Real-world evaluation of vascular complications and comorbidities in Portuguese patients with type 2 diabetes: Results from the cMORE study.

Type 2 diabetes poses a significant health challenge in Portugal, increasing the susceptibility to complications/comorbidities such as hypertension, obesity, and cardiovascular (CV) disease. This study aimed to evaluate the prevalence of type 2 diabetes-related vascular complications/comorbidities and their pharmacological management in Portugal. cMORE was a non-interventional, cross-sectional, multicenter study conducted in 32 Portuguese primary healthcare units between October 2020 and 2022. Secondary data, including sociodemographic, anthropometric, clinical information, cardiometabolic comorbidities, HbA1c levels, lipid parameters and medication, were collected from electronic medical records. Seven hundred and eighty adult patients with type 2 diabetes were included, predominantly male (55.5%), with an average age of 67.7 years and a mean disease duration of 10.5 years. Family history of type 2 diabetes (43.1%) and CV disease (32.1%) was prevalent. Mean HbA1c was 7.0%, progressively increasing with disease duration (p<0.001). Microvascular and macrovascular complications occurred in 38.1% and 19.6% of patients, respectively. The most prevalent comorbidities included overweight/obesity (85.5%), dyslipidemia (85.4%), and hypertension (82.6%). Multimorbidity burden was significant (99.3%) and positively correlated with older age, larger waist circumference, and overweight/obesity. Longer type 2 diabetes duration was associated with higher odds of diabetic retinopathy and CV disease/procedures, while dyslipidemia and hypertension were linked with older age, regardless of disease duration. Most patients received oral antidiabetic medications (94.6%), primarily biguanides (92.4%), followed by DPP-4 (39.1%) and SGLT2 inhibitors (34.2%). The cMORE study reveals a substantial burden of vascular complications/comorbidities among Portuguese patients with type 2 diabetes. Despite the high multimorbidity rates, effective type 2 diabetes management is observed, emphasizing the country's commitment to personalized care.

Alão S ，Silva T ，Leite AP ，do Rosário M ，Carvalho C ，Coelho J ，Ferreira H ，Ferreira R ，Abreu J ，Rosa M ，Azevedo S ，Cunha C ，Daniel C ，Juane B ，Sousa RA ，Casais AC ，cMORE study group ... -  《-》

A comparison of comorbidities and their risk factors prevalence across rheumatoid arthritis, psoriatic arthritis and axial spondyloarthritis with focus on cardiovascular diseases: data from a single center real-world cohort.

Management of comorbidities is essential to a patient-centered approach to the treatment of chronic inflammatory arthritis. The aim of this study was to compare the prevalence of comorbidities and their risk factors in rheumatoid arthritis (RA), psoriatic arthritis (PsA), and axial spondyloarthritis (axSpA) in a single center outpatient cohort. This cross-sectional study included adult patients diagnosed with RA, PsA, and axSpA from a single rheumatology outpatient center. Comorbidities were documented by physicians, and patients were categorized into two age groups, younger (< 45 years) and older (≥ 45 years), with age- and gender-based comparisons. Disease activity, comorbidities, and cardiovascular (CV) risk factors were analyzed using chi-squared tests for categorical variables and independent samples t-tests for continuous variables, with p values < 0.05 considered statistically significant. Comorbidities were registered by physicians using GoTreatIt® Rheuma software. Among 508 RA, 267 PsA, and 285 axSpA patients, the four most common comorbidities were hypertension (36.4%, 25.1%, and 19.7%, respectively), dyslipidemia (19.5%, 15.4%, 14.7% respectively), obesity (16.9%, 22.5%, 14% respectively) and thyroid disease (21.5%, 13.9%, 11.2% respectively). Other comorbidities differed among the diseases and included osteoporosis, osteoarthritis, diabetes mellitus, arrhythmia, and asthma in RA, diabetes mellitus, depression and asthma in PsA, osteoporosis and serious infection in axSpA. RA patients, compared to axSpA had a higher prevalence of coronary artery disease (4.1% vs. 0.7%, p = 0.006), arrhythmia (6.9% vs. 2.5%, p = 0.008) and major adverse cardiac events (2.6% vs. 0.4%, p = 0.024) compared to axSpA. Osteoporosis was more frequent in RA (19.1%) and axSpA (8.4%) than in PsA (2.3%; p < 0.001) and was frequently diagnosed in patients aged < 45. Depression prevalence was surprisingly low (1.6%, 5.2%, and 1.8%, respectively). RA patients had the highest multimorbidity rate, with 26.6% reporting three or more comorbidities, compared to 16.8% in PsA and 10.6% in axSpA (p < 0.001). Health status was poorest in RA and worse in women compared to men for all diseases. RA, PsA, and axSpA share the same four most common comorbidities: hypertension, dyslipidemia, obesity, and thyroid disease but have different prevalence of other disorders and CV risk factors, indicating the need for an individual screening and prevention approach. The possible unrecognition of depression should be evaluated.

Guła Z ，Łosińska K ，Kuszmiersz P ，Strach M ，Nowakowski J ，Biedroń G ，Zimba O ，Dyczek Ł ，Haugeberg G ，Korkosz M ... -  《-》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. Level III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》

Identifying and visualising multimorbidity and comorbidity patterns in patients in the English National Health Service: a population-based study.

Globally, there is a paucity of multimorbidity and comorbidity data, especially for minority ethnic groups and younger people. We estimated the frequency of common disease combinations and identified non-random disease associations for all ages in a multiethnic population. In this population-based study, we examined multimorbidity and comorbidity patterns stratified by ethnicity or race, sex, and age for 308 health conditions using electronic health records from individuals included on the Clinical Practice Research Datalink linked with the Hospital Episode Statistics admitted patient care dataset in England. We included individuals who were older than 1 year and who had been registered for at least 1 year in a participating general practice during the study period (between April 1, 2010, and March 31, 2015). We identified the most common combinations of conditions and comorbidities for index conditions. We defined comorbidity as the accumulation of additional conditions to an index condition over an individual's lifetime. We used network analysis to identify conditions that co-occurred more often than expected by chance. We developed online interactive tools to explore multimorbidity and comorbidity patterns overall and by subgroup based on ethnicity, sex, and age. We collected data for 3 872 451 eligible patients, of whom 1 955 700 (50·5%) were women and girls, 1 916 751 (49·5%) were men and boys, 2 666 234 (68·9%) were White, 155 435 (4·0%) were south Asian, and 98 815 (2·6%) were Black. We found that a higher proportion of boys aged 1-9 years (132 506 [47·8%] of 277 158) had two or more diagnosed conditions than did girls in the same age group (106 982 [40·3%] of 265 179), but more women and girls were diagnosed with multimorbidity than were boys aged 10 years and older and men (1 361 232 [80·5%] of 1 690 521 vs 1 161 308 [70·8%] of 1 639 593). White individuals (2 097 536 [78·7%] of 2 666 234) were more likely to be diagnosed with two or more conditions than were Black (59 339 [60·1%] of 98 815) or south Asian individuals (93 617 [60·2%] of 155 435). Depression commonly co-occurred with anxiety, migraine, obesity, atopic conditions, deafness, soft-tissue disorders, and gastrointestinal disorders across all subgroups. Heart failure often co-occurred with hypertension, atrial fibrillation, osteoarthritis, stable angina, myocardial infarction, chronic kidney disease, type 2 diabetes, and chronic obstructive pulmonary disease. Spinal fractures were most strongly non-randomly associated with malignancy in Black individuals, but with osteoporosis in White individuals. Hypertension was most strongly associated with kidney disorders in those aged 20-29 years, but with dyslipidaemia, obesity, and type 2 diabetes in individuals aged 40 years and older. Breast cancer was associated with different comorbidities in individuals from different ethnic groups. Asthma was associated with different comorbidities between males and females. Bipolar disorder was associated with different comorbidities in younger age groups compared with older age groups. Our findings and interactive online tools are a resource for: patients and their clinicians, to prevent and detect comorbid conditions; research funders and policy makers, to redesign service provision, training priorities, and guideline development; and biomedical researchers and manufacturers of medicines, to provide leads for research into common or sequential pathways of disease and inform the design of clinical trials. UK Research and Innovation, Medical Research Council, National Institute for Health and Care Research, Department of Health and Social Care, Wellcome Trust, British Heart Foundation, and The Alan Turing Institute.

Kuan V ，Denaxas S ，Patalay P ，Nitsch D ，Mathur R ，Gonzalez-Izquierdo A ，Sofat R ，Partridge L ，Roberts A ，Wong ICK ，Hingorani M ，Chaturvedi N ，Hemingway H ，Hingorani AD ，Multimorbidity Mechanism and Therapeutic Research Collaborative (MMTRC) ... -  《The Lancet Digital Health》

Metabolic health in people living with type 1 diabetes in Belgium: a repeated cross-sectional study.

Lavens A ，De Block C ，Oriot P ，Crenier L ，Philips JC ，Vandenbroucke M ，Vanherwegen AS ，Nobels F ，Mathieu C ，IQED Group of Experts ... -  《-》