Vol 13, No 1 (2024)
Research paper
Published online: 2024-02-06

open access

Page views 526
Article views/downloads 247
Get Citation

Connect on Social Media

Connect on Social Media

RESEARCH PAPER

Type 2 Diabetes at a Military Health Centre in Brazil: Clinical and Pharmacotherapeutic Profile

André Henrique Freitas de Braga e Bessa1Julieta Ueta1Vinícius Diniz Mayrink2Rinaldo Eduardo Machado de Oliveira13
1Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
2Federal University of Minas Gerais, Minas Gerais, Brazil
3University of Brasília, Brasília, DF, Brazil

Address for correspondence:

Rinaldo Eduardo Machado de Oliveira

University of Brasília, University Campus, Metropolitan Center, Brasília, DF, 72220-275, Brazil, phone: +55 61 3107-8442

e-mail: rinaldo.eduardo@unb.br

Clinical Diabetology 2024, 13; 1: 60–66

DOI: 10.5603/cd.98362

Received: 29.11.2023 Accepted: 28.12.2023

Early publication date: 6.02.2024

This article is available in open access under Creative Common Attribution-Non-Commercial-No Derivatives 4.0 International (CC BY-NC-ND 4.0) license, allowing to download articles and share them with others as long as they credit the authors and the publisher, but without permission to change them in any way or use them commercially.

ABSTRACT

Objective: To analyze the clinical and pharmacotherapeutic profile of people with type 2 diabetes (T2D) at a military health center in Brazil.

Materials and methods: This is a cross-sectional study. The sample of 170 medical records was selected by means of probabilistic sampling. The data collected were sociodemographic, clinical and laboratory data related to diabetes, as well as prescribed medications.

Results: Most of the subjects were male (57.6%), elderly (64.7%) and inactive military (55.2%). Adequate glycemic control was observed in 75.9% of the subjects, which was positively associated with multimorbidity and mono-therapeutic treatment (p < 0.05). Negative associations were observed in those subjects attending medical appointments less frequently and using prescribed insulin (p < 0.05). Medications prescribed for treatment of T2D were the following: metformin (90.6%), sulfonylureas (22.9%), dipeptidyl peptidase inhibitors-4 (16.5%) and sodium-glucose 2 co-transporter inhibitors (10.0%), in which 50.6% were monotherapy. Multimorbidity was 97.6%, in which systemic arterial hypertension (71.8%), lipid disorders (65.9%) and cardiovascular diseases (26.5%) were the main clinical conditions.

Conclusions: The frequency of inadequate glycemic control among subjects using prescribed insulin shows the importance of monitoring this population by means of insulin dosage adjustment, stimuli for pharmacological measures, including education on diabetes. (Clin Diabetol 2024; 13, 1: 60–66)

Keywords: diabetes mellitus, military health, chronic disease, multimorbidity, drug utilization

Introduction

Diabetes mellitus (DM) constitutes a public health problem. It is estimated that the worldwide prevalence of DM is around 10.5%, with a trend towards an increase in the coming decade. Brazil is currently ranked sixth in the world regarding the number of people with diabetes aged 20–79 years old, with this population being estimated at 15.7 million people. The disease has an impact on direct health costs, which increased from 232 billion dollar in 2007 to 966 billion dollar in 2021 worldwide [1].

DM has obesity, physical inactivity and inadequate nutrition as the main risk factors leading to metabolic syndrome (MS), which has been observed even in more controlled occupational settings, such as the armed forces, where the prevalence of DM is around 17.6% among the military personnel [2, 3], what indicates the need for surveillance and attention concerning DM risk factors.

The health status of the Brazilian military personnel, particularly, lacks information. In this way, studies on this theme are necessary for supporting the health service planning in military corporations. In this context, the present study aims to analyze the clinical and pharmacotherapeutic profile of people with type 2 diabetes (T2D) at a military healthcare center in Brazil, to contribute to the enhance of knowledge on health military personnel in this health unit allowing, in the future, necessary interventions, in the health service to improve it.

Methods

This is a cross-sectional descriptive survey study using medical records from a military healthcare center located in the State of São Paulo, Brazil. The study included male and female individuals diagnosed with T2D, aged 30 years or older, using medications prescribed for diabetes and attending at least one medical appointment in 2019. Pregnant women were excluded.

The search for subjects was performed from a list of individuals who underwent glycated hemoglobin test (HbA1c) at the local clinical analysis laboratory in 2019 by randomly selecting those who met the eligibility criteria. The minimum sample size was calculated as 168 subjects, considering 80-percent rate of people with diabetes using medications [4], acceptable absolute error of 5% and confidence coefficient of 95%.

The following data were collected: age, color/race, schooling level, gender, and recipient’s status (social-economic); number of outpatient appointments and rate of emergency care in the year of 2019 (use of healthcare services); and glycated hemoglobin, fasting plasma glucose, systemic arterial hypertension, levels of non-HDL cholesterol, LDL cholesterol, triglycerides and serum creatinine, and identification of the most frequent conditions (clinical and laboratory diseases). It was considered specifically LDL cholesterol less than 50 mg/dL as a category, in accordance with the Brazilian Diabetes Society guidelines, aiming this target to the very high-risk patients with T2D. The parameters outpatient appointments and access to emergency care were stratified into the following groups: 1–4 times, 5–8 times and more than 9 times to reduce considerable variations of the data collected.

Multimorbidity was defined as the presence of two or more conditions in the same individual [5], with these conditions being classified into concordant (related to a similar pathophysiology with T2D) and discordant (not related to a similar pathophysiology with T2D) in relation to T2D [6, 7]. The prescribed medications were classified according to the Anatomical Therapeutic Chemical (ATC) classification system set by the World Health Organization. Polypharmacy was defined as being the concomitant use of five or more medications [8].

The result data were analyzed by means of descriptive statistics with distribution of absolute and relative frequencies. Odds ratio and 95% confidence interval (95% CI) were calculated by using conditional method [9]. In the present study, the use of regression adjustment is related to the Poisson model for binary response in the analysis of the effect of each independent variable on the presence of glycemic control. The adjusted analysis was initially used to investigate the effect of each independent variable in a regression, including all variables selected from the data set, before being performed in two steps: (i) regression adjustment with two independent variables (bivariate model) and (ii) greater model adjustment containing an independent variable and those identified as statistically significant (p < 0.05) in the bivariate modelling [10].

Ethical considerations

The present study was approved by the ethics research committee of the São Paulo Armed Force Hospital according to the protocol number 37488620.7.0000.8928.

Results

The resulting sample had 170 subjects whose characteristics are listed in Table 1. The majority were male, the average age was 63.3 years [standard deviation (SD) = 8.9], 27.1% had completed secondary school and 38.2% were dependent, that is, partners, parents and/or children of the military who are also users of the health system.

Table 1. Social-Demographic Characteristics of the Study Sample (n = 170) (Air Force Health Centre, Pirassununga, SP, Brazil, 2019)

Variable

Result

Gender

Male (n, %)

98 (57.6%)

Female (n, %)

72 (42.4%)

Mean age ± standard deviation [years]

63.3 ± 8.9

Color/race

White (n, %)

131 (77.1%)

Non-white (n, %)

39 (22.9%)

Schooling level

Complete elementary school (n, %)

19 (11.2%)

Complete secondary school (n, %)

46 (27.1%)

Complete higher school (n, %)

26 (15.3%)

Not informed (n, %)

79 (46.5%)

Recipient’s status

Active (n, %)

6 (3.5%)

Reserve1 (n, %)

64 (37.6%)

Retired2 (n, %)

30 (17.6%)

Dependent3 (n, %)

65 (38.2%)

Pensioner4 (n, %)

5 (2.9%)

About the use of healthcare services, the rate of outpatient appointments was stratified into the following groups: 1–4 times, 5–8 times and more than 9 times, for which the prevalence found were 41.2%, 28.2% and 30.0%, respectively. On average, each subject had 6.5 appointments (SD = 4.5).

The access to emergency care was also stratified into the same groups of 1–4 times, 5–8 times and more than 9 times for which the prevalence found were 60.0%, 10.6% and 6.5%, respectively. The mean rate was 2.8 times (SD = 3.4). Emergency care was not used by 22.9% of the subjects.

Table 2 shows the results of the clinical and laboratory tests of the study subjects.

Table 2. Clinical and Laboratory Results of the Study subjects (n = 170) (Air Force Health Centre, Pirassununga, SP, Brazil, 2019)

Variable

n

Mean ± standard deviation

Glycated hemoglobin [%]

170

6.5 ± 1.0

Fasting plasma glucose [mg/dL]1

166

129.6 ± 48.5

Systolic arterial hypertension [mmHg]2

107

126.0 ± 15.6

Diastolic arterial hypertension [mmHg]3

107

80.4 ± 9.2

Non-HDL cholesterol [mg/dL]4

158

182.4 ± 47.8

LDL cholesterol [mg/dL]5

154

101.3 ± 40.1

Triglycerides [mg/dL]6

158

175.7 ± 118.8

Men’s serum creatinine [mg/dL]7

86

1.09 ± 0.7

Women’s serum creatinine [mg/dL]8

66

0.9 ± 0.2

The presence of multimorbidity was observed in 97.6% of the subjects, with the majority (57.6%) having from 2 to 4 conditions. The conditions occurring most simultaneously with T2D were systemic arterial hypertension (71.8%), lipid disorders (65.9%) and cardiovascular diseases (26.5%). As for the classification of the subjects in relation to concordant, discordant, and concordant/discordant conditions, the prevalence was 31.3%, 3.6% and 65.1%, respectively.

Among the subjects with adequate glycemic control, the highest rate (70.3%) was found in the category of subjects with both concordant and discordant conditions. This rate was followed by that of the categories of subjects with concordant diseases only (25.8%) and of those with discordant diseases only (3.9%).

As for the subjects who had inadequate glycemic control, it was found that 50.0% belonged to the concordant category, 47.4% to the concordant/discordant category and 2.6% to the discordant category.

As for prescribed medications, it was found that 5.7 drugs were prescribed per subject. In addition, 39.4% of the subjects were prescribed 1 to 4 drugs, whereas 60.6% were prescribed more than 5 drugs. The pharmacotherapy used for treatment of T2D is shown in Table 3.

Table 3. Pharmacotherapy Used for Treatment of Type 2 Diabetes in the Study Sample (n = 170). (Air Force Health Centre, Pirassununga, SP, Brazil, 2019)

Category

Result

Metformin (n,%)

86 (50.6%)

Metformin and other oral anti-diabetic drugs (n, %)

46 (27.1)

Insulin and oral anti-diabetic drugs (n, %)

22 (12.9%)

Insulin only (n, %)

5 (2.9%)

Sulfonylureas only (n, %)

4 (2.4%)

Other classes and combinations (n, %)

7 (4.1%)

Metformin was the main medication prescribed in the monotherapy treatment, corresponding to 90.5% of this group of drugs (metformin, insulin, or sulfonylureas). In addition, it was observed that in the category “metformin and other oral anti-diabetic drugs”, the most frequent association was that of metformin and sulfonylureas, with 9.4% in relation to the total of subjects.

Metformin was also used in dual therapy in combination with sodium-glucose 2 co-transporter inhibitors (SGLT2i) (dapagliflozin or empagliflozin), dipeptidyl peptidase inhibitors-4 (DPP-4) (sitagliptin, vildagliptin, alogliptin) or tiazolidinediones (pioglitazone), corresponding to 17.6% of the sample. In this category, it was also found that 10% of the subjects used triple and quadruple therapy using oral anti-diabetic drugs in several combinations with metformin, sulfonylureas, SGLT2i, DPP-4 inhibitors and tiazolidinedione.

In the category “insulin and oral anti-diabetic drugs”, the most frequent combination was that in which 7.6% of the sample used insulin and metformin, whereas other combinations involving insulin, metformin, and other oral anti-diabetic drugs such as sulfonylureas (glibenclamide or gliclazide), DPP-4 inhibitors (vildagliptin) and SGLT2i (dapagliflozin or empagliflozin) corresponded to 5.3% of the subjects. In the category “other classes and combinations”, DPP-4 inhibitors (vildagliptin, linagliptin and, sitagliptin) and SGLT2i (empagliflozin) were also prescribed.

Among the classes of medications prescribed for other conditions rather than T2D, one can highlight the angiotensin receptor antagonists (44.8%), diuretics (44.1%), angiotensin-converting enzyme inhibitors (18.3%) and calcium channel blockers (15.3%).

Table 4 shows the results of association tests performed between dependent (glycemic control control) and independent variables (gender, age, color/race, recipient’s status, medical appointments, emergency care, multimorbidity, number of diseases, systemic arterial hypertension, dyslipidemia, overweight/obesity, hypothyroidism, psychiatric disorders, polypharmacy, medications for T2D and monotherapy for T2D).

Table 4. Glycemic Control (Glycated Hemoglobin Less than 7.0%) of the Subjects According to Social-Demographic and Clinical Variables (n = 170) (Air Force Health Centre, Pirassununga, SP, Brazil, 2019)

Variable

Adjusted analysis1

PR (95% CI)

p-value

Gender

Female

Male

0.95 (0.81–1.13)

0.62

Age group [years]

30–49

50–59

0.85 (0.47–1.53)

0.55

60–69

0.82 (0.46–1.44)

0.45

70–79

0.93 (0.54–1.59)

0.78

Color/race

Non-white

White

1.11 (0.89–1.39)

0.28

Recipient’s status

Inactive

Active

1.13 (0.89–1.44)

0.49

Medical appointments (2019)

1–4

0.66 (0.48–0.91)

< 0.05

5–8

0.85 (0.61–1.18)

0.29

≥ 9

Emergency care (2019)

0

0.79 (0.44–1.45)

0.37

1–4

0.91 (0.63–1.32)

0.65

5–8

0.96 (0.58–1.60)

0.88

≥ 9

Multimorbidity [5]

No

Yes

3.98 (0.63–24.90)

<0.05

Number of diseases

1–3

4–5

1.18 (0.98–1.42)

0.06

≥ 6

1.19 (1.05–1.34)

<0.05

Systemic arterial hypertension

No

Yes

1.11 (0.89–1.39)

0.30

Dyslipidemia

No

Yes

1.05 (0.86–1.27)

0.60

Overweight/obesity

No

Yes

1.12 (0.92–1.35)

0.31

Hypothyroidism

No

Yes

1.22 (1.06–1.41)

0.06

Psychiatric disorders

No

Yes

1.18 (1.01–1.39)

0.14

Polypharmacy [8]

No

Yes

0.94 (0.79–1.11)

0.49

Medications for T2D

Oral anti-diabetic drugs

Oral anti-diabetic drugs
and insulin

0.23 (0.09–0.55)

< 0.05

Insulin only

0.31 (0.07–1.32)

< 0.05

Monotherapy for T2D

No

Yes

1.34 (1.09–1.65)

< 0.05

Discussion

Although the proportion of men in the population is 48.2% [11], in the present study it was observed that most of the subjects were male (57.6%), possibly due to the high rate of men serving in the Air Force (81.0%) [12]. The users of the healthcare center were military personnel who were active, inactive (retired/reserve), dependent and pensioners. However, it was found that the great majority of the subjects were inactive military personnel and their dependents, which can be partially explained by their older age compared to active ones [13]. It’s necessary to highlight that inactive militaries have already completed their career in the military organization. Therefore, they are older compared to the active militaries who are still developing their career.

A systematic review study with meta-analysis of the prevalence of MS among personnel of the armed forces and military corporations of several countries found a proportion of 8.3% [14]. Another study of the Brazilian Navy personnel detected a prevalence of 17.6% for MS [2], whereas a cross-sectional study of the Brazilian general population estimated a prevalence of 38.4% [15]. Therefore, military personnel are less likely to develop T2D compared to the general population since the former are required to practice physical activities regularly.

About the utilization of healthcare services, it was observed that there was a relationship between inadequate glycemic control and low rate of medical visits, thus indicating that individuals with chronic conditions (e.g., T2D) can benefit from the care provided by the health team as they need a minimum number of accesses to healthcare services. In fact, there is evidence that the care provided by a multiprofessional team for management of T2D favors the outcome of the patient. The inclusion of a pharmacist in the team should also be emphasized as such a professional can contribute to achieving the glycemic goals of these people with diabetes [16, 17]. In the present study, the reference value of HbA1c for an adequate glycemic control was below 7.0% [18, 19]. Therefore, 75.9% of the subjects in our sample had an adequate glycemic control, which is corroborated by another study reporting a rate of 62.0% among individuals living in the south-eastern region of the country [20].

About systemic arterial hypertension, it was observed that this condition was highly prevalent in the population studied, reaching 25.9% in the south-eastern region [21]. This finding points to the opportunity of improving the treatment of the disease on a continuous basis.

As for the lipid profile, the parameters analyzed were found to be adequate only for approximately half of the sample, thus making this finding an important point of attention for patients with T2D. Regarding renal function markers in patients with T2D, it is known that the measurement of serum creatinine level is a very used parameter in the initial examination, although more parameters are required to obtain a precise diagnosis [22].

As for multimorbidity, other authors also reported a simultaneous prevalence of T2D and other conditions such as systemic arterial hypertension, lipid disorders and cardiovascular diseases [23, 24], which is in accordance with the present study.

It should be emphasized that the subjects of the present study had an average of 3.3 diseases, a figure close to that reported in the literature (i.e., 3.1 diseases per individual) [25]. This demonstrates the association between T2D and multimorbidity and reinforces the discussion on providing multi-professional care for these individuals on an integral basis through qualified healthcare providers [5]. As well as other studies [25, 26], a relationship between multimorbidity and adequate glycemic control was also found here. One can conclude that a higher number of medical appointments is related to a better provision of care for individuals so that they can control their T2D adequately.

Another important aspect in the analysis of multimorbidity was the stratification of subjects into those who had concordant, concordant-discordant, and discordant diseases. Our results were like those of another study using real-life data from primary health care [6], showing that many individuals with adequate glycemic control were those with concordant and discordant conditions. Nevertheless, another issue raised in the present study is that the hypertension rates as well as the lipid parameters, in general, were not adequate for most of the sample studied, differently from what occurs with HbA1c. Therefore, a strategic planning should be proposed to implement health actions aimed at the integrity of care.

Metformin was the mostly widely prescribed medication in the monotherapy for T2D. The prescription rate of metformin is coherent with the medical recommendations as the first line pharmacotherapeutic schemes for treatment of T2D due to its efficacy, good security profile, cardiovascular protection, reduced rate of hypoglycemia and weight gain neutrality, besides being easily available and free of charge from the Brazilian public health system [18, 27].

The current pharmacotherapeutic recommendations have been guiding the treatment with the aim to reduce the glycemia as well as to prevent cardiovascular and renal damage, regardless of the levels of HbA1c, since individuals with T2D are more likely to develop cardiovascular diseases and renal harm compared to those not affected by this condition. This is why one of the principles for combining other oral anti-diabetic drugs lies in their cardiovascular and renal protective effects [18, 27]. The prescribed combination of insulin and oral anti-diabetic drugs is justifiably aimed at minimizing adverse events of the treatment with insulin, that is, hypoglycemia and weight gain. The concomitant use of insulin with metformin can lead to an adequate glycemic control and result in less hypoglycemic events and less weight gain compared to treatment with insulin only [28].

Polypharmacy is frequent in a scenario of multimorbidity, which can have negative consequences as it is associated with all causes of mortality, including acute myocardial infarction [29]. Therefore, it is important to review the prescribed medications periodically based on the best evident available in the literature.

About limitations, it was not possible to determine the causality between the variables analyzed because this is a cross-sectional study. Furthermore, this is a single-center study performed in a military environment, thus the findings observed may be limited to other health units based in Brazil or in other countries. Another limitation is the quality of the information, as a high number of medical records lacked data on anthropometric measurements such as height, weight, and abdominal circumference. Moreover, failures in the recording of blood pressure as well as in the laboratory results were noted.

The present study has shown the clinical and pharmacotherapeutic profile of the people attending a military healthcare center, with most of the subjects having an adequate glycemic control and metformin being the most prescribed medication for control of T2D. However, the glycemic control was found to be inadequate for those subjects who used insulin. In addition, high rates of multimorbidity and polypharmacy were also observed.

Article information

Data availability statement

Data from this study can be requested from the corresponding author.

Author contributions

The authors approved the final version of the article after contributing to the conception and planning of the study, data analysis and interpretation, and writing of the manuscript.

Funding

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior — Brazil (CAPES) — Finance Code 001.

Conflict of interest

The authors declare no conflict of interest.

References

  1. International Diabetes Federation. Global Picture. International Diabetes Federation Atlas [Internet]. 2021; 10th: 30-63. https://diabetesatlas.org/ (٢٨.١١.٢٠٢٣).
  2. Costa FF, Montenegro VB, Lopes TJ, et al. Combination of risk factors for metabolic syndrome in the military personnel of the Brazilian Navy. Arq Bras Cardiol. 2011; 97(6): 485492, doi: 10.1590/s0066-782x2011005000113, indexed in Pubmed: 22030564.
  3. Fortes Md, Rosa SE, Coutinho W, et al. Epidemiological study of metabolic syndrome in Brazilian soldiers. Arch Endocrinol Metab. 2019; 63(4): 345350, doi: 10.20945/2359-3997000000115, indexed in Pubmed: 30916165.
  4. Tavares N, Costa K, Mengue S, et al. Uso de medicamentos para tratamento de doenças crônicas não transmissíveis no Brasil: resultados da Pesquisa Nacional de Saúde, 2013. Epidemiologia e Serviços de Saúde. 2015; 24(2): 315323, doi: 10.5123/s1679-49742015000200014.
  5. Forman DE, Maurer MS, Boyd C, et al. Multimorbidity in Older Adults With Cardiovascular Disease. J Am Coll Cardiol. 2018; 71(19): 21492161, doi: 10.1016/j.jacc.2018.03.022, indexed in Pubmed: 29747836.
  6. Heikkala E, Mikkola I, Jokelainen J, et al. Multimorbidity and achievement of treatment goals among patients with type 2 diabetes: a primary care, real-world study. BMC Health Serv Res. 2021; 21(1): 964, doi: 10.1186/s12913-021-06989-x, indexed in Pubmed: 34521389.
  7. Piette JD, Kerr EA. The impact of comorbid chronic conditions on diabetes care. Diabetes Care. 2006; 29(3): 725731, doi: 10.2337/diacare.29.03.06.dc05-2078, indexed in Pubmed: 16505540.
  8. World Health Organization. Medication safety in polypharmacy [Internet]. 2019; Geneva, Switzerland: WHO Library Caraloguing-in-Publication Data. https://www.who.int/publications/i/item/WHO-UHC-SDS-2019.11 (٢٨.١١.٢٠٢٣).
  9. Wilcosky TC, Chambless LE. A comparison of direct adjustment and regression adjustment of epidemiologic measures. J Chronic Dis. 1985; 38(10): 849856, doi: 10.1016/0021-9681(85)90109-2, indexed in Pubmed: 4044770.
  10. Casella G, Berger RL. Statistical Inference, 2nd edition. Boston: Cengage Learning, Boston 2002.
  11. Instituto Brasileiro de Geografia e Estatística. Estimativa da população por gênero [Internet]. 2020. https://educa.ibge.gov.br/jovens/conheca-o-brasil/populacao/18320-quantidade-de-homens-e-mulheres.html (٢٨.١١.٢٠٢٣).
  12. Brasil. Ministério da Defesa. Livro Branco de Defesa Nacional [Internet]. 2020. https://www.gov.br/defesa/pt-br/assuntos/copy_of_estado-e-defesa livro_branco_congresso_nacional.pdf (٢٨.١١.٢٠٢٣).
  13. Flor L, Campos M. Prevalência de diabetes mellitus e fatores associados na população adulta brasileira: evidências de um inquérito de base populacional. Revista Brasileira de Epidemiologia. 2017; 20(1): 1629, doi: 10.1590/1980-5497201700010002.
  14. Rostami H, Tavakoli HR, Rahimi MH, et al. Metabolic Syndrome Prevalence among Armed Forces Personnel (Military Personnel and Police Officers): A Systematic Review and Meta-Analysis. Mil Med. 2019; 184(9-10): e417e425, doi: 10.1093/milmed/usz144, indexed in Pubmed: 31247092.
  15. Oliveira L, Santos B, Machado Í, et al. Prevalência da Síndrome Metabólica e seus componentes na população adulta brasileira. Ciência & Saúde Coletiva. 2020; 25(11): 4269–4280, doi: 10.1590/1413-812320202511.31202020.
  16. Jeong S, Lee M, Ji E. Effect of pharmaceutical care interventions on glycemic control in patients with diabetes: a systematic review and meta-analysis. Ther Clin Risk Manag. 2018; 14: 1813–1829, doi: 10.2147/TCRM.S169748, indexed in Pubmed: 30319263.
  17. Choudhary K, Mali M, Bhaskar K, et al. Effect of Pharmaceutical Care Services Provided by Clinical Pharmacists on Type-2 Diabetes Patients. Journal of Pharmacy Practice and Community Medicine. 2019; 5(1): 2226, doi: 10.5530/jppcm.2019.1.5.
  18. Sociedade Brasileira de Diabetes. Diretrizes da Sociedade Brasileira de Diabetes 2022 [Internet]. 2022. https://diretriz.diabetes.org.br/ (٢٨.١١.٢٠٢٣).
  19. Cosentino F, Grant PJ, Aboyans V, et al. ESC Scientific Document Group. 2019 ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD. Eur Heart J. 2020; 41(2): 255323, doi: 10.1093/eurheartj/ehz486, indexed in Pubmed: 31497854.
  20. Muzy J, Campos M, Emmerick I, et al. Prevalência de diabetes mellitus e suas complicações e caracterização das lacunas na atenção à saúde a partir da triangulação de pesquisas. Cadernos de Saúde Pública. 2021; 37(5), doi: 10.1590/0102-311x00076120.
  21. Brasil, Ministério da Saúde. Pesquisa Nacional de Saúde 2019: percepção do estado de saúde, estilos de vida, doenças crônicas e saúde bucal [Internet]. 2020. https://biblioteca.ibge.gov.br/visualizacao/livros/liv101764.pdf (٢٨.١١.٢٠٢٣).
  22. Sodré F, Costa J, Lima J. Avaliação da função e da lesão renal: um desafio laboratorial. Jornal Brasileiro de Patologia e Medicina Laboratorial. 2007; 43(5): 329337, doi: 10.1590/s1676-24442007000500005.
  23. Veloso J, Guarita-Souza L, Júnior EL, et al. Perfil clínico de portadores de Diabetes Mellitus em acompanhamento multiprofissional em saúde. Revista Cuidarte. 2020, doi: 10.15649/cuidarte.1059.
  24. Oliveira REM, Franco LJ. Glycemic control in elderly people with type 2 diabetes mellitus attending primary health care units. Prim Care Diabetes. 2021; 15(4): 733736, doi: 10.1016/j.pcd.2021.04.011, indexed in Pubmed: 33903088.
  25. McCoy RG, Lipska KJ, Van Houten HK, et al. Paradox of glycemic management: multimorbidity, glycemic control, and high-risk medication use among adults with diabetes. BMJ Open Diabetes Res Care. 2020; 8(1), doi: 10.1136/bmjdrc-2019-001007, indexed in Pubmed: 32075810.
  26. Teljeur C, Smith SM, Paul G, et al. Multimorbidity in a cohort of patients with type 2 diabetes. Eur J Gen Pract. 2013; 19(1): 1722, doi: 10.3109/13814788.2012.714768, indexed in Pubmed: 23432037.
  27. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care [Internet]. 2022; 43, suppl. 1. https://diabetesjournals.org/care/issue/45/Supplement_1 (٢٨.١١.٢٠٢٣).
  28. Swinnen SG, Hoekstra JB, DeVries JH. Insulin therapy for type 2 diabetes. Diabetes Care. 2009; 32 Suppl 2(Suppl 2): S253S259, doi: 10.2337/dc09-S318, indexed in Pubmed: 19875560.
  29. Al-Musawe L, Martins AP, Raposo JF, et al. The association between polypharmacy and adverse health consequences in elderly type 2 diabetes mellitus patients; a systematic review and meta-analysis. Diabetes Res Clin Pract. 2019; 155: 107804, doi: 10.1016/j.diabres.2019.107804, indexed in Pubmed: 31376400.