The co-existence of peripheral and vestibular neuropathy in diabetes: a cross-sectional study.

PURPOSE: Diabetic neuropathy can lead to decreased peripheral sensation and motor neuron dysfunction associated with impaired postural control and risk of falling. However, the relationship between decreased peripheral sensation and impaired vestibular function in diabetes mellitus is poorly investigated. Therefore, the aim of this study was to investigate the relationship between peripheral and autonomic measurements of diabetic neuropathy and measurements of vestibular function. METHODS: A total of 114 participants with type 1 diabetes (n = 52), type 2 diabetes (n = 51) and controls (n = 11) were included. Vestibular function was evaluated by video head impulse testing. Peripheral neuropathy was assessed by quantitative sensory testing and nerve conduction. Autonomic neuropathy using the COMPASS 31 questionnaire. Data were analyzed according to data type and distribution. RESULTS: Measurements of vestibular function did not differ between participants with type 1 diabetes, type 2 diabetes or controls (all p-values above 0.05). Subgrouping of participants according to the involvement of large-, small- or autonomic nerves did not change this outcome. Correlation analyses showed a significant difference between COMPASS 31 and right lateral gain value (ρ = 0.23, p = 0.02,), while no other significant correlations were found. CONCLUSION: Diabetic neuropathy does not appear to impair vestibular function in diabetes, by means of the VOR. CLINICAL TRIALS: NCT05389566, May 25th, 2022.

Fracture patterns in adult onset type 1 diabetes and associated risk factors - A nationwide cohort study.

OBJECTIVE: This study aimed to determine the hazard ratios (HR) for various fracture sites and identify associated risk factors in a cohort of relatively healthy adult people with newly diagnosed type 1 diabetes (T1D). METHODS: The study utilized data from the UK Clinical Practice Research Datalink GOLD (1987-2017). Participants included people aged 20 and above with a T1D diagnosis code (n = 3281) and a new prescription for insulin. Controls without diabetes were matched based on sex, year of birth, and practice. Cox regression analysis was conducted to estimate HRs for any fracture, major osteoporotic fractures (MOFs), and peripheral fractures (lower-arm and lower-leg) in people with T1D compared to controls. Risk factors for T1D were examined and included sex, age, diabetic complications, medication usage, Charlson comorbidity index (CCI), hypoglycemia, previous fractures, falls, and alcohol consumption. Furthermore, T1D was stratified by duration of disease and presence of microvascular complications. RESULTS: The proportion of any fracture was higher in T1D (10.8 %) than controls (7.3). Fully adjusted HRs for any fracture (HR: 1.43, CI95%: 1.17-1.74), MOFs (HR: 1.46, CI95%: 1.04-2.05), and lower-leg fractures (HR: 1.37, CI95%: 1.01-1.85) were statistically significantly increased in people with T1D compared to controls. The primary risk factor across all fracture sites in T1D was a previous fracture. Additional risk factors at different sites included previous falls (HR: 1.64, CI95%: 1.17-2.31), antidepressant use (HR: 1.34, CI95%: 1.02-1.76), and anxiolytic use (HR: 1.54, CI95%: 1.08-2.29) for any fracture; being female (HR: 1.65, CI95%: 1.14-2.38) for MOFs; the presence of retinopathy (HR: 1.47, CI95%: 1.02-2.11) and previous falls (HR: 2.04, CI95%: 1.16-3.59) for lower-arm and lower-leg fractures, respectively. Lipid-lowering medication use decreased the risk of MOFs (HR: 0.66, CI95%: 0.44-0.99). Stratification of T1D by disease duration showed that the relative risk of any fracture in T1D did not increase with longer diabetes duration (0-4 years: HR: 1.52, CI95%: 1.23-1.87; 5-9 years: HR: 1.30, CI95%: 0.99-1.71; <10 years: HR: 1.07, CI95%: 0.74-1.55). Similar patterns were observed for other fracture sites. Moreover, the occurrence of microvascular complications in T1D was linked to a heightened risk of fractures in comparison to controls. However, when considering the T1D cohort independently, the association was not statistically significant. CONCLUSION: In a cohort of relatively healthy and newly diagnosed people with T1D HRs for any fracture, MOFs, and lower-leg fractures compared to controls were increased. A previous fracture was the most consistent risk factor for a subsequent fracture, whereas retinopathy was the only diabetes related one. We postulate a potential initial fracture risk, succeeded by a subsequent risk reduction, which might potentially increase in later years due to the accumulation of complications and other factors.

Fracture patterns and associated risk factors in pediatric and early adulthood type 1 diabetes: Findings from a nationwide retrospective cohort study.

PURPOSE: People with pediatric and early adulthood type 1 diabetes (T1D) might have a higher fracture risk at several sites compared to the general population. Therefore, we assessed the hazard ratios (HR) of various fracture sites and determined the risk factors associated with fractures among people with newly diagnosed childhood and adolescence T1D. METHODS: All people from the UK Clinical Practice Research Datalink GOLD (1987-2017), below 20 years of age with a T1D diagnosis code (n = 3100) and a new insulin prescription, were included and matched 1:1 by sex, age, and practice to a control without diabetes. Cox regression was used to estimate HRs of any, major osteoporotic fractures (MOFs) and peripheral fractures (lower-arm and lower-legs) for people with T1D compared to controls. The analyses were adjusted for sex, age, diabetic complications, medication (glucocorticoids, anti-depressants, anxiolytics, bone medication, anti-convulsive), Charlson-comorbidity-index (CCI), hypoglycemia, falls and alcohol. T1D was further stratified by diabetes duration, presence of diabetic microvascular complications (retinopathy, nephropathy, and neuropathy) and boys versus girls. RESULTS: The crude HRs for any fracture (HR: 1.30, CI95%: 1.11-1.51), lower-arm (HR: 1.22, CI95%: 1.00-1.48), and lower-leg fractures (HR: 1.54, CI95%: 1.11-2.13) were statistically significant increase in T1D compared to controls, but the effect disappeared in the adjusted analyses. For MOFs, no significant differences were seen. Risk factors in the T1D cohort were few, but the most predominantly one was a previous fracture (any fracture: HR: 2.00, CI95%: 1.70-2.36; MOFs: HR: 1.89, CI95%: 1.44-2.48, lower- arm fractures: HR: 2.08, CI95%: 1.53-2.82 and lower-leg fractures: HR: 2.08, CI95%: 1.34-3.25). Others were a previous fall (any fracture: HR: 1.54, CI95%: 1.20-1.97), hypoglycemia (Any fracture: HR: 1.46, CI95%: 1.21-1.77 and lower-leg fractures: HR: 2.34, CI95%: 1.47-3.75), and anxiolytic medication (Any fracture: HR: 1.52, CI95%: 1.10-2.11). Whereas girls had a lower risk compared to boys (Any fracture: HR: 0.78, CI95%: 0.67-0.90 and lower-arm fractures; HR: 0.51, CI95%: 0.38-0.68). The risk of any fracture in T1D did not increase with longer diabetes duration compared to controls (0-4 years: HR: 1.20, CI95%: 1.00-1.44; 5-9 years: HR: 1.17, CI95%: 0.91-1.50; <10 years: HR: 0.83, CI95%: 0.54-1.27). Similar patterns were observed for other fracture sites. Furthermore, one complication compared to none in T1D correlated with a higher fracture risk (1 complication: HR: 1.42, CI95%: 1.04-1.95). CONCLUSION: The overall fracture risk was not increased in pediatric and early adulthood T1D; instead, it was associated with familiar risk factors and specific diabetes-related ones.

Effects of Incretin Therapy on Skeletal Health in Type 2 Diabetes-A Systematic Review.

Diabetes poses a significant risk to bone health, with Type 1 diabetes (T1D) having a more detrimental impact than Type 2 diabetes (T2D). The group of hormones known as incretins, which includes gastric inhibitory peptide (GIP) and glucagon-like peptide 1 (GLP-1), play a role in regulating bowel function and insulin secretion during feeding. GLP-1 receptor agonists (GLP-1 RAs) are emerging as the primary treatment choice in T2D, particularly when atherosclerotic cardiovascular disease is present. Dipeptidyl peptidase 4 inhibitors (DPP-4is), although less potent than GLP-1 RAs, can also be used. Additionally, GLP-1 RAs, either alone or in combination with GIP, may be employed to address overweight and obesity. Since feeding influences bone turnover, a relationship has been established between incretins and bone health. To explore this relationship, we conducted a systematic literature review following the PRISMA guidelines. While some studies on cells and animals have suggested positive effects of incretins on bone cells, turnover, and bone density, human studies have yielded either no or limited and conflicting results regarding their impact on bone mineral density (BMD) and fracture risk. The effect on fracture risk may vary depending on the choice of comparison drug and the duration of follow-up, which was often limited in several studies. Nevertheless, GLP-1 RAs may hold promise for people with T2D who have multiple fracture risk factors and poor metabolic control. Furthermore, a potential new area of interest is the use of GLP-1 RAs in fracture prevention among overweight and obese people. Based on this systematic review, existing evidence remains insufficient to support a positive or a superior effect on bone health to reduce fracture risk in people with T2D. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Bone parameters in T1D and T2D assessed by DXA and HR-pQCT - A cross-sectional study: The DIAFALL study.

INTRODUCTION/AIM: People with type 1 diabetes (T1D) and type 2 diabetes (T2D) have an increased risk of fractures due to skeletal fragility. We aimed to compare areal bone mineral density (aBMD), volumetric BMD (vBMD), cortical and trabecular measures, and bone strength parameters in participants with diabetes vs. controls. METHODS: In a cross-sectional study, we included adult participants with T1D (n = 111, MA = 52.9 years), T2D (n = 106, MA = 62.1 years) and controls (n = 328, MA = 57.7 years). The study comprised of DXA scans and HR-pQCT scans, biochemistry, handgrip strength (HGS), Timed Up and GO (TUG), vibration perception threshold (VPT), questionnaires, medical histories, alcohol use, and previous fractures. Group comparisons were performed after adjustment for sex, age, BMI, diabetes duration, HbA1c, alcohol, smoking, previous fractures, postmenopausal, HGS, TUG, and VPT. RESULTS: We found decreased aBMD in participants with T1D at the femoral neck (p = 0.028), whereas T2D had significantly higher aBMD at peripheral sites (legs, arms, p < 0.01) vs. controls. In T1D we found higher vBMD (p < 0.001), cortical vBMD (p < 0.001), cortical area (p = 0.002) and thickness (p < 0.001), lower cortical porosity(p = 0.008), higher stiffness (p = 0.002) and failure load (p = 0.003) at radius and higher vBMD (p = 0.003), cortical vBMD(p < 0.001), bone stiffness (p = 0.023) and failure load(p = 0.044) at the tibia than controls. In T2D we found higher vBMD (p < 0.001), cortical vBMD (p < 0.001), trabecular vBMD (p < 0.001), cortical area (p < 0.001) and thickness (p < 0.001), trabecular number (p = 0.024), lower separation (p = 0.010), higher stiffness (p < 0.001) and failure load (p < 0.001) at the radius and higher total vBMD (p < 0.001), cortical vBMD (p < 0.011), trabecular vBMD (p = 0.001), cortical area (p = 0.002) and thickness (p = 0.021), lower trabecular separation (p = 0.039), higher stiffness (p < 0.001) and failure load (p = 0.034) at tibia compared with controls. CONCLUSION: aBMD measures were as expected lower in T1D and higher in T2D than controls. Favorable bone microarchitecture and strength parameters were seen at the tibia and radius for T1D and T2D.

Impaired postural control in diabetes-a predictor of falls?

New evidence points toward that impaired postural control judged by center of pressure measures during quiet stance is a predictor of falls in people with type 1 and type 2 diabetes-even in occurrence of well-known risk factors for falls. INTRODUCTION/AIM: People with type 1 diabetes (T1D) and type 2 diabetes (T2D) are at risk of falling, but the association with impaired postural control is unclear. Therefore, the aim was to investigate postural control by measuring the center of pressure (CoP) during quiet standing and to estimate the prevalence ratio (PR) of falls and the fear of falling among people with diabetes compared to controls. METHODS: In a cross-sectional study, participants with T1D (n = 111) and T2D (n = 106) and controls without diabetes (n = 328) were included. Study procedures consisted of handgrip strength (HGS), vibration perception threshold (VPT), orthostatism, visual acuity, and postural control during quiet stance measured by CoPArea (degree of body sway) and CoPVelocity (speed of the body sway) with "eyes open," "eyes closed" in combination with executive function tasks. A history of previous falls and fear of falling was collected by a questionnaire. CoPArea and CoPVelocity measurements were analyzed by using a multiple linear regression model. The PR of falls and the fear of falling were estimated by a Poisson regression model. Age, sex, BMI, previous falls, alcohol use, drug, HGS, VPT, orthostatism, episodes of hypoglycemia, and visual acuity were covariates in multiple adjusted analyses. RESULTS: Significantly larger mean CoPArea measures were observed for participants with T1D (p = 0.022) and T2D (0.002), whereas mean CoPVelocity measures were only increased in participants with T2D (p = 0.027) vs. controls. Additionally, T1D and T2D participants had higher PRs for falls (p = 0.044, p = 0.014) and fear of falling (p = 0.006, p < 0.001) in the crude analyses, but the PRs reduced significantly when adjusted for mean CoPArea and mean CoPVelocity, respectively. Furthermore, multiple adjusted PRs were significantly higher than crude the analyses.    CONCLUSION: Impaired postural control during quiet stance was seen in T1D and T2D compared with controls even in the occurrence of well-known risk factors. and correlated well with a higher prevalence of falls.

The incidence of fractures at various sites in newly treated patients with type 2 diabetes mellitus.

Purpose: In this descriptive study, we examined the incidence of fractures in patients with newly treated type 2 diabetes mellitus (T2D) compared to matched reference population. Methods: Participants from the UK Clinical Practice research datalink (CPRD) GOLD (1987-2017), aged ≥30 years, with a T2D diagnosis code and a first prescription for a non-insulin anti-diabetic drug (n = 124,328) were included. Cases with T2D were matched by year of birth, sex and practice to a reference population (n = 124,328), the mean follow-up was 7.7 years. Crude fracture incidence rates (IRs) and incidence rate ratios (IRRs) were calculated. Analyses were stratified by fracture site and sex and additionally adjusted for BMI, smoking status, alcohol use and history of any fracture at index date. Results: The IR of all fractures and major osteoporotic fractures was lower in T2D compared to the reference population (IRR 0.97; 95%CI 0.94-0.99). The IRs were lower for clavicle (IRR 0.67; 0.56-0.80), radius/ulna (IRR 0.81; 0.75-0.86) and vertebral fractures (0.83; 0.75-0.92) and higher for ankle (IRR 1.16; 95%CI 1.06-1.28), foot (1.11; 1.01-1.22), tibia/fibula (1.17; 1.03-1.32) and humerus fractures (1.11; 1.03-1.20). Differences in IRs at various fracture sites between T2D and the reference population were more pronounced in women than in men. In contrast, BMI adjusted IRs for all fractures (IRR 1.07; 1.04-1.10) and most individual fracture sites were significantly higher in T2D, especially in women. Conclusion: The crude incidence of all fractures was marginally lower in patients with newly treated T2D compared to the matched reference population but differed according to fracture site, especially in women. BMI adjusted analyses resulted in higher incidence rates in T2D at almost all fracture sites compared to crude incidence rates and this was more pronounced in women than in men. This implies that BMI may have a protective impact on the crude incidence of fractures, especially in women with newly treated T2D.

Diabetes and osteoporosis - Treating two entities: A challenge or cause for concern?

People with T1D and T2D have an increased risk of fractures than the general population, posing several significant pathophysiologic, diagnostic, and therapeutic challenges. The pathophysiology is still not fully elucidated, but it is considered a combination of increased skeletal fragility and falls. Diagnostics issues exist, as regular and even newer scan methods underestimate the true incidence of osteoporosis and thus the fracture risk. Therefore, co-managing diabetes and osteoporosis by using top-line strategies is essential to preserve bone health and minimize the risk of falls. The therapeutic focus should start with lifestyle implementation and physical exercise interventions to reduce diabetic complications, strengthen bones, and improve postural control strategies. In addition, osteoporosis should be treated according to current guidelines by including bisphosphonates and antidiabetic drugs that support bone health. Finally, potentially modifiable risk factors for falls should be managed.

Is predicted body-composition and relative fat mass an alternative to body-mass index and waist circumference for disease risk estimation?

BACKGROUND AND AIMS: New methods to estimate body-composition have recently been proposed, but their relation to diseases, such as diabetes and coronary heart disease, needs further investigation. The purpose of this study was to investigate the association between proposed prediction of body-composition (PBC); Relative Fat Mass (RFM), Body Mass Index (BMI), Waist Circumference (WC) and disease. METHODS: In a cross-sectional cohort (NHANES) the association between the four body measures and diabetes, high blood pressure, coronary heart disease, cancer, arthritis, and hospitalization were assessed. A total of 13,348 people was included in this study. Receiver operating characteristic (ROC), Area Under Curve (AUC) and statistical testing were used to evaluate the differences. RESULTS: PBC/RFM had significant higher AUC than BMI or WC for diabetes, high blood pressure, hospitalization, and arthritis. PBC had a significant higher AUC than RFM, BMI, WC for Cancer and coronary heart disease. CONCLUSIONS: RFM and PBC could be a better indicator to distinguish amongst people with a risk of diseases compared to traditional measures such as BMI and WC. However, future studies need to investigate the longitudinal association between RFM, PBC and the risk of disease development to assess if these measures are better suited for risk-stratification.

Prevalent Morphometrically Assessed Vertebral Fractures in Individuals With Type 2 Diabetes, Prediabetes and Normal Glucose Metabolism: The Maastricht Study.

BACKGROUND: Type 2 diabetes (T2D) is frequently reported to be associated with an increased fracture risk. Epidemiological data on prevalent morphometric vertebral fractures (VFs) in T2D are sparse and even less is known in the prediabetic state. PURPOSE: To determine the association between prevalence and severity of morphometric VFs and glucose metabolism state: normal glucose metabolism (NGM), impaired glucose metabolism (prediabetes) or T2D. METHODS: This study included cross-sectional data from 3625 participants of the Maastricht Study who had a vertebral fracture assessment on lateral Dual Energy X-Ray Absorptiometry images. VFs were classified based on morphometric assessment into mild, moderate and severe VFs (respectively 20-24%, 25-39% or ≥40% reduction in expected vertebral body height). Logistic regression models were used to investigate the association between glucose metabolism status and the prevalence and severity of VFs. Analyses were adjusted for subject characteristics and life-style factors. RESULTS: T2D individuals were older (62.8 ± 7.5 years old) and less often female (30.5%) compared to the NGM group (57.7 ± 8.5 years old, and 58.8% female, respectively). At least one mild, moderate or severe prevalent VF was found in 8.6% of the men and 2.2% of the women in the T2D group, in 9.4% and 8.4% in the prediabetes group and in 9.1% and 4.8% in the NGM group, respectively. After adjustment T2D in women was associated with a lower probability of having a prevalent VF compared to NGM [adjusted OR 0.25 (95% CI 0.09-0.65)], while this was not the case for prediabetes. Furthermore, women with T2D had a significantly lower probability of a prevalent moderate or severe VF [adjusted OR 0.32 (95% CI 0.11-0.96)]. In men there was no significant association between T2D or prediabetes and prevalent VFs. CONCLUSION: Women with T2D had a lower probability of prevalent VFs compared to women with a normal glucose metabolism, while this was not the case for men with T2D and participants with prediabetes.

Fracture Patterns in Type 1 and Type 2 Diabetes Mellitus: A Narrative Review of Recent Literature.

PURPOSE OF REVIEW: In this narrative review, we have summarized the literature on fracture risk in T1DM and T2DM with a special focus on fracture site, time patterns, glucose-lowering drugs, and micro- and macrovascular complications. RECENT FINDINGS: T1DM and T2DM were associated with an overall increased fracture risk, with preferent locations at the hip, vertebrae, humerus, and ankle in T1DM and at the hip, vertebrae, and likely humerus, distal forearm, and foot in T2DM. Fracture risk was higher with longer diabetes duration and the presence of micro- and macrovascular complications. In T2DM, fracture risk was higher with use of insulin, sulfonylurea, and thiazolidinediones and lower with metformin use. The increased fracture risk in T1DM and T2DM concerns specific fracture sites, and is higher in subjects with longer diabetes duration, vascular complications, and in T2DM with the use of specific glucose-lowering medication.

Precise Prediction of Total Body Lean and Fat Mass From Anthropometric and Demographic Data: Development and Validation of Neural Network Models.

BACKGROUND: Estimating body composition is relevant in diabetes disease management, such as drug administration and risk assessment of morbidity/mortality. It is unclear how machine learning algorithms could improve easily obtainable body muscle and fat estimates. The objective was to develop and validate machine learning algorithms (neural networks) for precise prediction of body composition based on anthropometric and demographic data. METHODS: Cross-sectional cohort study of 18 430 adults and children from the US population. Participants were examined with whole-body dual X-ray absorptiometry (DXA) scans, anthropometric assessment, and answered a demographic questionnaire. The primary outcomes were predicted total lean body mass (predLBM), total body fat mass (predFM), and trunk fat mass (predTFM) compared with reference values from DXA scans. RESULTS: Participants were randomly partitioned into 70% training (12 901) data and 30% validation (5529) data. The prediction model for predLBM compared with lean body mass measured by DXA (DXALBM) had a Pearson's correlation coefficient of R = 0.99 with a standard error of estimate (SEE) = 1.88 kg (P < .001). The prediction model for predFM compared with fat mass measured by DXA (DXAFM) had a Pearson's coefficient of R = 0.98 with a SEE = 1.91 kg (P < .001). The prediction model for predTFM compared with DXA measured trunk fat mass (DXAFM) had a Pearson's coefficient of R = 0.98 with a SEE = 1.13 kg (P < .001). CONCLUSIONS: In this study, neural network models based on anthropometric and demographic data could precisely predict body muscle and fat composition. Precise body estimations are relevant in a broad range of clinical diabetes applications, prevention, and epidemiological research.

Increased Risk of Falls, Fall-related Injuries and Fractures in People with Type 1 and Type 2 Diabetes - A Nationwide Cohort Study.

INTRODUCTION: People with diabetes could have an increased risk of falls as they show more complications, morbidity and use of medication compared to the general population. This study aimed to estimate the risk of falls and to identify risk factors associated with falls in people with diabetes. The second aim was to estimate fall-related injuries, such as lesions and fractures, including their anatomic localization in people with diabetes compared with the general population. METHODS: From the Danish National Patient Register, we identified people with Type 1 Diabetes (T1D) (n=12,975) Type 2 Diabetes (T2D) (n=407,009). The cohort was divided into two groups, with respective control groups matched on age and sex (1:1). All episodes of people hospitalized with a first fall from 1996 to 2017 were analyzed using a Cox proportional-hazards model. Risk factors such as age, sex, diabetic complications, a history of alcohol abuse and the use of medication were included in an adjusted analysis. The incidence rate, incidence rate difference and incidence rate ratio (IRR) of falls and the anatomic localization of fall-related injuries as lesions and fractures were identified. RESULTS AND DISCUSSION: The cumulative incidence, of falls requiring hospital treatment, was 13.3% in T1D, 11.9% in T2D. In the adjusted analysis, T1D and T2D were associated with a higher risk of falls [T1D, Hazard Ratio (HR): 1.33 (95% CI: 1.25 - 1.43), T2D, HR: 1.19 (95% CI:1.16 - 1.22), respectively]. Women [group 1, HR 1.21 (CI:95%:1.13 - 1.29), group 2, HR 1.61 (CI:95%:1.58-1.64)], aged >65 years [groups 1, HR 1.52 (CI:95%:1.39 - 1.61), group 2, HR 1.32 (CI:95%:1.58-1.64)], use of selective serotonin receptor inhibitors (SSRI) [group 1, HR 1.35 (CI:95%:1.1.30 - 1.40), group 2, HR 1.32 (CI:95%:1.27-1.38)], opioids [group 1, HR 1.15 (CI:95%:1.12 - 1.19), group 2, HR 1.09 (CI:95%:1.05-1.12)] and a history of alcohol abuse [group 1, HR 1.77 (CI:95%:1.17 - 2.15), group 2, HR 1.88 (CI:95%:1.65-2.15)] were significantly associated with an increased risk of falls in both groups. The IRR of fall-related injuries as hip, radius, humerus and skull/facial fractures were higher in people with T2D than controls [IRR 1.02 (CI:95%:1.01-1.04), IRR 1.39 (CI:95%: 1.18-1.61), IRR 1.24 (CI:95%: 1.12-1.37) and IRR 1.15 (CI:95%:1.07-1.24)]. People with T1D had a higher IRR of hip fractures than controls [IRR: 1.11 (CI:95%:1.02 - 1.23)]. CONCLUSION: People with diabetes have an increased risk of first fall and a higher incidence of fall- related injuries, including fractures. Advanced aging and sex are non-modifiable risk factors, whereas diabetes, the use of SSRIs and opioids and alcohol abuse could be potentially modifiable risk factors for falls. Gaining information on risk factors for falls could guide the management of diabetes treatment, i.e., choice of drugs, which enables us to improve treatment, particularly in people with a high risk of falls and fractures associated with high mortality.

Falls and Fractures in Diabetes-More than Bone Fragility.

PURPOSE OF REVIEW: Based on a systematic literature search, we performed a comprehensive review of risk factors for falls and fractures in patients with diabetes. RECENT FINDINGS: Patients with diabetes have an increased risk of fractures partly explained by increased bone fragility. Several risk factors as altered body composition including sarcopenia and obesity, impaired postural control, gait deficits, neuropathy, cardiovascular disease, and other co-morbidities are considered to increase the risk of falling. Diabetes and bone fragility is well studied, but new thresholds for fracture assessment should be considered. In general, the risk factors for falls in patients with diabetes are well documented in several studies. However, the fall mechanisms among diabetic patients have only been assessed in few studies. Thus, a gab of knowledge exits and may influence the current understanding and treatment, in order to reduce the risk of falling and thereby prevent fractures.

Validity of diagnostic coding for undernutrition in hospitals.

BACKGROUND & AIMS: We examined the accuracy of ICD-10 diagnostic coding for undernutrition in Danish Hospitals, including the use of Nutritional Risk Screening 2002 guidelines. METHODS: We investigated a random sample of hospitalized patients registered in the Danish National Registry of Patients with a discharge diagnosis of undernutrition between 2002 and 2011 in the North Denmark Region. Based on medical record review we estimated the positive predictive value (PPV) of the undernutrition diagnosis. Stratification was made by calendar period, hospital type (local vs. university), gender, age, speciality and type of diagnosis code. Subsequently, we evaluated the use of Nutritional Risk Screening 2002 as recommended by the European Society of Clinical Nutrition and Metabolism and the Danish National Board of Health. RESULTS: We could retrieve the medical records of 172/200 sampled patients with undernutrition (86%). Nineteen patients were classified as being definite (screening-confirmed) cases and another 103 patients as probable (clinically-confirmed) cases of undernutrition, yielding a PPV of 11.0% (95% confidence interval [CI]: 6.8-16.7) for definite undernutrition and 70.9% (95% CI: 63.5-77.6) for any confirmed undernutrition. Only 26.2% of patients coded with undernutrition had been screened according to the Nutritional Risk Screening 2002. CONCLUSIONS: This population-based study found modest agreement between ICD-10 codes for undernutrition compared to a standard method (Nutritional Risk Screening 2002) as documented in medical doctors' records in Danish hospitals. Diagnoses of undernutrition contained in hospital discharge registries should be used with caution.