndrome, thyroid dysfunction
|How to cite this article:|
Khalil OA, Awad M, Selim FO, Sadek AM, Fawzy MS. Thyroid dysfunction in patients with metabolic syndrome in medical ICU of Zagazig university hospitals. Benha Med J 2018;35:350-5
|How to cite this URL:|
Khalil OA, Awad M, Selim FO, Sadek AM, Fawzy MS. Thyroid dysfunction in patients with metabolic syndrome in medical ICU of Zagazig university hospitals. Benha Med J [serial online] 2018 [cited 2019 Nov 23];35:350-5. Available from: http://www.bmfj.eg.net/text.asp?2018/35/3/350/249425
| Introduction|| |
Obesity, insulin resistance, sedentary life, advanced age, and hormonal imbalance are suggested underlying risk factors for metabolic syndrome (MS) .
Thyroid hormones fundamentally influence lipoprotein metabolism, consequently affecting general cardiovascular disease hazard .
Multiple studies have demonstrated a relationship between MS and hypothyroidism, especially in women .
However, limited studies explore the connection between thyroid dysfunction (TD) and components of MS. Therefore, we designed this study to explore the frequency of undiagnosed TD among patients with MS in medical ICU and its relation to each component of MS, morbidity, and mortality.
| Patients and methods|| |
We conducted a cross-sectional cohort study.
We carried out this work from the medical ICU of Internal Medicine Department in the period from January 2017 to June 2017.
We had selected 106 patients of 941 patients who were admitted to the medical ICU according to International Diabetes Federation criteria of MS 2006 .
The estimated sample size was 106 patients at 80% power and 95% confidence interval (Open Epi, Open Source Epidemiologic Statistics for Public Health, Version. www.OpenEpi.com).
We had managed this study according to the Declaration of Helsinki ethical principles, including a written informed consent from the patients if possible or from their guardian to participate in the study after taking Institutional Review Board Research Committee approval of the Zagazig Faculty of Medicine (Institutional Review Board Number).
We included adult subjects of both sexes with International Diabetes Federation criteria of MS as follows: central obesity, defined by waist circumference more than 102 cm in male and more than 88 cm in female individuals, and two of the following: triglycerides (TGs) more than 150 mg/dl, high density lipoprotein cholesterol (HDL-C) less than 40 mg/dl for men and less than 50 mg/dl for women, blood pressure more than 130/85 mmHg, and fasting plasma glucose more than 100 mg/dl.
We excluded patients who were pregnant, had malignancy, had immunodeficiency diseases, had septicemia, had preexisting thyroid disorder, were on corticosteroids therapy, took drugs that affect thyroid function (e.g. amiodarone and propranolol), or took any drugs for TD.
We had performed a full history taking and thorough clinical examination. We took anthropometric measures like waist circumference, waist–hip ratio, and BMI ,.
We did routine investigations like complete blood picture, liver chemistry, renal function tests, bleeding profile, lipid profile, fasting blood glucose level, arterial blood gases, ECG, abdominal ultrasound, and thyroid ultrasound.
We had calculated the severity assessment by acute physiology and chronic health evaluation (APACHE) II score within 24 h from admission .
We undertook serum level of free T4, free T3, and thyroid stimulating hormone (TSH) within 48 h after admission to avoid nonthyroidal illness, by using the enzyme-linked immunosorbent assay.
We used SPSS software version 17 (SPSS Inc., Chicago, Illinois, USA) . Data were expressed in the form of mean±SD, median, and range for continuous variables and number and percentage for categorical variables. We had tested continuous data for normality by using Shapiro–Wilk test. We found that the continuous data were normally distributed; therefore, we had interpreted the data by using independent Student t-test. We had compared percent of categorical variables by using the χ2-test. An α level less than 0.05 was considered statistically significant. Logistic regression model was generated to detect the most independent variables that affect the dependent ones. We calculated the relative risk (RR) of each component of MS on mortality.
| Results|| |
The age of the included participants ranged from 50 to 82 years (mean±SD of 65.7±6.0). There were 69 female and 37 male participants. Overall, 65 patients were hypertensive, 78 were hyperglycemic, and 33 were smokers.
Demographic, clinical, and laboratory data presented in [Table 1] showed a significant difference between patients with MS having TD and patients with euthyroid MS in age, sex, vital signs, anthropometric measures, fasting blood sugar, complete blood picture, creatinine, TGs, and APACHE II score.
|Table 1 Comparison of the mean±SD of various variables in patients with metabolic syndrome with and without thyroid dysfunction|
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Patterns of thyroid dysfunction
The frequency of different thyroid patterns was 30.19%, and hypothyroidism was the leading type of dysfunction (90.6%) ([Table 2]).
|Table 2 Frequency of patterns of thyroid dysfunction in patients with metabolic syndrome in medical ICU|
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Risk factors for thyroid dysfunction
The main risk factor for TD in patients with MS was age more than 60 years, female sex, smoking, BMI more than 30, and metabolic components of at least 4, with a RR of 1.23-, 1.92-, 1.51-, 1.16-, and 1.37-fold, respectively ([Table 3]).
|Table 3 Relative risk of age, sex, smoking, BMI, and number of components of metabolic syndrome on developing thyroid dysfunction in patients with metabolic syndrome|
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RR of MS components (BMI >30, hypertension, hypercholesterolemia, hypertriglyceridemia, and hyperglycemia) was 1.25-, 1.45-, 1.37-, 1.19-, and 0.72-fold, respectively ([Table 4]).
|Table 4 Relative risk of thyroid dysfunction on the development of each component of metabolic syndrome|
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Logistic regression for the effect of TD on MS risk factors revealed that obesity, hypertension, and hypercholesterolemia were the most affected (P<0.001) ([Table 5]).
|Table 5 Stepwise logistic regression analysis of thyroid dysfunction effect on components of metabolic syndrome|
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Outcome of thyroid dysfunction
TD had worsened morbidity and mortality in MS with a RR for APACHE II score above 14 of 1.05-fold and for short-term in-hospital mortality of 1.26-fold ([Table 6]).
|Table 6 Relative risk of thyroid dysfunction on morbidity (acute physiology and chronic health evaluation II score) and mortality in patients with metabolic syndrome patients|
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| Discussion|| |
WHO estimates a global increase of weight, with more than one billion overweight and 300 million obese adults. MS prevalence in 2008 in sub-Saharan Africa and Middle East countries reached 33.5% .
Many studies have analyzed the relationship between the MS and TD, but the results are ambiguous .
In this study, we looked for the frequency of undiagnosed TD in patients with MS who were admitted to medical ICU and identify its relation to some cardiovascular risk factors such as age, sex, smoking, BMI, and number of MS components. Moreover, the effect of undiagnosed TD on each component of MS, morbidity, and mortality was analyzed.
Our study showed a high frequency (30.19%) of undiagnosed TD in patients with MS, and this supported the results of Gyawali et al.  who reported similar prevalence in general population.
The present study showed that age older than 60 years increases the RR of developing TD in patients with MS, and this goes in line with the results reported by Singh et al. .
Regarding sex in this study, the RR of developing TD in patients with MS increased in female, which is in agreement with Uzunulu et al.  and Meng et al. . This is attributed to the higher iodine requirements in females; moreover, changes in reproductive hormones also cause changes in thyroid hormone levels. In addition, some females develop autoimmune antibodies to thyroid during pregnancy, which causes postpartum subacute thyroiditis and can increase the risk of developing permanent hypothyroidism .
We found that obesity increased the RR of TD in patients with MS than those with overweight, supporting the results of Biondi et al.  who reported a positive correlation between serum leptin and serum TSH levels in obese individuals, which could reflect the positive association between TSH and BMI.
The current study showed that smoking increased the risk of TD in patients with MS than nonsmokers, which is attributed to the increase in sympathetic activity in smokers, which may promote the development of thyrotoxicosis in predisposed individuals. Immunological disturbances caused by smoking are another possibility .
The current study showed that an increased number of the components of MS (four or more components) leads to an increased risk of TD than those with three components, which was attributed to the hypothesis that the axis involving the hypothalamus, pituitary, thyroid, and adipose tissue was somehow disrupted . Some studies suggesting that some humoral or hormonal mediators from adipose tissue stimulate the hypothalamus–pituitary–thyroid axis to increase TSH secretion. The main suspected mechanism is a possible relationship between leptin and the thyroid hormones. There is possibly a relationship between leptin and the thyroid hormones via an influence of leptin on the negative feedback regulation of thyroid hormones. Leptin regulates TRH expression .
Regarding hypertension in the present study, it was found that overt and subclinical TD increases the risk of hypertension than euthyroid patients with MS, and this was close to the results of Roos et al. .
We had observed that TD increases the risk of hypercholesterolemia and hypertriglyceridemia than euthyroid patients, with similar results obtained by Serter et al. . Although decreased thyroid function is accompanied by reduced activity of HMG-CoA reductase and TGs and low density lipoprotein cholesterol (LDL-C) levels are increased, this is owing to the decreased LDL-receptors’ activity, resulting in decreased catabolism of LDL . Moreover, a decrease in LPL activity limits the clearance of TG-rich lipoproteins .
We found that the most important risk factors affected by TD in MS were marked obesity, hypertension, and hypercholesterolemia in patients admitted to medical ICU.
The current study showed that TD worsens APACHE II score than euthyroid patients with MS, thus TD worsens functional outcome in patients with MS. Similar result was obtained by Wang et al. , who explain this association by reduced adrenergic tone and hypometabolic state.
Finally, the present study showed that thyroid disorders increase the mortality of patients with MS than euthyroid. Similar results were obtained by Wang et al. , who reported that inhibition of the enzyme 5′-deiodinase, which catalyses the conversion of T4–T3, has been considered a possible mechanism responsible for increased mortality of patients with MS. Several mechanisms can contribute to the inhibition of 5’-monodeiodination and to the low serum T3 concentrations in critically ill patients: cytokines such as tumor necrosis factor (TNF), interferon alpha (IFN-α), nuclear factor kappa B (NF-κB), and interleukin 6 (IL-6), and free (nonesterified) fatty acids .
| Conclusion|| |
Undiagnosed TD in patients with MS is common mainly in female patients, metabolic components of at least 4, age more than 60 years old, and smoking. It was affected by obesity, hypertension, and hypercholesterolemia more than other MS components, with worsened functional outcome and mortality. Early detection and management of TD may improve short-term, with subsequent long-term, prognosis.
This study was supported by Faculty of Medicine, Zagazig University, Zagazig, Egypt.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Grundy SM. Metabolic syndrome scientific statement by the American Heart Association and the National Heart, Lung, and Blood Institute. Arterioscler Thromb Vasc Biol 2005; 25:2243–2244.
Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA et al.
Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005; 112:2735–2752.
Uzunlulu M, Yorulmaz E, Oguz A. Prevalence of subclinical hypothyroidism in patients with metabolic syndrome. Endocr J 2007; 54:71–76.
Graham IM. Guidelines on cardiovascular disease prevention in clinical practice: the European perspective. Curr Opin Cardiol 2005; 20:430–439.
van der Kooy K, Leenen R, Seidell JC, Deurenberg P, Droop A, Bakker CJ. Waist–hip ratio is a poor predictor of changes in visceral fat. Am J Clin Nutr 1993; 57:327–333.
Mei Z, Grummer-Strawn LM, Pietrobelli A, Goulding A, Goran MI, Dietz WH. Validity of body mass index compared with other body-composition screening indexes for the assessment of body fatness in children and adolescents. Am J Clin Nutr 2002; 75:978–985.
Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med 1985; 13:818–829.
Levesque R. SPSS Programming and Data Management. In: A Guide for SPSS and SAS Users. Fourth Edition 2010. SPSS Inc., Chicago, Illionis.
Misra A, Khurana L. Obesity and the metabolic syndrome in developing countries. J Clin Endocrinol Metab 2008; 93:S9–S30.
Park SB, Choi HC, Joo NS. Th relation of thyroid function to components of the metabolic syndrome in Korean men and women. J Korean Med Sci 2011; 26:540–545.
Gyawali P, Takanche JS, Shrestha RK, Bhattarai P, Khanal K, Risal P et al.
Pattern of thyroid dysfunction in patients with metabolic syndrome and its relationship with components of metabolic syndrome. Diabetes Metab J 2015; 39:66–73.
Singh BM, Goswami B, Mallika V. Association between insulin resistance and hypothyroidism in females attending a tertiary care hospital. Indian J Clin Biochem 2010; 25:141–145.
Meng Z, Liu M, Zhang Q, Liu L, Song K, Tan J et al.
Gender and age impacts on the association between thyroid function and metabolic syndrome in Chinese. Medicine (Baltimore) 2015; 94:e2193.
Knudsen N, Laurberg P, Rasmussen LB, Bülow I, Perrild H, Ovesen L et al.
Small differences in thyroid function may be important for body mass index and the occurrence of obesity in the population. J Clin Endocrinol Metab 2005; 90:4019–4024.
Biondi B. Thyroid and obesity: an intriguing relationship. J Clin Endocrinol Metab 2010; 95:3614–3617.
Caturegli P, De Remigis A, Ferlito M, Landek-Salgado MA, Iwama S, Tzou SC et al.
Anatabine ameliorates experi-mental autoimmune thyroiditis. Endocrinology 2012; 153:4580–4587.
Schäffler A, Binart N, Schölmerich J, Büchler C. Hypothesis paper brain talks with fat − evidence for a hypothalamic-pituitary-adipose axis? Neuropeptides 2005; 39:363–367.
Sari R, Balci MK, Altunbas H, Karayalcin U. The effect of body weight and weight loss on thyroid volume and function in obese women. Clin Endocrinol (Oxf) 2003; 59:258–262.
Roos A, Bakker SJ, Links TP, Gans RO, Wolffenbuttel BH. Thyroid function is associated with components of the metabolic syndrome in euthyroid subjects. J Clin Endocrinol Metab 2007; 92:491–496.
Serter R, Demirbas B, Korukluoglu B, Culha C, Cakal E, Aral Y. The effect of l-thyroxine replacement therapy on lipid based cardiovascular risk in subclinical hypothyroidism. J Endocrinol Invest 2004; 27:897–903.
Abrams JJ, Grundy SM. Cholesterol metabolism in hypothyroidism and hyperthyroidism in man. J Lipid Res 1981; 22:323–338.
Nikkilä EA, Kekki M. Plasma triglyceride metabolism in thyroid disease. J Clin Invest 1972; 51:2103–2114.
Wang F, Pan W, Wang H, Wang S, Pan S, Ge J. Relationship between thyroid function and ICU mortality: a prospective observation study. Crit Care 2012; 16:R11.
Economidou F, Douka E, Tzanela M, Nanas S, Kotanidou A. Thyroid function during critical illness.Hormones (Athens) 2011; 10:117–124.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]