Definition, Classification, Diagnosis and Differential Diagnosis of Diabetes Mellitus: Update 2023

Notice Of Update

The DDG clinical practice guidelines are updated regularly during the second half of the calendar year. Please ensure that you read and cite the respective current version.

Updates To Content Compared To The Previous Year’s Version

Change 1: Various changes in the section “Diagnostic approach for diagnosing diabetes” and “Pre-analytics of glucose measurement”. The new requirements for pre-analysis and analysis of glucose determination in accordance with the revised guideline of the German Medical Association for quality assurance of laboratory medical examinations (Rili-BAEK) are listed.

Reason: In May 2023, an updated version of the Rili-BAEK was published.

If applicable, supporting references: [13]

Change 2: The formulation on the reliability of HbA_1c in renal insufficiency has been adjusted.

Reason: Alignment with the clinical practice guideline “Nephropathy and Diabetes”.

If applicable, supporting references: [23]

Change 3: New section “Determination of ketone bodies”.

Reason: Measurement of ketone bodies is required in some clinical situations to determine the need for insulin therapy. Urine diagnostics, in which acetoacetate is measured, are delayed, and urine samples cannot be obtained easily at any time. On the other hand, measuring β-hydroxybutyrate in plasma or blood makes it possible to assess the risk of ketoacidosis more quickly.

If applicable, supporting references: [36] [37]

Change 4: Addition of the section “Differential diagnosis” to include a summarised description of the course of the development of type 1 or type 2 diabetes.

Reason: The differential diagnosis of type 1 and type 2 diabetes is summarised and thus easier for readers to understand.

Change 5: Removal of flow chart for differential diagnosis of type 1, type 2 diabetes and MODY

Reason: Due to the sometimes considerable fluctuations that can occur in the determination of C-peptide or autoantibodies depending on the laboratory and method, and due to the lack of standardisation in this context, the flow diagram has been removed. The diagnostic algorithm shown in this figure is still cited in the text, but it also points out the variability in the determination of C-peptide and autoantibodies.

Change 6: The “Outlook” section addresses the subtyping of type 1 and type 2 diabetes.

Reason: Subtyping is increasingly being discussed and is already being used in type 2 diabetes. A detailed analysis of the subtyping is still missing, so that no conclusive assessment is possible yet.

If applicable, supporting references: [64] [65]

Change 7: Brief discussion of diabetes diagnosis in clinics in the “Outlook” section.

Reason: There is a lack of systematic diabetes screening in clinics. The diagnostic algorithm is also not easily applicable. However, there is no national or international consensus on the glucose threshold above which a diabetes diagnosis is likely in inpatients. The additional measurement of HbA_1c may be useful in reducing the proportion of patients with undiagnosed diabetes.

Definition of diabetes mellitus

Diabetes mellitus is the collective term for a group of metabolic disorders resulting from chronic hyperglycaemias. The cause is either a disturbed or deficient insulin secretion or various grades of insulin resistance, or usually both to varying degrees.

Classification

Type 1 diabetes

• β-cell destruction that leads to an absolute insulin deficiency due to an absolute insulin deficiency, mostly immunologically mediated.

• Checkpoint inhibitor-induced diabetes with and without autoantibodies [1] [2]

• Latent Autoimmune Diabetes in Adults (LADA): a type of diabetes which usually slowly develops at an older age, classified as type 1 diabetes.

Type 2 diabetes

• Can range from a predominant insulin resistance with relative insulin deficiency to an extensive secretory insulin deficiency with insulin resistance.

• It is often associated with other conditions such as hypertension, obesity, lipid metabolism disorders, atherosclerosis, chronic obstructive pulmonary disease (COPD), obstructive sleep apnoea syndrome, depression, and metabolic-dysfunction associated fatty liver disease (MAFLD).

Other specific diabetes types

• Exocrine pancreatic diseases (e. g. pancreatitis, cystic fibrosis, hemochromatosis, pancreatic cancer, after pancreatic surgery (“Pancreatogenic diabetes”),

• Endocrinopathies (e. g. Cushing syndrome, acromegaly, pheochromocytoma);

• Drug-induced (e. g. glucocorticoids, neuroleptics, interferon-alpha, pentamidine, streptozocin),

• Infections (e. g., mumps)

• Rare forms of autoimmune-mediated diabetes.

• Genetic defects:

  • of β-cell function (e. g., Maturity Onset Diabetes of the Young [MODY] and neonatal forms)

  • of insulin action

• Other genetic syndromes which can be associated with a type of diabetes

Gestational diabetes

A glucose use disorder which is first diagnosed during pregnancy [3] [4] [5] [6].

Diagnosis

Diagnostic criteria

Diabetes mellitus

The diagnostic criteria listed for diabetes mellitus are in accordance with the recommendations of the international diabetes associations (International Diabetes Federation [IDF], American Diabetes Association [ADA], European Association for the Study of Diabetes [EASD], etc.) and the World Health Organization (WHO).

The medical evaluation limits presented here represent the current state of scientific consensus.

Table 1 Oral glucose tolerance test (oGTT).

Performing the 75g OGTT – oral glucose tolerance test – in accordance with WHO guidelines
Performing the test in the morning After 8–12 hours fasting from food, nicotine and alcohol After a≥3-day diet rich in carbohydrates (≥150 g carbohydrates per day) Sitting or lying (no muscular exertion); no smoking before or during the test
At time 0, ingestion of 75 g glucose (or equivalent amount of hydrolysed starch) in 250–300 ml water within 5 min. For children 1.75 g/kg (maximum 75 g) Venous blood sampling at time 0 and 120 minutes Proper sample processing, storage, and measurement of glucose concentration using a quality-assured method (see below).
Test contraindicated in intercurrent diseases, for gastrointestinal resection or gastrointestinal diseases with altered resorption or if diabetes mellitus has already been diagnosed.
Self-preparing of the glucose solution to perform the oGTT is rejected by the DDG for reasons of quality assurance [15] [16]. As with all other laboratory tests, it is a prerequisite that the oGTT is performed correctly for diagnostic purposes, including preparation of the patient. The intra- and inter-individual varying absorption behaviour can lead to increased variability of glucose concentrations in the oGTT [17].

Test contraindicated in intercurrent diseases, for gastrointestinal resection or gastrointestinal diseases with altered resorption or if diabetes mellitus has already been diagnosed.

Venous plasma glucose is the measured variable

• Occasional plasma glucose concentration of≥11.1 mmol/l (≥200 mg/dl; mmol/l is the starting unit, mg/dl figures have been rounded to whole numbers)

• or

• Fasting plasma glucose concentration of≥7.0 mmol/l (≥126 mg/dl) (fasting period 8 to 12 hours)

• or

• oral glucose tolerance test (OGTT) 1-h value in venous plasma≥11.1 mmol/l (≥200 mg/dl) (for procedure specifications see [Table 1]) or

  HbA _1c is the measured variable

• HbA1c≥48 mmol/mol haemoglobin (Hb) (≥6.5%)

taking into account influencing factors and specificities ([Table 5])

Table 5 Comparison of selected factors relevant to the diagnosis of diabetes which influence fasting plasma glucose or HbA1c (+= influence, −=no or little influence).

	Glucose	HbA1c
Muscle exertion	+	–
Food intake	+	–
Location of blood sampling	+	–
Haemoglobinopathies:	–	+
Haematological disease	–	+
Erythrocyte turnover	–	+
Age	–	+
Individual variation from day to day	+(12 to 15%)	– (<2%)
Blood sample	+(unstable in whole blood)	– (stable up to 7 days at room temperature)

Abnormally-elevated fasting plasma glucose concentration

IFG (impaired fasting glucose) for the range of fasting glucose of 5.55 to <7.0 mmol/l (100 to <126 mg/dl) in venous plasma. A fasting glucose level of<7.0 mmol/l (<100 mg/dl) does not rule out manifest diabetes.

An abnormally elevated fasting glucose concentration is defined inconsistently internationally. For example, the ADA sets the glucose limit value at 5.6 mmol/l (100 mg/dl) [7], while the IDF and WHO set this limit at 6.1 mmol/l (110 mg/dl) [8] [9].

Impaired glucose tolerance

Impaired glucose tolerance (IGT) corresponds to a 2-h plasma glucose value oGTT in the range of 7.8–11.1 mmol/l (140 to<200 mg/dl) with fasting plasma glucose concentrations of<7.0 mmol/l (<126 mg/dl) in venous plasma.

Internationally, there is no uniform definition of impaired glucose tolerance. While the WHO defines an IGT only in the context of an IFG [8], the ADA has an IGT with and without an IFG[7]. The IDF clearly distinguishes between IGT (2 h value between 7.8 to<11.0 mmol/l (140 to<200 mg/dl) and separately an IFG with fasting glucose values of 6.1 to 6.9 mmol/l (110 to 125 mg/dl) [9].

However, many people with a glucose use disorder have IFG and IGT. In recommendations of various international diabetes societies, an HbA_1c value of 39 to 48 mmol/mol Hb (5.7 to 6.4%) is referred to as “pre-diabetes” ([Fig. 1]) [7], however, this circumstance is not necessarily associated with a manifestation of diabetes. For the age dependency of the HbA1c value, see [Table 2].

Table 2 Reference ranges for HbA1c values collected in two large adult collectives in Germany.

	Roth J et al., 2016 [26] (n=6783)	Masuch A et al., 2019 [27] (n=8665)
<40 years	27 to 41 mmol/mol Hb (4.6 to 5.9%)	20 to 42 mmol/mol Hb (4.0 to 6.0%)
40 to<60 years	29 to 44 mmol/mol Hb (4.8 to 6.2%)	21 to 44 mmol/mol Hb (4.1 to 6.2%)
≥60 years	31 to 46 mmol/mol Hb (5.0 to 6.4%)	25 to 49 mmol/mol Hb (4.4 to 6.6%)

Gestational diabetes

In accordance with the recommendations of the Joint National Committee (G-BA) in the latest version dated 1 January 2022, all pregnant women should be offered a screening test with 50 g glucose solution for gestational diabetes between 24+0 and 27+6 weeks of pregnancy as part of statutory health insurance. Pregnant women do not need to fast for the test and screening can be carried out regardless of the time of the last meal [https://www.g-ba.de/richtlinien/19/]. The plasma glucose concentration should be determined 60 min after administration of the glucose solution in a venous blood sample using a quality-controlled method.

A leaflet is provided to pregnant women early on in order to help them make an informed decision about performing the test and possible treatment options (https://www.g-ba.de/richtlinien/anlage/170/). A 75 g-oGTT should be performed promptly in pregnant women with a result of the 1 h value of 7.5 to 11.1 mmol/l (135 to 200 mg/dl). Gestational diabetes is diagnosed directly for a result>11.1 mmol/l (200 mg/dl). As of 2019, it is also possible for midwives to perform the screening test (https://www.gkv-spitzenverband.de/media/dokumente/krankenversicherung_1/ambulante_leistungen/hebammen/aktuelle_dokumente/Hebammen_Anlage_1.3_Verguetungsverzeichnis_ab_01.01.19.pdf). The information listed in [Table 3] for glucose measurement results in the oGTT with regard to diagnosing gestational diabetes are based on the results of the HAPO Study [3]. Exceeding one glucose limit value in the oGTT is sufficient to make the diagnosis [4] [5] [6]. A recent study from New Zealand suggests that these glucose limits do not reduce the risk of neonatal macrosomia compared to slightly higher glucose limits [10]. On the other hand, the study showed higher costs in health care when using the established, lower limit values.

Table 3 Limit values for glucose measurement results for diagnosing diabetes/gestational diabetes with a 75 g oGTT. Diabetes is confirmed when one of the glucose levels is exceeded. For the aspects to be considered in the pre-analysis of glucose determination (see below) as well as in the quality of glucose measurement and for further information, reference is made to the S3 guideline on gestational diabetes [5] and to a current review [6] as well as the latest version of the guideline of the German Medical Association for quality assurance of laboratory medical examinations (Rili-BAEK) [13].

	Venous plasma glucose concentration
	mmol/l	mg/dl
Fasting	≥5.1	≥92
60 min	≥10.0	≥180
120 min	≥8.5	≥153

In pregnant women in whom only one measured value is elevated and this values is close to the decision value – or a definitive exclusion or confirmation of the diagnosis is not possible taking into account the “minimum difference” (see below) – the oGTT should be repeated after one week .

Diagnostic approach for diagnosing diabetes

The recommended diagnostic approach is shown in [Fig. 1].

Fig. 1 Algorithm for the diagnosis of diabetes. The simultaneous measurement of glucose and HbA1c has practical advantages, as these measured variables complement each other. If plasma glucose and HbA1c are pathologically elevated (see text), no other determination is necessary. In case of discrepant results of the different parameters, an oGTT should be performed. In practice, a repeat plasma glucose and HbA1c measurement can be done prior to an oGTT. A repeated measurement should be performed promptly, within 1 to 2 weeks. oGTT: oral glucose tolerance test; IFG: impaired fasting glucose; IGT: impaired glucose tolerance. *A normal fasting plasma glucose concentration (<5.55 mmol/l;<100 mg/dl) does not exclude manifest diabetes.

Only quality-assured laboratory methods may be used to measure the venous plasma glucose concentration and the HbA1c value for diagnosing diabetes [11] [12]. This is defined in the guideline of the German Medical Association for Quality Assurance of Laboratory Medical Examinations (Rili-BAEK) as standard for laboratories in hospitals and in private practice as well as for point-of-care testing (POCT) [13]. This does not include systems for patient self-testing.

In the updated Rili-BAEK dated May 2023, there are two important changes with regard to glucose regulations, which will become mandatory in June 2026 after a transition period of three years:

1. Pre-analytics: If plasma separation or glucose measurement is not performed within 15 minutes, blood collection tubes with suitable glycolysis inhibition must be used. The use of serum is unsuitable.

2. Pre-analytics: The requirements for the measurement quality of glucose determination are reduced from±11% to±5% for internal quality assurance and from±15% to±8% for external quality assurance (ring trials).

To date, participation in ring trials has not been mandatory for point-of-care testing for measuring these parameters, as they are used in practices, although the updated version of the Rili-BAEK generally recommends participation for physicians in private practices and medical services without a central laboratory. Furthermore, care must be taken to ensure that the respective glucose monitoring systems for point-of-care-testing are approved by the manufacturer for diagnosis before use in diabetes diagnostics.

Selected analytical aspects

Pre-analytics of glucose measurement

Proper pre-analytical handling of blood samples is crucial for reliable glucose measurement. Suitable blood collection tubes must be used so that glycolysis is completely inhibited in the blood collected. For this the addition of citrate plus fluoride is necessary; fluoride alone is not sufficient. The blood collection tubes with glycolysis inhibitors currently on the market exhibit various handling characteristics as seen in [Table 4]. These glycolysis inhibitors work reliably, and it has been shown that the glucose levels correspond to precisely defined baseline values [14]. The hypothesis of an overdetermination of the glucose concentration when using such tubes could thus be refuted.

Table 4 Commercially available blood collection tubes that achieve complete glycolysis inhibition by the addition of fluoride and citrate (current status see manufacturers’ homepages).

Manufacturer	Product name	Correct filling absolutely necessary	Sufficient mixing required	Dilution factor
Greiner bio-one	Vacuette FC-Mix	No	10 times	No (granulate)
Kabe	Primavette, KABEVETTE	Yes	Few times	1.16 (liquid additive)
Sarstedt	S-Monovette GlucoEXACT	Yes	Few times	1.16 (liquid additive)

The blood collection tubes made by the company Greiner bio-one (Vacuette FC-Mix) contain a granulate. The tubes must be gently swirled ten times to adequately dissolve the additive and mix the blood with the glycolytic inhibitors. Experience has shown that dilution errors occur when using blood collection tubes by the company (Primavette, KABEVETTE) and the company (S-Monovette GlucoEXACT) if the tubes have not been filled completely. The laboratory must reliably identify such tubes in order to identify and exclude from analysis tubes that are not correctly filled according to the manufacturer’s specifications and to take into account the dilution factor of 1.16.

Alternatively, if blood collection tubes are used without immediate and complete glycolysis inhibition, they must be centrifuged immediately after sample collection and the plasma separated from the cells. When using blood collection tubes with a gel, centrifugation automatically separates the plasma supernatant from the blood cells. If a blood collection tube without gel is used, the plasma supernatant must be removed immediately after centrifugation. If a time window of 15 min until centrifugation is exceeded, the affected samples should be discarded due to the ongoing glycolysis and the therefore falsely lower glucose values caused by it [13].

HbA_1c for diabetes diagnosis

The use of a single HbA1c value for diabetes diagnosis is not generally recommended – contrary to recommendations of other international professional societies – as HbA1c values are influenced by various factors, including diabetes-independent age increase (see below). In the case of pathological values, diabetes mellitus is usually present; however, it is not possible to rule out diabetes with HbA1c values in the reference range; there are too many other factors here that can lead to false-low values. If the suspicion of a diabetes diagnosis is based on an HbA_1c measurement, then a confirmatory measurement by re-measuring this parameter is not useful (see above). Since HbA _1c is a haemoglobin , it is influenced by various factors, including haematological factors [18] (see also info box). Furthermore, there are a number of methodological problems to be considered [19] [20].]

In order to improve the precision and correctness of the HbA1c measurement, the permitted pass marks for internal quality assurance and external quality assurance (ring trials) have been adjusted. For example, the permissible deviation for internal quality control has been reduced from±10% to initially±5% and for external quality control from±18% to±8% [21]. As of December 2023, the binding permissible deviation for internal quality control has been reduced from±5% to±3% [13].

In order to detect possible influences on the HbA1c value, an up-to-date Hb value should be available as part of a blood count, especially if the HbA_1c value is to be used to diagnose diabetes mellitus.

Notice

Factors that lead to the influence of the HbA1c or to disturbances of the HbA1c measurement. Factors which influence the HbA1c value and lead to a

• decrease (especially factors that increase erythrocyte turnover).

  • Haemolytic anaemia caused, e. g., by immunological processes, medications such as cephalosporins.

  • Treatment of iron or vitamin deficiency anaemia with appropriate medication

  • Severe hepatic or renal insufficiency

  • Haematologic diseases that increase erythrocyte turnover (thalassemias, pathologic haemoglobins).

increase (especially factors that decrease erythrocyte turnover).

• Anaemia, e. g., due to iron or vitamin deficiency (B12, folic acid).

• Splenectomy

• Age [22]

• Ethnicity, HbA1c is approx. 4 mmol/mol Hb (~0.4%) higher in African Americans than in Caucasians

Interference factors that can falsify the measurement of HbA _1c

• Most notably, haemoglobin variants that mismeasure HbA1c, depending on the method used

• As of stage G3b/G4 Kidney Disease: Improving Global Outcomes (KDIGO), the HbA1c value is no longer a reliable parameter for the quality of metabolic control, as it can be unreliable, especially in the presence and/or treatment of renal anaemia [23].

The HbA _1c value is not suitable for diagnosing diabetes in

• Neonates (HbF~90%)

• Pregnant women for the diagnosis of gestational diabetes

• Women up to about 2 months postpartum

• Hyperglycaemic drugs, e. g., glucocorticoids, psychotropic drugs if taken<2 months

• Diseases of the pancreas incl. pancreatic surgery

• Blood transfusions, blood donation, major bleeding (surgery, accidents)

Age dependency of HbA_1c

HbA_1c increases with age in people without diabetes [24] [25] [26] [27] [28] [29] [30]. This physiological increase can be 0.4–0.7% (4–8 mmol/mol Hb) in absolute terms. This, in addition to methodological differences, limits the use of HbA1c value for diabetes diagnosis, especially in the range below 53 mmol/mol Hb (7.0%) in people aged 60 and over. [Table 2] shows reference values of HbA1c level in non-diabetic adults of younger, middle and older age from two German populations [26] [27]. In the table 2.5th to 97.5th percentiles are given as the reference range. However, a measured value above the reference range does not necessarily have to be pathological [31].

Advantages and disadvantages of the glucose and HbA_1c parameters

The laboratory parameters glucose, especially fasting plasma glucose, and HbA1c, which are approved for the diagnosis of diabetes, both have advantages and disadvantages, however they complement each other perfectly ([Table 5]).

Comparison of glucose and HbA1c

The 2-hour value according to oGTT and the HbA_1c value are approved for the diagnosis of diabetes mellitus, fasting plasma glucose (see above). The DECODE study, however, shows that normal fasting glucose does not rule out diabetes. Approximately 1/3 of the people with a clearly diabetic 2-h value had normal fasting plasma glucose values [32]. On the other hand, an HbA_1c<48 mmol/mol Hb does not exclude manifest diabetes. In more than one-third of people with a diabetic 2-h plasma glucose level (≥11.10 mmol/l or 200 mg/dl), the HbA_1c value was below the threshold of 48 mmol/mol Hb (6.5%) [33] [34].

Quality assurance

According to the guidelines of the German Medical Association for Quality Assurance of Laboratory Medical Examinations (Rili-BAEK), internal quality control for glucose and HbA_1c measurements must be carried out on working days with suitable control material. Successful participation in external quality assurance is required once per quarter.

This applies to all laboratory systems. It should also apply to unit-use systems of point-of-care testing (individual test strips or cuvettes, as defined by the Rili-BAEK) used by practices and intended by the manufacturer for diagnosing diabetes. The updated Rili-BAEK now also recommends participation in ring trials for this area [13].

Minimum difference

How should a single measured value be evaluated in consideration of the measurement uncertainty of the measurement results?

In the case of measurement results, there is the general question of whether the deviation from the diagnostic cut-off is so far removed from this decision limit (i. e., greater than the minimum difference (MD), see below) that this measured value can clearly be assessed as lower or higher. In such cases the MD should be used for assessment.

In order to meet the clinical requirements, the analytical variability of the absolute values at decision limits is specified. The MD is a simple tool to illustrate the meaning of the random error to the user and is calculated from the standard deviation (SD) (MD=2×SD) ([Fig. 2]) [35]. The factor 2 by which the SD is multiplied depends on the confidence level. While a factor of 2 corresponds to a confidence level of 95% [35], a factor of 1.65 ( [13]) corresponds to only 90%.

Fig. 2 Minimum difference, expressed in the unit of glucose determination (mmol/l or mg/dl) for the considered diagnostic clinical decision values as a function of the coefficient of variation. If the measured values are below the overlapping range of the inverted triangles, the diagnostic clinical decision values can be analytically differentiated from each other and thus used for the diagnosis.

This MD, which can be obtained from the cooperative laboratory, gives concrete concentrations in absolute values above which a measured value differs from a diagnostic cut-off. At a fasting plasma glucose concentration cut-off value of 7.0 mmol/l (126 mg/dl), the MD should not be greater than 0.7 mmol/l (12.6 mg/dl). The same applies to an HbA1c cut-off of 48 mmol/mol Hb (6.5%). The MD should not be greater than 2 mmol/mol Hb (0.2%).

Determination of ketone bodies

Measurement of ketone bodies in the first manifestation of diabetes mellitus is necessary in some situations to determine the need to start insulin therapy.

Ketone bodies are often measured qualitatively in urine (acetone), but urine samples cannot be obtained at any time without any problems. In principle, β-hydroxybutyrate, which is primarily produced in ketoacidosis, can also be sensitively measured in the blood or plasma. An increase in the concentration of β-hydroxybutyrate in the blood occurs without any time delay [36], different to an increase in the concentration of acetone in the urine, however the measurement is currently associated with higher costs. In the case of clinical symptoms of ketoacidosis, which can also occur in a normoglycaemic state, especially with SGLT-2 inhibitor therapy, measurement in blood or plasma can offer advantages over urine diagnostics. Values of>3 mmol/l β-hydroxybutyrate in serum are certainly to be regarded as pathological [37].

Determination of islet autoantibodies

The measurement of specific islet autoantibodies (AAB) is helpful for the differential diagnosis of the different types of diabetes, but in practice it is only used in justified individual cases ([Table 6], [7]) [38]. Thus, the presence of islet AAB can be considered an early stage in the development of type 1 diabetes mellitus, without symptoms or metabolic changes. Since the islet AABs can often be detected years before clinical manifestation in people at high risk of disease, they represent important predictive and early diagnostic markers. Antibody diagnostics is also useful for the differential diagnosis of patients with insulin deficiency due to autoimmune β-cell destruction and of patients with clinically quite similar severe insulin-deficient diabetes (SIDD) [39] [40] [41] both of which have a different prognosis. Islet AAB determination is also useful in estimating the risk of developing type 1 diabetes in patients with polyglandular autoimmune syndromes.

Table 6 Islet autoantibodies used in routine diagnostics in the initial diagnosis of type 1 diabetes mellitus. Data according to [38]

Antigen	Islet autoantibodies1	Prevalence at initial diagnosis2
Glutamate decarboxylase	GADA	60 to 85%
Insulinoma-associated antigen-2	IA-2A	50 to 85%
Zinc transporter ZnT8	ZnT8A	50 to 80%
Insulin	IAA3	Adults:<30% children<5 years:>90%
Various islet cell antigens	ICA4	Variable

¹ There are now certified combination tests that can be used to measure GADA, IA-2A and ZnT8A simultaneously. ² Due to the limited number of studies, the prevalence figures are to be viewed with reservations. ³ The prevalence of IAA is inversely correlated with the patient’s age at diabetes diagnosis. ⁴ Due to the measurement method (indirect immunofluorescence on human pancreatic tissue), the assessment of the test result depends on the experience of the examiner. The test provides only semi-quantitative results and is therefore obsolete.

Table 7 Indication for the determination of islet autoantibodies Data according to [38]

Early diagnosis of type 1 diabetes in people with type 1 diabetes in the family, as part of screening programs or studies (GADA/IA-2A/ZnT8A/IAA) Confirmation of the diagnosis of type 1 diabetes (GADA/IA-2A/ZnT8A/IAA up to 14 days after initiation of insulin therapy) Confirmation of the diagnosis of a LADA (GADA/IA-2A/ZnT8A) Diabetes with therapy with immune checkpoint inhibitors (ICPI). The islet autoantibodies can be positive or negative Differential diagnosis of diabetes in polyendocrine disorders Exclusion of autoimmune diabetes in case of suspected MODY Exclusion of autoimmune diabetes in diseases of the exocrine pancreas

In contrast to classical laboratory measured values in diabetology, such as glucose, HbA1c, C-peptide and insulin, which are molecularly precisely defined, islet AABs have a high biological variability. This means that a molecular definition and thus a standardisation are impossible [38] [42], Biological variability is due to several factors:

• Islet AABs are produced individually by each person and thus differ in their amino acid sequence and therefore in the binding region of the autoantigen.

• Islet AABs are polyclonal, i. e. they also differ molecularly within a single person (even in one individual, autoantibodies have a different affinity for the antigen).

• The epitopes detected by islet AABs are mostly conformational epitopes. This means that not only one specific amino acid sequence, but also secondary or tertiary protein structures are recognised. Therefore, a test based on only one epitope is not sufficient. False negative results must be expected.

• Islet AABs vary over time. This means that a patient’s islet AAB can change over time in terms of immunoglobulin isotypes, subtypes (IgG1 to IgG4) and target epitopes.

In the determination of the various islet autoantibodies, the measured variable is therefore not precisely defined molecularly. Thus, the autoantibodies are not defined themselves, but by the recognition of their target antigen and by their isotype and are determined as such. Comparability of the measured values, if they are carried out in different (special) laboratories, must be achieved via external quality assurance and possible use of reference methods using islet AAB standards [43]. In practice, only independently evaluated islet AAB assays with high sensitivity and specificity should be used.

Measurement of β-cell function

Measuring the functionality of β-cells in the islets of Langerhans in the pancreas is increasingly important not only for diabetes typing [44], in people with type 2 diabetes [45] and pre-diabetes with their subtypes [39] [40] [41] but also for deciding whether insulin therapy is indicated in people with type 2 diabetes [45]. With the help of the HOMA model (Homeostasis Model Assessment), it is possible to make a qualitative statement about the degree of insulin resistance or reduced β-cell secretion [46] [47].

The β cells secrete insulin and C-peptide into the blood in equivalent quantities as the two β-cell-specific intracellular cleavage products of proinsulin. Already during the first passage through the liver, up to 90% of the secreted insulin is broken down there. C-peptide, on the other hand, is predominantly (approx. 80%) eliminated in the kidneys [48] [49]. Both peptide hormones are measurable by immunological methods in heparin/EDTA plasma samples or serum. C-peptide measurement as a surrogate parameter of β-cell function is superior to insulin measurement due to the much longer in vivo half-life of C-peptide compared to insulin, the extensive resistance of C-peptide to degradation in haemolysed blood, and the better laboratory standardisation of the measurement of C-peptide in immunoassays .

The assessment of the C-peptide concentration measured in plasma or serum is only possible to a limited extent with decreasing filter function of the kidneys (eGFR) [50]. In patients with impaired renal function, this should be taken into account or this diagnosis should not be performed.

As with many other measurement methods, the reproducibility of the measurement (CV) and the lower limit of detection for C-peptide depend on the assays used. Only CE-marked assays performed in medical laboratories should be used.

Differential diagnosis

The differential diagnostic criteria for the most common diabetes types are listed in [Table 8]. The diagnostic algorithm, such as the one developed by the ADA and the EASD [52], is of increasing importance because the different diabetes types require different treatment strategies and have different long-term prognoses. However, this does not mean that MODY diabetes should also be reliably excluded at considerable financial expense for every type 1 diabetes that is clinically and chemically unambiguous [Table 9].

Table 8 Differential diagnostic criteria for common diabetes types at diagnosis. Data according to [51].

	Type 1 diabetes1	Type 2 diabetes	MODY
Aetiology	Autoimmune, genetic predisposition	Genetic predisposition, multifactorial	Monogenic
Heredity	Variable	Variable	Autosomal dominant; diabetes in≥3 generations
Frequency among all diabetes types	5 to 10%	90 to 95%	Approx. 2%
Pathogenesis	Autoantibodies, absolute insulin deficiency	Insulin resistance and secretion disorder up to (absolute) insulin deficiency	Mutation of genes of transcription factors or glucokinase of the β-cells
Typical age of manifestation	Childhood to adulthood	Adulthood	Adolescence to early adulthood
Clinical manifestation	Acute: polyuria, polydipsia, severe hyperglycaemia, ketoacidosis	Slow onset, often secondary diseases at the time of diagnosis, moderate hyperglycaemia	Slow onset, variable hyperglycaemia
Concomitant diseases	Autoimmune thyroiditis, celiac disease	Visceral obesity, hypertension, dyslipidaemia, diabetes (also called metabolic syndrome)	Renal cysts also according to MODY type
Tendency to ketosis	Yes	No	No
Body weight	Normal weight	Overweight	Normal weight
Plasma insulin/C-peptide serum HOMA-B2	Reduced to lacking	Often high at beginning, then reduced	Mostly reduced
Autoantibodies	Yes	No	No
Insulin resistance HOMA-IR3	No	Yes	No
Therapy	Insulin	Lifestyle modification measures, oral antidiabetics, GLP-1 RA, insulin	Possibly none, OADs, insulin (according to MODY type)

GLP-1 RA: glucagon-like peptide-1 receptor agonist; MODY: Maturity Onset Diabetes of the Young; OADs: oral antidiabetic drugs. ¹ Latent Autoimmune Diabetes in Adults (LADA) is associated with a slow loss of β-cell function. LADA has a rapid failure of oral antidiabetics. If LADA is suspected, determination of islet autoantibodies is recommended. ^{2, 3} HOMA-B or Homa-IR Homeostasis Model Assessment (see below) to quantify β-cell function and insulin resistance.

Table 9 Stages of type 1 diabetes.

	Stage 1	Stage 2	Stage 3
Characteristics	Islet autoimmunity, normoglycaemia, pre-symptomatic	Islet autoimmunity, disglycaemia, pre-symptomatic	Islet autoimmunity, hyperglycaemia 3a: Pre-symptomatic* (see [Fig. 1]) 3b: Symptomatic [53]
Diagnostic criteria	≥2 islet autoantibodies positive	Islet autoantibodies positive	Islet autoantibodies may not (or no longer) be present

^*Other international medical societies classify only symptomatic people with type 1 diabetes as stage 3 [7].

However, if the diabetes type is unclear, differential diagnosis should be initiated, although both C-peptide concentrations and autoantibody titers may vary depending on the laboratory and its analyses.

In the development of type 1 and type 2 diabetes, various pathological events occur. The development of type 2 diabetes is triggered by genetic predisposition and constitutional factors that promote insulin resistance and are initially compensatory for increased insulin and C-peptide levels. Over the course of most of the years, there is an increasing β-cell dysregulation (decreasing insulin and C-peptide concentrations) resulting in pre-diabetes and finally manifest diabetes. In contrast, type 1 diabetes is an autoimmune disease (usually detectable by autoantibodies) that is likely triggered by a number of environmental factors in genetic predisposition [54]. Autoimmune processes lead to the destruction of the β-cells and thus to an absolute insulin deficiency.

Type 1 diabetes – stages and early diagnosis

In a new classification, three stages of type 1 diabetes are defined ([Table 9]).

Multiple islet autoantibodies are a risk factor for the development of clinically-manifest diabetes [55] and an indication for intervention in clinical trials aimed at delaying or preventing the progressive loss of β-cells.

Screening for pre-symptomatic type 1 diabetes through screening tests to detect autoantibodies to insulin, GAD, IA-2, or zinc transporter-8 is currently recommended in screening programs (e. g., Fr1da, https://www.fr1da.de), clinical research studies, and for family members of a subject with type 1 diabetes. Early detection, training and monitoring can prevent the occurrence of diabetic ketoacidosis in patients in stages 1 and 2 during clinical manifestation. This may contribute to a reduction in associated short- and long-term morbidity and mortality, improved residual β-cell function through early therapy, and better long-term glucose control [56].

Latent Autoimmune Diabetes in Adults (LADA)

LADA is a mostly slow-developing diabetes that occurs mainly in adults (>35 years) and is genotypically and phenotypically extremely heterogeneous. Indications of LADA arise from a positive family history of autoimmune diseases (e. g. thyroid disease, celiac disease, vitiligo with and without type 1 diabetes) and normal to overweight. Lifestyle changes with reduction of obesity, increase in physical activity and oral antidiabetic drugs can be therapeutically effective and thus phenotypically correspond to type 2 diabetes. However, deterioration in glucose control occurs remarkably quickly (within months or 1 to 2 years) at relatively low C-peptide levels. At this point, at the latest, the diagnosis of type 2 diabetes should be reconsidered and islet autoantibodies should be measured in order to initiate insulin therapy at an early stage [57] [58], Due to the often limited specificity of autoantibody determinations, there are both “real” patients with type 1 diabetes and patients with type 2 diabetes with a false positive antibody test. A recent systematic review shows a high incidence of type 1 diabetes in adulthood, with global incidences lowest among Asians and highest in the Nordic countries. It is higher in men than in women [59].

MODY

The term MODY is used to describe various diabetes types that are usually diagnosed from adolescence to adulthood and are caused by known genetic mutations. The diagnostic algorithm of the main MODY forms is shown in [Fig. 3.]

Fig. 3 The most common MODY forms: Clinic, genes, protein, therapy, heredity. Data according to [60] [66] and MODY Probability Calculator (www.diabetesgenes.org). SHs: sulfonylureas; GLP-1 RA: glucagon-like peptide-1 receptor agonist; DPP4: dipeptidyl peptidase-4; MODY: Maturity Onset Diabetes of the Young.

Pancreoprive diabetes mellitus

Diabetes that develops due to diseases of the pancreas is subsumed under the term pancreopriver diabetes mellitus. The diagnostic criteria are listed in [Table 10].

Table 10 Diabetes diagnosis of a diabetes due to an exocrine pancreas disease. Data according to [61].]

Criteria	Expression
Main criteria (all must be present)	Exocrine pancreatic insufficiency (documented by stool tests for elastase-1 or a direct functional test)Pathological imaging of the pancreas (sonography, endosonography, MRI, CT)Lack of autoantibodies as an indication of type 1 diabetes
Additional criteria	Impaired β-cell function (e. g., HOMA-B, C-peptide-glucose quotient) [45]No greatly increased insulin resistance (e. g. HOMA-IR)Reduced incretin secretion (e. g. GLP-1, pancreatic polypeptide)Low serum values of fat-soluble vitamins (A, D, E and K)

HOMA-IR=Homeostasis Model Assessment for Insulin Resistance;HOMA-B=Homeostasis Model Assessment of β-cell function;CT=computed tomography; MRI=magnetic resonance imaging; GLP-1=glucagon-like peptide-1.

Screening

For primary screening for type 2 diabetes, a diabetes risk test is recommended.

The following questionnaires are recommended:

• German Diabetes Risk Score (https://drs.dife.de/)

• FINDRISK Questionnaire (https://www.diabetesstiftung.de/findrisk)

The procedure for elevated scores, manifest cardiovascular disease or the presence of obesity with other risk factors, e. g. hypertension, dyslipidaemia (elevated triglycerides or LDL cholesterol or low HDL cholesterol), or in the case of a positive family history of type 2 diabetes in first-degree relatives, gestational diabetes, PCOS (polycystic ovary syndrome) or non-alcoholic fatty liver disease is described in [Fig. 1].

There is a lack of systematic screening in clinics with regard to the proportion of people with diabetes who are treated there. According to a study by the University Hospital Tübingen, 24% of the patients newly admitted to the hospital had pre-diabetes and 22% had manifest diabetes, with one in 6 people with diabetes not previously aware of the disease [62].

Outlook

The discussion on subtyping of type 1 and type 2 diabetes is growing [64] [65]. While the relevance of subtyping type 1 diabetes is currently questionable in practice, subtyping of type 2 diabetes is already taking place to allow for appropriate therapy, e. g. in older people with mild diabetes. A detailed analysis of the additional parameters required compared to the standard of care as well as the need for regularly repeated determinations of these parameters in order to map the possible change between the subtypes compared to the clinical benefit is currently not available.

Since plasma glucose is often measured in hospitals, the measured values could be used to reduce the proportion of people with undiagnosed diabetes, especially in the emergency room and internal medicine departments. However, the diabetes algorithm shown in [Fig. 1] is not readily applicable. So far, there is no national or international consensus on possible thresholds for diabetes diagnosis in inpatients. The additional, parallel determination of HbA_1c can be useful in this context.

The high variability in oGTT has been known for a long time [17], so that the question is raised about the relationship between the fasting or 1-h or 2-h value with the risk of secondary diseases. A number of studies indicate that the 1-h value has a higher predictive value for type 2 diabetes than the 2-h value [63].

German Diabetes Association: Clinical Practice Guidelines This is a translation of the DDG clinical practice guidelinepublished in Diabetol Stoffwechs 2023; 18 (Suppl 2): S100–S113. doi: 10.1055/a-2075-9943

Information/Links

Addresses on the Internet

https://www.ddg.info

Current version of the evidence-based guidelines:

https://www.ddg.info/behandlung/leitlinien

Notice

This article was changed according to the following Erratum on March 12th 2024.

Erratum

The first sentence on the 4th page of the article was corrected. Correct is:

In pregnant women in whom only one measured value is elevated and this values is close to the decision value – or a defi nitive exclusion or confi rmation of the diagnosis is not possible taking into account the “minimum diff erence” (see below) – the oGTT should be repeated after one week.

Conflict of interest

S. Pleus is an employee of the Institut für Diabetes-Technologie Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm (IfDT).A. Tytko is a diabetologist in private practice and received consulting fees from Roche as part of a project of the Association of Registered Diabetologists of Lower Saxony (VNDN); lecture fees and reimbursement of travel expenses from the companies Lilly, Novo Nordisk, Sanofi.R. Landgraf declares the following potential conflicts of interest: Advisory boards: Lilly Deutschland, Novo Nordisk Pharma; lecture fees: Lilly Deutschland, Novo Nordisk Pharma. Other activities: Curator of the German Diabetes Foundation, member of the steering group for the development and updating of the National Healthcare Guidelines on Diabetes.L. Heinemann is a shareholder of the Profil Institute for Metabolism Research GmbH, Neuss. He is an advisor for many companies which develop new diagnostic and therapeutic options for diabetes therapy.C. Werner declares the following potential conflicts of interest: Travel reimbursement from Novartis Oncology, most recently in 2018. Shareholdings in Medtronic and Novo Nordisk.D. Müller-Wieland declares the following potential conflicts of interest: Member of advisory boards and lecture fees: Amarin, Amgen, Boehringer Ingelheim, Daiichi-Sankyo, Lilly, MSD, AstraZeneca, Novo Nordisk, Novartis, Sanofi.A.G. Ziegler received consulting and lecture fees from Provention Bio and Sanofi. U.A. Müller declares no conflicts of interest. Public declaration of interests: https://www.akdae.de/Kommission/Organisation/Mitglieder/DoI/Mueller.pdfG. Freckmann is Medical Director and Managing Director of the IfDT, which carries out clinical studies e.g. with medical devices for diabetes therapy on its own initiative and on behalf of various companies. G.F./IfDT have received speakers’ honoraria or consulting fees in the last 3 years Abbott, Berlin Chemie, Boydsense, Dexcom, Lilly Deutschland, Novo Nordisk, Perfood, Pharmasens, Roche, Sinocare, Terumo, Ypsomed.E. Schleicher declares no conflicts of interest.H. Kleinwechter declares no conflict of interest with regard to this clinical practice guideline.M. Nauck has received lecture fees from Amgen, Novartis, Synlab, Tosoh Bioscience, Radiometer, Roche Diagnostics, Technopath. Advisory board: Novartis.A. Petersmann has received consulting and lecture fees from Tosoh Bioscience, Radiometer, Roche Diagnostics, Nova Biomedical, Siemens Healthineers, Technopath.

^† First Authors: Stefan Pleus, Andrea Tytko

• References

• 1 Akturk HK, Kahramangil D, Sarwal A. et al. Immune checkpoint inhibitorinduced Type 1 diabetes: a systematic review and meta-analysis. Diabet Med 2019; 36: 1075-1081
• 2 Chen X, Affinati AH, Lee Y. et al. Immune Checkpoint Inhibitors and Risk of Type 1 Diabetes. Diabetes Care 2022; 45: 1170-1176
• 3 The HAPO Study Cooperative Research Group. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med 2008; 358: 1991-2002
• 4 Gemeinsamer Bundesausschuss (G-BA). Im Internet: https://www.g-ba.de/themen/methodenbewertung/ambulant/frueherkennung-krankheiten/erwachsene/schwangerschaft-mutterschaft/
• 5 Deutsche Diabetes Gesellschaft und Deutsche Gesellschaft für Gynäkologie und Geburtshilfe. Hrsg. S3-Leitlinie Gestationsdiabetes mellitus (GDM), Diagnostik, Therapie und Nachsorge. AWMF-Registernummer: 057-008. 2018. Im Internet (Stand: 14.08.2019): 2. Auflage: https://www.awmf.org/uploads/tx_szleitlinien/057-008l_S3_Gestationsdiabetes-mellitus-GDM-Diagnostik-Therapie-Nachsorge_2019-06.pdf
• 6 Kleinwechter H. Gestational diabetes mellitus. update 2022. MMW Fortschr Med 2022; 164: 29-34
• 7 ElSayed NA, Aleppo G, Aroda VR. et al. 2. Classification and Diagnosis of Diabetes: Standards of Care in Diabetes-2023. Diabetes Care 2023; 46: S19-S40
• 8 World Health Organization. Definition and diagnosis of diabetes mellitus and intermediate hyperglycemia. 2006
• 9 International Diabetes Federation. IDF Diabetes Atlas 10th Edition. Im Internet: https://diabetesatlas.org/data/en/
• 10 Crowther CC, Samuel D, McCowan LME. et al. Lower versus Higher Glycemic Criteria for Diagnosis of Gestational Diabetes. N Engl J Med 2022; 387: 587-598
• 11 Pleus S, Heinemann L, Freckmann G. et al. Glukosemessung in der Diabetesdiagnostik und -therapie: Laboratoriumsmedizinische Untersuchung inkl. Patientennaher Sofortdiagnostik, Blutglukoseselbstmesung und kontinuierliches Glukosemonitoring. Diabetol Stoffwechs 2022; 17: 52-60
• 12 Freckmann G, Heinemann L, Pleus S. et al. Messqualität bei der Glukosemessung im Rahmen der Diabetesdiagnose und -therapie in Deutschland. Dtsch Med Wochenschr 2022; 147: 413-417
• 13 Richtlinie der Bundesärztekammer zur Qualitätssicherung laboratoriumsmedizinischer Untersuchungen. Deutsches Ärzteblatt 2023;
• 14 Fischer MM, Hannemann A, Winter T. et al. Relative Efficacy of Different Strategies for Inhibition of in Vitro Glycolysis. Clin Chem 2021; 67: 1032-1034
• 15 Heinemann L, Adamczewski H. Neumann Ch et al. Gemeinsames Positionspapier der Kommission Labordiagnostik in der Diabetologie der DDG und DGKL und der Kommission Apotheker in der Diabetologie BAK/DDG zur Herstellung einer oGTT-Lösung für die Diagnose eines Diabetes einschließlich eines Gestationsdiabetes. Diabetol Stoffwechs 2020; 15: 470-471
• 16 Krüger M, Heinemann L. Verfügbarkeit von Fertiglösungen für den oGTT: ein Update. Diabetes Stoffw. Herz 2023; 23: 90-91
• 17 Heil W, Jachtmann A, Rick W. Zur Reproduzierbarkeit der Ergebnisse des oralen Glucose-Toleranz-Tests. Lab Med 1990; 14: 440-444
• 18 Landgraf R. HbA1c in der Diabetes-Diagnostik. Der Goldstandard? Diabetes aktuell 2021; 19: 22-29
• 19 Heinemann L, Freckmann G. Quality of HbA1c Measurement in the Practice: The German Perspective. J Diabetes Sci Technol 2015; 9: 687-695
• 20 Heinemann L, Kaiser P, Freckmann G. et al. Higher HbA1c Measurement Quality Standards are Needed for Follow-Up and Diagnosis: Experience and Analyses from Germany. Horm Metab Res 2018; 50: 728-734
• 21 Richtlinie der Bundesärztekammer zur Qualitätssicherung laboratoriumsmedizinischer Untersuchungen. Deutsches Ärzteblatt 2019;
• 22 Pani LN, Korenda L, Meigs JB. et al. Effect of aging on A1C levels in individuals without diabetes: evidence from the Framingham Offspring Study and the National Health and Nutrition Examination Survey 2001-2004. Diabetes Care. 2008 31. 1991-1996
• 23 Merker L, Ebert T, Guthoff M. et al. Nephropathie bei Diabetes. Diabetol Stoffwechs 2022; 17: S327-S331
• 24 Baker L, Maley JH, Arévalo A. et al. Real-world characterization of blood glucose control and insulin use in the intensive care unit. Sci Rep 2020; 10: 10718
• 25 Pieri M, Paleari R, Dalfrá MG. et al. Reference intervals for HbA1c partitioned for gender and age: a multicenter study. Acta Diabetol 2016; 53: 1053-1056
• 26 Roth J, Müller N, Lehmann T. et al. HbA1c and Age in Non-Diabetic Subjects: An Ignored Association?. Exp Clin Endocrinol Diabetes 2016; 124: 637-642
• 27 Masuch A, Friedrich N, Roth J. et al. Preventing misdiagnosis of diabetes in the elderly: age-dependent HbA1c reference intervals derived from two population-based study cohorts. BMC Endocr Disord 2019; 19: 20
• 28 Ma Q, Liu H, Xiang G. et al. Association between glycated hemoglobin A1c levels with age and gender in Chinese adults with no prior diagnosis of diabetes mellitus. Biomed Rep 2016; 4: 737-740
• 29 Wu L, Lin H, Gao J. et al. Effect of age on the diagnostic efficiency of HbA1c for diabetes in a Chinese middle-aged and elderly population: The Shanghai Changfeng Study. PLoS One 2017; 12: e0184607
• 30 Qi J, Su Y, Song Q. et al. Reconsidering the HbA1c Cutoff for Diabetes Diagnosis Based on a Large Chinese Cohort. Exp Clin Endocrinol Diabetes 2021; 129: 86-92
• 31 Ozarda Y, Sikaris K, Streichert T. et al. Distinguishing reference intervals and clinical decision limits – A review by the IFCC Committee on Reference Intervals and Decision Limits. Crit Rev Clin Lab Sci 2018; 55: 420-431
• 32 The DECODE-study group on behalf of the European Diabetes Epidemiology Group. Is fasting glucose sufficient to define diabetes? Epidemiological data from 20 European studies. Diabetologia 1999; 42: 647-654
• 33 vanʼt Riet E, Alssema M, Rijkelijkhuizen JM. et al. Relationship between A1C and glucose levels in the general Dutch population: the new Hoorn study. Diabetes Care 2010; 33: 61-66
• 34 Peter A, Fritsche A, Stefan N. et al. Diagnostic value of hemoglobin A1c for type 2 diabetes mellitus in a population at risk. Exp Clin Endocrinol Diabetes 2011; 119: 234-237
• 35 Keutmann S, Zylla S, Dahl M. et al. Measurement Uncertainty Impacts Diagnosis of Diabetes Mellitus: Reliable Minimal Difference of Plasma Glucose Results. Diabetes Ther 2020; 11: 293-303
• 36 Taboulet P, Deconinck N, Thurel A. et al. Correlation between urine ketones (acetoacetate) and capillary blood ketones (3-beta-hydroxybutyrate) in hyperglycaemic patients. Diabetes Metab 2007; 33: 135-139
• 37 Glaser N, Fritsch M, Priyambada L. et al. ISPAD clinical practice consensus guidelines 2022: Diabetic ketoacidosis and hyperglycemic hyperosmolar state. Pediatr Diabetes 2022; 23: 835-856
• 38 Thaler M, Roos M, Petersmann A. et al. Auto-Antikörper-Diagnostik in der Diabetologie – Aktueller Stand der Analytik und klinische Anwendung in Deutschland. Diabetol Stoffwechs 2022; 17: 382-388
• 39 Ahlqvist E, Storm P, Käräjämäki A. et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol 2018; 6: 361-369
• 40 Wagner R, Heni M, Tabák AG. et al. Pathophysiology-based subphenotyping of individuals at elevated risk for type 2 diabetes. Nat Med 2021; 27: 49-57
• 41 Herder C, Roden M. A novel diabetes typology: towards precision diabetology from pathogenesis to treatment. Diabetologia 2022; 65: 1770-1781
• 42 Hörber S, Achenbach P, Schleicher E. et al. Harmonization of immunoassays for biomarkers in diabetes mellitus. Biotechnol Adv 2020; 39: 107359
• 43 Lampasona V, Pittman DL, William AJ. et al. Islet Autoantibody Standardization Program 2018 Workshop: Interlaboratory Comparison of Glutamic Acid Decarboxylase Autoantibody Assay Performance. Clin Chem 2019; 65: 1141-1152
• 44 Jones AG, Hattersley AT. The clinical utility of C-peptide measurement in the care of patients with diabetes. Diabet Med 2013; 30: 803-817
• 45 Fritsche A, Heni M, Peter A. et al. Considering Insulin Secretory Capacity as Measured by a Fasting C-Peptide/Glucose Ratio in Selecting Glucose-Lowering Medications. Exp Clin Endocrinol Diabetes 2022; 130: 200-204
• 46 Matthews DR, Hosker JP, Rudenski AS. et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28: 412-419
• 47 Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care 2004; 27: 1487-1495
• 48 Zavaroni I, Deferrari G, Lugari R. et al. Renal metabolism of C-peptide in man. J Clin Endocrinol Metab 1987; 65: 494-498
• 49 Bonser AM, Garcia-Webb P. C-peptide measurement: methods and clinical utility. Crit Rev Clin Lab Sci 1984; 19: 297-352
• 50 DʼElia JA, Mulla CH, Liu J. et al. Variations in glucose/C-peptide ratio in patients with type 2 diabetes associated with renal function. Diabetes Res Clin Pract 2019; 150: 1-7
• 51 Nationale Versorgungsleitlinie Typ-2-Diabetes. Teilpublikation der Langfassung Version 1. 2021. AWMF Register Nr. nvl-001. Im Internet: www.leitlinien.de/themen/diabetes
• 52 Holt RIG, DeVries JH, Hess-Fischl A. et al. The Management of Type 1 Diabetes in Adults. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care 2021; 44: 2589-2625
• 53 Besser REJ, Bell KJ, Couper JJ. et al. ISPAD clinical practice consensus guidelines 2022: Stages of type 1 diabetes in children and adolescents https://www.ispad.org/resource/resmgr/consensus_guidelines_2018_/guidelines2022/ch._2_pediatric_diabetes_-_2.pdf
• 54 Rewers M, Ludvigsson J. Environmental risk factors for type 1 diabetes. Lancet 2016; 387: 2340-2348
• 55 Ziegler AG, Rewers M, Simell O. et al. Seroconversion to multiple islet autoantibodies and risk of progression to diabetes in children. JAMA 2013; 309: 2473-2479
• 56 Sims EK, Besser REJ, Dayan C. et al. Screening for Type 1 Diabetes in the General Population: A Status Report and Perspective. Diabetes 2022; 71: 610-623
• 57 Buzzetti R, Zampetti S, Maddaloni E. Adult-onset autoimmune diabetes: current knowledge and implications for management. Nat Rev Endocrinol 2017; 13: 674-686
• 58 Leslie RD, Evans-Molina C, Freund-Brown J. et al. Adult-Onset Type 1 Diabetes: Current Understanding and Challenges. Diabetes Care 2021; 44: 2449-2456
• 59 Harding JL, Wander PL, Zhang X. et al. The Incidence of Adult-Onset Type 1 Diabetes: A Systematic Review From 32 Countries and Regions. Diabetes Care 2022; 45: 994-1006
• 60 Badenhoop K. MODY und andere monogenetische Diabetesformen. Diabetologe 2017; 13: 453-463
• 61 Bojunga J, Schlereth F. Type 3c diabetes mellitus-prevalence, diagnosis, special aspects of treatment. Diabetologe 2018; 14: 269-277
• 62 Kufeldt J, Kovarova M, Adolph M. et al. Prevalence and Distribution of Diabetes Mellitus in a Maximum Care Hospital: Urgent Need for HbA1c-Screening. Exp Clin Endocrinol Diabetes 2018; 126: 123-129
• 63 Ahuja V, Aronen P, Pramodkumar TA. et al. Accuracy of 1-hour plasma glucose during the oral glucose tolerance test in diagnosis of type 2 diabetes in adumts: A meta-analsis. Diabetes Care 2021; 44: 1062-1069
• 64 Zaharia OP, Strassburger K, Strom A. et al. Risk of diabetes-associated diseases in subgroups of patients with recent-onset diabetes: a 5-year follow-up study. Lancet Diabetes Endocrinol 2019; 7: 684-694
• 65 Achenbach P, Hippich M, Zapardiel-Gonzalo J. et al. A classification and regression tree analysis identifies subgroups of childhood type 1 diabetes. EBioMedicine 2022; 82: 104118
• 66 Broome DT, Pantalone KM, Kashyap SR. et al. Approach to the Patient with MODY-Monogenic Diabetes. J Clin Endocrinol Metab 2021; 106: 237-250

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Artikel online veröffentlicht:
20. Februar 2024