Structured diabetes care routines in cardiac rehabilitation are associated with increased diabetes detection and improved treatment after myocardial infarction: a nationwide observational study
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Abstract Background Despite the detrimental impact of abnormal glucose metabolism on cardiovascular prognosis after myocardial infarction (MI), diabetes is both underdiagnosed and undertreated. We aimed to investigate associations between structured diabetes care routines in cardiac rehabilitation (CR) and detection and treatment of diabetes at one-year post-MI. Methods Center-level data was derived from the Perfect-CR survey, which evaluated work routines applied at Swedish CR centers (n = 76). Work routines involving diabetes care included: 1) routine assessment of fasting glucose and/or HbA1c, 2) routine use of oral glucose tolerance test (OGTT), 3) having regular case rounds with diabetologists, and 4) whether glucose-lowering medication was adjusted by CR physicians. Patient-level data was obtained from the national MI registry SWEDEHEART (n = 7601, 76% male, mean age 62.6 years) and included all post-MI patients irrespective of diabetes diagnosis. Using mixed-effects regression we estimated differences between patients exposed vs. not exposed to the four above-mentioned diabetes care routines. Outcomes were diabetes incidence and the proportion of patients receiving oral glucose-lowering medication at one-year post-MI. Results Routine assessment of fasting glucose/HbA1c was performed at 63.2% (n = 48) of the centers, while 38.2% (n = 29) reported using OGTT for detecting glucose abnormalities. Glucose-lowering medication adjusted by CR physicians (n = 13, 17.1%) or regular case rounds with diabetologists (n = 7, 9.2%) were less frequently reported. In total, 4.0% of all patients (n = 304) were diagnosed with diabetes during follow-up and 17.9% (n = 1361) were on oral glucose-lowering treatment one-year post-MI. Routine use of OGTT was associated with higher diabetes incidence at one-year (adjusted incidence change 2.00%, risk ratio [95% confidence interval]: 1.62 [1.26, 1.98], p = 0.0007). At one-year a higher proportion of patients were receiving oral glucose-lowering medication at centers routinely using OGTT (1.22 [1.07, 1.37], p = 0.0046) and where such medication was adjusted by CR physicians (1.31 [1.06, 1.56], p = 0.0155). Compared to having none of the structured diabetes care routines, the more routines implemented the higher the diabetes incidence (from 0 routines: 2.7% to 4 routines: 6.3%; p for trend = 0.0014). Conclusions Having structured routines for diabetes care implemented within CR can improve detection and treatment of diabetes post-MI. A cluster-randomized trial is warranted to ascertain causality.
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Structured diabetes care routines in cardiac rehabilitation are associated with increased diabetes detection and improved treatment after myocardial infarction: a nationwide observational study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Structured diabetes care routines in cardiac rehabilitation are associated with increased diabetes detection and improved treatment after myocardial infarction: a nationwide observational study Bashaaer Sharad, Nils Eckerdal, Martin Magnusson, Halldora Ögmundsdottir Michelsen, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4554688/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Sep, 2024 Read the published version in Cardiovascular Diabetology → Version 1 posted 9 You are reading this latest preprint version Abstract Background Despite the detrimental impact of abnormal glucose metabolism on cardiovascular prognosis after myocardial infarction (MI), diabetes is both underdiagnosed and undertreated. We aimed to investigate associations between structured diabetes care routines in cardiac rehabilitation (CR) and detection and treatment of diabetes at one-year post-MI. Methods Center-level data was derived from the Perfect-CR survey, which evaluated work routines applied at Swedish CR centers (n = 76). Work routines involving diabetes care included: 1) routine assessment of fasting glucose and/or HbA1c, 2) routine use of oral glucose tolerance test (OGTT), 3) having regular case rounds with diabetologists, and 4) whether glucose-lowering medication was adjusted by CR physicians. Patient-level data was obtained from the national MI registry SWEDEHEART (n = 7601, 76% male, mean age 62.6 years) and included all post-MI patients irrespective of diabetes diagnosis. Using mixed-effects regression we estimated differences between patients exposed vs. not exposed to the four above-mentioned diabetes care routines. Outcomes were diabetes incidence and the proportion of patients receiving oral glucose-lowering medication at one-year post-MI. Results Routine assessment of fasting glucose/HbA1c was performed at 63.2% (n = 48) of the centers, while 38.2% (n = 29) reported using OGTT for detecting glucose abnormalities. Glucose-lowering medication adjusted by CR physicians (n = 13, 17.1%) or regular case rounds with diabetologists (n = 7, 9.2%) were less frequently reported. In total, 4.0% of all patients (n = 304) were diagnosed with diabetes during follow-up and 17.9% (n = 1361) were on oral glucose-lowering treatment one-year post-MI. Routine use of OGTT was associated with higher diabetes incidence at one-year (adjusted incidence change 2.00%, risk ratio [95% confidence interval]: 1.62 [1.26, 1.98], p = 0.0007). At one-year a higher proportion of patients were receiving oral glucose-lowering medication at centers routinely using OGTT (1.22 [1.07, 1.37], p = 0.0046) and where such medication was adjusted by CR physicians (1.31 [1.06, 1.56], p = 0.0155). Compared to having none of the structured diabetes care routines, the more routines implemented the higher the diabetes incidence (from 0 routines: 2.7% to 4 routines: 6.3%; p for trend = 0.0014). Conclusions Having structured routines for diabetes care implemented within CR can improve detection and treatment of diabetes post-MI. A cluster-randomized trial is warranted to ascertain causality. cardiac rehabilitation myocardial infarction diabetes secondary prevention Figures Figure 1 Background Abnormal glucose metabolism is common in patients with ischemic heart disease, and is associated with a considerably higher risk of mortality and recurrent cardiovascular events ( 1 ). The reported prevalence of diabetes mellitus in patients with myocardial infarction (MI) is 20–25% ( 2 – 4 ). Further two-thirds of patients with MI without known diabetes have undiagnosed diabetes or pre-diabetes (impaired fasting glucose or impaired glucose tolerance) diagnosed by fasting glucose, hemoglobin A1c (HbA1c) or with an oral glucose tolerance test (OGTT) ( 5 ). Both patients with diabetes and those with pre-diabetes have a worse prognosis than patients with normal glucose metabolism ( 6 , 7 ). Despite improvements in diagnostic methods, a considerable proportion of MI patients with diabetes and pre-diabetes remain undiagnosed and are therefore untreated ( 5 , 8 ). In recent years, new treatments (e.g., glucagon-like peptide-1 receptor agonists [GLP-1RA] and sodium-glucose cotransporter-2 [SGLT-2] inhibitors provide additional prognostic benefit beyond optimal metabolic and risk factor control ( 9 ). Given this background, there is a need to improve screening for, and treatment of, abnormal glucose metabolism in patients with MI to improve long-term prognosis. According to international guidelines on diabetes and cardiovascular disease, fasting glucose and HbA1c should be routinely measured in all patients with MI to confirm or exclude a diabetes diagnosis ( 5 , 10 ). An OGTT may be considered in cases where a diabetes diagnosis is still unclear ( 5 ). If abnormal glucose metabolism is identified, management of risk factors including lifestyle modification, adequate secondary preventive treatment and glycemic control should be applied to decrease the risk for recurrent cardiovascular events ( 5 , 10 ). Despite guideline recommendations, follow-up at many cardiac rehabilitation (CR) centers for post-MI patients does not routinely include assessment of glucose metabolism ( 2 – 4 ). Also, pharmaceutical treatment and lifestyle modifications in patients with concomitant MI and diabetes are insufficient ( 11 ). In Sweden, CR for post-MI patients is well integrated into routine healthcare and holds a high international standard ( 4 , 12 – 14 ). However, there is considerable variation in both target attainment and the work routines applied at Swedish CR centers to reach treatment targets for risk factors ( 4 , 12 ). It is unknown to which extent structured routines for diabetes care are integrated into CR in Sweden, and whether having such routines implemented within CR improves detection and treatment of glucometabolic abnormalities for post-MI patients. The main purpose of this study was to 1) describe how screening and management of glucometabolic abnormalities is organized at CR centers in Sweden and 2) explore associations between work routines for management of glucometabolic abnormalities at center-level and diabetes incidence and treatment at patient-level at one-year post-MI. Methods Study design This was an observational survey- and registry-based cohort study. Data collection Three databases were used in this study: the Perfect-CR study, the national MI registry SWEDEHEART ( 4 ) and The Statistics Sweden registry ( 15 ). The Perfect-CR study was a survey-based study which evaluated the work routines followed at CR centers in Sweden in 2016 ( 12 ). All 78 centers actively following post-MI patients in Sweden at the time completed the survey and missing data was minimal (< 3%). Details of the study procedure have previously been published ( 12 ). In the current study we focused on the part of the survey exploring work routines pertaining to diabetes management during CR. These included four work routines, defined as the study exposures: 1) routine assessment of fasting glucose and/or HbA1c values by a nurse at the start of the CR program (laboratory measures performed at index MI hospitalization or prior to CR start), 2) routine use of OGTT during follow-up, 3) having regular joint case rounds with diabetologists, and 4) initiation and/or adjustment of glucose-lowering medication by the CR center’s physicians. The use of OGTT could be performed in all patients without known diabetes or on a selection of patients (high normal HbA1c/fasting glucose). Out of the 78 CR centers participating in Perfect-CR, two centers had no follow-up data and were excluded from further analysis. Patient baseline and outcome data were extracted from the SWEDEHEART and Statistics Sweden registries. SWEDEHEART is a nationwide registry for cardiac disease. The registry includes patient data from all hospitals in Sweden that treat and follow up patients with acute MI. Data on acute care is collected at coronary care units and follow-up data is collected at CR centers at 2-months and one-year post-MI ( 16 , 17 ). All coronary care units and CR centers in the country report to SWEDEHEART. The registry data includes information on comorbidities, previous medical history and medications, laboratory analyses, risk factors, psychosocial- and lifestyle variables, and readmissions ( 4 ). Patient inclusion is shown in Figure S1 . Inclusion criteria were: 1) discharged alive after hospitalization for type-1 MI, 2) age 18–74 years, and 3) attending CR in the year preceding administration of the Perfect-CR survey. The timeframe was chosen to match the time in which patients attended CR with the time reflected in the Perfect-CR survey answers. There were no exclusion criteria. Prevalent and incident diabetes (type 1 or 2) in SWEDEHEART is defined as a diagnosis in medical records and/or by the patient being prescribed glucose-lowering medication. A diagnosis of pre-diabetes is not registered in SWEDEHEART. At the time of the study, variables reflecting diabetes treatment were "Treatment with insulin (yes/no)” and “Treatment with other oral glucose-lowering medications (yes/no)”. Further classification of glucose-lowering medication was not registered at the time in SWEDEHEART and injection therapy other than insulin was uncommon ( 18 ). Statistics Sweden is the Swedish government agency responsible for producing official statistics including data from Swedish health care units ( 15 ). Data from Statistics Sweden used in this study included baseline data on socioeconomic status including country of birth, disposable household income, marital status, occupational status, and level of education ( 15 ). Center-level data were merged with patient-level data by linking each patient to the specific CR center where the patient underwent their follow-up ( 19 ). The final dataset used in the current study included all patients (n = 7601) discharged with an MI diagnosis (ICD-10 codes I21) between Nov 2015 and Oct 2016 and subsequently followed at the 76 included CR centers. Outcome definition The outcomes were 1) diabetes incidence and 2) the proportion of patients receiving glucose lowering treatment other than insulin at a one-year follow-up visit registered in SWEDEHEART. If one-year data was missing, data from the 2-month follow-up visit was used. Only diabetes was included in the incidence outcome as pre-diabetes is not registered in SWEDEHEART. Also, as it is uncommon for CR physicians to initiate or adjust insulin, we only included treatment with oral glucose-lowering medication in the treatment outcome. All patients irrespective of diabetes diagnosis were included in the diabetes treatment outcome analysis to ascertain inclusion of patients with pre-diabetes, that might be treated with oral glucose-lowering medication (mostly metformin) ( 20 ). Statistical analysis Baseline data are reported in frequencies (%), medians and interquartile ranges (Q1, Q3), means and standard deviations (SD) as appropriate. Exposures were modelled in three different ways: i) having two to four routines implemented defined as exposure versus having no or one routine implemented defined as reference; ii) each working routine defined as a separate exposure with not having that routine implemented defined as the reference; and iii) the number of implemented routines from zero to four, with zero being the reference. The association between the exposures and the outcomes were estimated as incidence changes (risk differences) and incidence ratios (risk ratios). Both measures were based on a mixed-effects linear model, with random intercepts for each CR center. The risk ratio was estimated as the sum of the crude control-group incidence and the risk difference, divided by the control-group incidence. The variance of the risk ratio estimate was calculated using the delta method. Patient- and center-level covariates included in the models were selected based on clinical expertise and predictors identified as meaningful for the attainment of lipid- and blood pressure treatment targets as identified in a previous publication from the Perfect-CR study ( 19 ). Selected covariates are portrayed in a Directed Acyclic Graph (DAG) in Figure S2 . To handle missing data and avoid biasing of estimates from using only complete cases, multiple imputation was implemented. With the overall rate of missingness among covariates being only 1.3%, simple hot deck imputation was used. Missing values on individual-level covariates were replaced by the value of a randomly selected individual from the same CR center. Missing values on CR center-level covariates were replaced by the value of a randomly selected CR center. 30 imputed data sets were created, and the results were combined using Rubin’s rules. ( 21 ). Statistical significance was set to p < 0.05. Data was analyzed using IBM SPSS (version 27, Chicago, Illinois, USA) and R version 4.2.2. Results Center-level baseline characteristics Out of the 76 CR centers participating in Perfect-CR where follow-up data on patient-level was available, nine centers (11.8%) were based at university hospitals. The median number of patients eligible for follow-up per center in 2016 was 101 (68, 164). Fasting glucose and/or HbA1c were routinely evaluated at CR program initiation at 63.2% (n = 48) of the CR centers, while 38.2% (n = 29) of the centers reported routinely performing OGTT. At 17.1% (n = 13) of the CR centers the physicians independently initiated and/or adjusted glucose-lowering medication and 9.2% (n = 7) reported having regular joint case rounds with diabetologists. Most centers had none (23.7%, n = 18) or one (36.8%, n = 28) of the work routines for structured diabetes care in place, while 39.4% (n = 30) of the CR centers reported having two or more routines implemented. Only 2.6% (n = 2) of the centers reported having all four work routines implemented. Further details can be seen in Table 1 . Table 1 Diabetes care work routines applied at cardiac rehabilitation centers in Sweden as surveyed in the Perfect-CR survey. Questionnaire item N (%) CR centers 76 Fasting glucose and/or HbA1c levels are routinely evaluated at the start of the CR program 48 (63.2) Use of OGTT* OGTT is performed on all patients 7 (9.2) OGTT is performed on a selection of patients 22 (28.9) We do not perform OGTT on our patients post-MI 46 (60.5) Unknown 1 (1.3) Glucose-lowering medication is initiated and/or adjusted by the CR center physicians 13 (17.1) Regular joint case rounds with diabetologists at the CR center 7 (9.2) *In patients without previous diabetes diagnosis. HbA1c: hemoglobin A1c; CR: cardiac rehabilitation; OGTT: oral glucose tolerance test; MI: myocardial infarction. Patient-level baseline characteristics In total, 7601 patients followed at the 76 CR centers were included. Mean age of the patients was 62.6 ± 8.7 years and 76% were male. The proportion of patients with previously known or newly detected diabetes during hospitalization was 22.5% (n = 1710), out of which 80.8% were treated with any glucose-lowering agent (oral or injection) at discharge. Diabetes prevalence at one-year follow-up was 26.5% (n = 2013) with 86.3% of the patients being treated with any glucose-lowering agent. Further patient-level baseline characteristics are shown in Table 2 . Table 2 Baseline characteristics at patient-level. Total sample 0–1 routines followed 2–4 routines followed P-value Missing, n (%) 7601 (100.0) 4947 (65.0) 2654 (35.0) Demographics Male, n (%) 5744 (76.0) 3770 (76.2) 2004 (75.5) 0.50 0 (0) Age, years 62.6 ± 8.7 62.7 + 8.7 62.5 + 8.6 0.86 0 (0) Risk factors and previous disease Prevalent diabetes, n (%) 1522 (20.0) 1005 (20.3) 517 (19.5) 0.09 18 (0.2) Active smoker, n (%) 2119 (27.9) 1331 (27.0) 788 (30.0) 0.003 186 (2.4) Chronic heart failure, n (%) 364 (4.8) 217 (4.3) 147 (5.5) < 0.001 184 (2.4) Hypertension, n (%) 3576 (47.0) 2340 (47.3) 1236 (47.0) 0.80 34 (0.4) Prior myocardial infarction, n (%) 1426 (18.8) 876 (17.7) 550 (20.7) 0.006 27 (0.4) Physiological and laboratory measures at baseline Fasting plasma glucose, mmol/L 8.0 (3.5) 8.0 (3.5) 8.1 ± 3.5 0.16 724 (9.5) HbA1c, mmol/mol 44.0 (14.2) 43.9 (14.4) 44.1 ± 13.9 0.50 5406 (71.1) Type of myocardial infarction STEMI, n (%) 2966 (39.0) 1093 (22.1) 1063 (40.0) 0.18 0 (0) NSTEMI, n (%) 4635 (61.0) 3044 (61.5) 1591 (60.0) 0.19 0 (0) Glucose-lowering treatment on hospital admission Treatment with insulin, n (%) 681 (9.0) 457 (9.2) 224 (8.4) < 0.001 118 (1.5) Treatment with oral glucose lowering medication, n (%) 974 (12.8) 646 (13.1) 328 (12.4) < 0.001 124 (1.6) Glucose-lowering treatment at hospital discharge Treatment with insulin, n (%) 722 (9.5) 490 (10.0) 232 (8.7) 0.10 1 (0) Treatment with oral glucose-lowering medication, n (%) 1080 (14.2) 686 (13.9) 394 (14.8) 0.24 0 (0) Data are presented as count (%) or decimal mean (SD). HbA1c: hemoglobin A1c; DM: diabetes mellitus; STEMI: ST elevation myocardial infarction; NSTEMI: non-ST elevation myocardial infarction. Analysis of routines Routinely performing OGTT was the work routine which implementation differed the most between the dichotomized groups 0–1 routines (11%) vs. 2–4 routines (87%) (Table 3 ). Also, none of the CR centers where 0–1 routines were followed reported CR physicians to initiate and/or adjust glucose-lowering medication. Routine composition for individual routine exposures, by the number of patients per routine and the percentage of patients exposed/not exposed to other routines are shown in Table S1 . Table 3 The number and percentage of patients followed at CR centers applying the surveyed diabetes care work routines, by advancing number of routines (0–4 routines) and dichotomized (0–1 vs. 2–4 routines). Number of routines n FG/HbA1c measured OGTT routinely performed Joint case rounds Glucose lowering medication adjusted 0 2024 0 (0) 0 (0) 0 (0) 0 (0) 1 2919 2161 (74) 529 ( 18 ) 229 ( 8 ) 0 (0) 2 1890 1686 (89) 1546 (82) 256 ( 14 ) 292 ( 15 ) 3 478 478 (100) 478 (100) 170 (36) 308 (64) 4 284 284 (100) 284 (100) 284 (100) 284 (100) 0–1 4943 2161 (44) 529 ( 11 ) 229 ( 5 ) 0 (0) 2–4 2652 2448 (92) 2308 (87) 710 ( 27 ) 884 (33) Data are presented as counts (%). FG: fasting glucose; HbA1c: hemoglobin A1c; OGTT: oral glucose tolerance test. Outcome analyses Outcome data on diabetes incidence was available for 7595 (99.9%) patients. During the first year post-MI 303 patients were diagnosed with diabetes, resulting in a diabetes incidence during follow-up of 4.0%. The diabetes incidence for patients followed at centers where 0, 1, 2, 3 and 4 routines were implemented was 2.7%, 3.7%, 5.1%. 5.4% and 6.3%. Further details on incidence rates are shown in Table 4 . Outcome data was available on 7594 (99.9%) patients for oral glucose-lowering treatment. Glucose-lowering medication other than insulin was prescribed to 1080 (14.2%) patients at discharge and 17.9% at one-year follow-up. Almost all these patients had a diabetes diagnosis (96.6%). The percentage of treated patients followed at centers where 0, 1, 2, 3 and 4 routines were implemented was 16.8%, 17.3%, 17.1%, 20.4% and 32.4%. The results from the mixed-effect modelling are shown in Table 5 , displaying the adjusted incidence changes and risk ratios with confidence intervals for the exposures dichotomized as 0–1 versus 2–4 routines and each routine separately. Having 2–4 routines in place was associated with a higher diabetes incidence (adjusted incidence change 1.79%, risk ratio (RR) [95% confidence interval]: 1.54 [1.20, 1.88], p = 0.0017). The proportion of patients being treated with oral glucose-lowering medication was marginally higher for patients exposed to 2–4 routines compared to those exposed to 0–1 routines (adjusted difference 2.12%) without reaching statistical significance (RR 1.12 [0.98, 1.27], p = 0.0974). When examining each routine separately, routinely performing OGTT was associated with both outcomes, with an adjusted difference in diabetes incidence of 2.00% (RR 1.62 [1.26, 1.98], (p = 0.0007) and a higher probability of patients receiving diabetes treatment at one-year (adjusted difference 3.64%, RR 1.22 [1.07, 1.37], p = 0.0046). The proportion of patients receiving oral glucose-lowering treatment at one-year post-MI was also higher when such medication was reported to be adjusted by the CR physicians (adjusted difference 5.34%, RR 1.31 [1.06, 1.56], p = 0.0155). As shown in Fig. 1 , compared to having no work routines for diabetes care in place, the more routines implemented the higher the diabetes incidence (p for trend = 0.0014). Table 4 The proportion of patients with incident diabetes (left) and proportion of patients treated with oral glucose-lowering medication (right) as registered at follow-up visits within CR during the first year post-MI. Diabetes incidence Glucose-lowering treatment Exposed Non-exposed Exposed Non-exposed FG/HbA1c measured 4.5% 3.2% 18.0% 17.6% OGTT routinely performed 5.3% 3.2% 19.8% 16.7% Oral glucose-lowering medication adjusted 5.4% 3.8% 23.3% 17.1% Joint case rounds 4.6% 3.9% 22.7% 17.3% Exposed/non-exposed refers to patients followed at CR centers where the respective routine was applied/not applied. FG: fasting glucose; HbA1c: hemoglobin A1c; OGTT: oral glucose tolerance test. Table 5 Adjusted differences and relative risks (confidence intervals) in diabetes incidence and proportion receiving oral glucose-lowering treatment for patients followed at centers applying 0–1 vs 2–4 routines, as well as for each routine separately. Diabetes incidence Proportion receiving glucose-lowering medication Adjusted difference Relative risk p-value Adjusted difference Relative risk p-value Exposure definition 0–1 vs. 2–4 routines 1.79% (0.70%, 2.88%) 1.54 (1.20, 1.88) 0.0017 2.12% (-0.38%, 4.62%) 1.12 (0.98, 1.27) 0.0974 Each routine separately FG/HbA1c measured 0.71% (-0.6, 2.02%) 1.22 (0.81, 1.64) 0.2890 0.91% (-1.98%, 3.81%) 1.05 (0.89, 1.22) 0.5360 OGTT routinely performed 2.00% (0.88%, 3.11%) 1.62 (1.26, 1.98) 0.0007 3.64% (1.13%, 6.15%) 1.22 (1.07, 1.37) 0.0046 Oral glucose-lowering medication adjusted 1.12% (-0.92%, 3.17%) 1.30 (0.76, 1.84) 0.2830 5.34% (1.02%, 9.65%) 1.31 (1.06, 1.56) 0.0155 Joint case rounds 1.39% (-0.77%, 3.55%) 1.36 (0.80, 1.91) 0.2080 3.70% (-0.82%, 8.22%) 1.21 (0.95, 1.48) 0.1090 FG: fasting glucose; HbA1c: hemoglobin A1c; OGTT: oral glucose tolerance test. Discussion In this study we observed that having structured work routines for diabetes care in CR was associated with a higher diabetes incidence and a higher proportion of patients being treated with oral glucose-lowering medication at one-year post-MI. Out of the four diabetes care routines examined, using OGTT during follow-up was most strongly associated with both outcomes, followed by glucose-lowering medication being initiated and/or adjusted by the CR physicians. Also, we observed a dose-response incremental benefit with a greater number of implemented routines. Although CR programs are overall relatively comprehensive in Sweden, our study indicates considerable variation in how work routines for screening and treatment of diabetes in post-MI patients are applied across CR sites. In the European Society of Cardiology guidelines for diabetes and cardiovascular disease and the American Diabetes Association update (both from 2023), screening for potential diabetes among patients who have suffered a cardiovascular event is highly recommended ( 5 , 10 ). It has previously been shown that by analyzing fasting glucose, HbA1c and/or performing OGTT, two-thirds of patients with acute coronary syndromes without known diabetes are found to have undiagnosed diabetes or other abnormalities in glucose metabolism ( 6 ). This highlights the importance of early screening for glucometabolic abnormalities in patients with MI to enable adequate treatment, which in turn improves long-term prognosis reducing cardiovascular disease- and diabetes complications. Only 63% of the CR centers reported routinely evaluating fasting glucose and HbA1c at the start of the CR program, a percentage that should be closer to 100%. Also, only 40% reported routinely using OGTT, most of whom reported screening only a selection of patients. The results indicate ample room for improvement in screening for glucometabolic abnormalities within CR in Sweden. Adequate diabetes treatment post-MI is strongly recommended ( 5 ). Our findings showed that 80.8% of patients with diabetes were treated with glucose-lowering agents (oral or insulin) at discharge and 86.3% at one-year follow-up. Initiating or adjusting glucose-lowering treatment was, however, not consistently carried out by physicians at CR centers, with only one in six centers reporting to follow this routine. As indicated by the latest EUROASPIRE survey, conducted during the same time as the Perfect-CR study (2016–2017), there also seemed to be room for improvement in adequate diabetes treatment among patients with coronary artery disease in Europe. The authors showed that 75% of patients with established diabetes were treated with glucose-lowering medication, most commonly metformin ( 11 ). The importance of identifying diabetes post-MI holds even more true with recent advancements of glucose-lowering treatment with cardioprotective capacity, specifically SGLT-2 inhibitors, and GLP-1RA ( 22 , 23 ). The use of SGLT-2 inhibitors and/or GLP-1RA has exhibited positive outcomes in terms of reducing the risk of cardiovascular death, hospitalization for heart failure, and renal complications ( 24 ). Recent data from the SWEDEHEART registry has shown a marked increase in the use of SGLT-2 inhibitors and GLP-1RA in recent years, with more than 60% of post-MI patients being treated with either or both classes of drugs in 2023 ( 4 ). Still there is room for improvement, especially for GLP-1RA which were only used in ~ 10% of patients in the same year. Combined, these results indicate that CR physicians need to take a larger responsibility for adequate diabetes treatment post-MI. As such, this aspect of the risk factor treatment arsenal should to a larger extent be included in comprehensive CR care, analogous to treatment for hypertension and dyslipidemia. The optimal laboratory assessments to detect glucometabolic abnormalities in patients with cardiovascular disease is still debated. Two of the diabetes care work routines examined in our study were evaluating fasting glucose and/or HbA1c values at the start of the CR program and routinely performing OGTT for detecting glucometabolic abnormalities during post-MI follow-up. Out of the two routines, performing OGTT was associated with an increased diabetes incidence at one-year post-MI. Karayiannides et al. recently showed that performing OGTT identified 10% more patients with undetected diabetes at the time of MI, compared to using fasting glucose and HbA1c alone ( 7 ). Similarly, EUROASPIRE V demonstrated that if OGTT was not conducted, 30% of patients diagnosed with type 2 diabetes and 70% of individuals with impaired glucose tolerance would have remained undetected ( 11 ). Combined, these results support recommendations from the European Society of Cardiology and American Diabetes Association guidelines on complementing diabetes screening with fasting glucose and HbA1c with OGTT in unclear cases ( 5 , 10 ). OGTT is also necessary to diagnose patients with impaired glucose tolerance ( 25 , 26 ) which is estimated to carry the same high risk for cardiovascular disease as newly detected diabetes ( 27 ). Having joint case rounds with diabetologists was the work routine surveyed in the Perfect-CR study most seldom implemented at CR centers. The importance of the multidisciplinary team has been recognized to improve patient care and prevent disease complications and premature mortality in several different disease states ( 28 , 29 ). In a review by Muuza, the risk of amputation in patients with diabetes-related foot ulcers after initiation a multidisciplinary approach was investigated ( 28 ). While the team composition varied, in 94% of the included studies major amputations were reduced. Also, patients under the care of multidisciplinary teams consistently demonstrated improved glycemic control, management of vascular and infection diseases, and a lower incidence of major amputations ( 28 ). Chava et al demonstrated the benefit of having a multidisciplinary team in caring for patients with congestive heart failure, showing a significant decrease in both readmission rates and length of hospital stay ( 29 ). While falling short of statistical significance, we observed that at centers reporting to have joint case rounds with diabetologists for managing post-MI patients with diabetes, the chance of diagnosing more patients with diabetes and the proportion of patients being prescribed oral glucose-lowering medication was numerically higher. Combined, others´ and our results suggest that multidisciplinary team collaboration may contribute to better identification, treatment, and outcomes in several disease states. Strengths and limitations Our study focused on the association of CR work routines for diabetes care at center-level and detection and treatment of diabetes on patient-level, an aspect that to our knowledge has not been previously studied. Data was used from the nationwide SWEDEHEART registry and the Perfect-CR cohort, both having a center-level coverage of 100%. Missing data at center-level was minimal, increasing representativity and minimizing selection bias. All the same, some limitations should be mentioned. Classification of glucose-lowering medication in the SWEDEHEART registry at the time of study was limited to insulin and oral glucose-lowering agents. Data on fasting glucose and HbA1c was often missing and could thus not be included as an individual outcome of diabetes treatment quality. Finally, residual confounding cannot be excluded because this was an observational study and caution is required with respect to causal interpretation. Conclusions In conclusion, this study provides supporting evidence to the advantage of structured follow-up for identifying and managing patients with abnormal glucose metabolism post-MI. Our results particularly encourage the use of OGTT as a routine diagnostic work-up. Abbreviations CR – Cardiac rehabilitation GLP-1RA – Glucagon-like peptide-1 receptor agonist HbA1c – Hemoglobin A1C MI – Myocardial infarction OGTT – Oral glucose tolerance test SWEDEHEART – The Swedish Web system for Enhancement and Development of Evidence-based care in Heart Disease Evaluated According to Recommended Therapies SGLT-2 – Sodium-glucose cotransporter-2 Declarations Ethical approval and consent to participate The need for signed consent by patients for inclusion in Swedish quality registries and waived. Upon hospital admission, patients with MI are informed verbally and in writing by a nurse or physician about SWEDEHEART and their unrestricted ability to opt out of the registry at any time (extremely rare, 0-5 individuals/year). The study complied with the Helsinki Declaration and was reviewed and approved by the Ethics Committee at Lund University (2018-55). Consent for publication Not applicable. Availability of data and materials Access to data from the SWEDEHEART registry needs to be applied for and third-party data usage is not allowed. Instead, given ethical study approval from the Swedish Ethical Review Authority, access to SWEDEHEART data supporting the present findings can be applied for from the Uppsala Clinical Research Center in Sweden. Further information can be found on the UCR www.ucr.uu.se/en/ and Swedish Ethical Review Authority etikprovningsmyndigheten.se/ websites. Aggregated data used in the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was funded by The Swedish Research Council for Health, Working Life and Welfare (FORTE, grant number 2019-00365); The Swedish Heart and Lung Association (grant number 20190431); and the Region of Skane, Sweden. Authors’ contributions EH and MLe conceived and designed the study. HÖM and MLe were involved in data acquisition. BS, MLe, NE, RP, and JW conducted the statistical analyses. BS and MLe drafted the manuscript. MM, EH and MLe provided supervision and mentorship. MLe provided funding and administrated the project. All authors reviewed and revised the manuscript, gave final approval, and agreed to be accountable for all aspects of the work. Acknowledgements Not applicable. References Bartnik M, Norhammar A, Rydén L. Hyperglycaemia and cardiovascular disease. J Intern Med. 2007;262(2):145-56. Jacoby RM, Nesto RW. Acute myocardial infarction in the diabetic patient: pathophysiology, clinical course and prognosis. J Am Coll Cardiol. 1992;20(3):736-44. Gyberg V, De Bacquer D, De Backer G, Jennings C, Kotseva K, Mellbin L, et al. Patients with coronary artery disease and diabetes need improved management: a report from the EUROASPIRE IV survey: a registry from the EuroObservational Research Programme of the European Society of Cardiology. Cardiovasc Diabetol. 2015;14:133. Vasko P AJ, Bäck M, et al. SWEDEHEART 2023 Annual Report. In: Center UCR, editor. Uppsala, Sweden2024. Marx N, Federici M, Schütt K, Müller-Wieland D, Ajjan RA, Antunes MJ, et al. 2023 ESC Guidelines for the management of cardiovascular disease in patients with diabetes. Eur Heart J. 2023. Norhammar A, Tenerz A, Nilsson G, Hamsten A, Efendíc S, Rydén L, Malmberg K. Glucose metabolism in patients with acute myocardial infarction and no previous diagnosis of diabetes mellitus: a prospective study. Lancet. 2002;359(9324):2140-4. Karayiannides S, Djupsjo C, Kuhl J, Hofman-Bang C, Norhammar A, Holzmann MJ, Lundman P. Long-term prognosis in patients with acute myocardial infarction and newly detected glucose abnormalities: predictive value of oral glucose tolerance test and HbA1c. Cardiovasc Diabetol. 2021;20(1):122. Sarwar N, Gao P, Seshasai SR, Gobin R, Kaptoge S, Di Angelantonio E, et al. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet. 2010;375(9733):2215-22. Zelniker TA, Wiviott SD, Raz I, Im K, Goodrich EL, Furtado RHM, et al. Comparison of the Effects of Glucagon-Like Peptide Receptor Agonists and Sodium-Glucose Cotransporter 2 Inhibitors for Prevention of Major Adverse Cardiovascular and Renal Outcomes in Type 2 Diabetes Mellitus. Circulation. 2019;139(17):2022-31. ElSayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D, et al. 2. Classification and Diagnosis of Diabetes: Standards of Care in Diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S19-s40. Ferrannini G, De Bacquer D, De Backer G, Kotseva K, Mellbin L, Wood D, Rydén L. Screening for Glucose Perturbations and Risk Factor Management in Dysglycemic Patients With Coronary Artery Disease-A Persistent Challenge in Need of Substantial Improvement: A Report From ESC EORP EUROASPIRE V. Diabetes Care. 2020;43(4):726-33. Ögmundsdottir Michelsen H, Sjölin I, Schlyter M, Hagström E, Kiessling A, Henriksson P, et al. Cardiac rehabilitation after acute myocardial infarction in Sweden – evaluation of programme characteristics and adherence to European guidelines: The Perfect Cardiac Rehabilitation (Perfect-CR) study. European Journal of Preventive Cardiology. 2020;27(1):18-27. Piepoli MF, Corrà U, Adamopoulos S, Benzer W, Bjarnason-Wehrens B, Cupples M, et al. Secondary prevention in the clinical management of patients with cardiovascular diseases. Core components, standards and outcome measures for referral and delivery: A Policy Statement from the Cardiac Rehabilitation Section of the European Association for Cardiovascular Prevention & Rehabilitation. Endorsed by the Committee for Practice Guidelines of the European Society of Cardiology. European Journal of Preventive Cardiology. 2020;21(6):664-81. Visseren FLJ, Mach F, Smulders YM, Carballo D, Koskinas KC, Back M, et al. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J. 2021;42(34):3227-337. Ludvigsson JF, Svedberg P, Olén O, Bruze G, Neovius M. The longitudinal integrated database for health insurance and labour market studies (LISA) and its use in medical research. Eur J Epidemiol. 2019;34(4):423-37. Jernberg T, Attebring MF, Hambraeus K, Ivert T, James S, Jeppsson A, et al. The Swedish Web-system for enhancement and development of evidence-based care in heart disease evaluated according to recommended therapies (SWEDEHEART). Heart. 2010;96(20):1617-21. Bäck M, Leosdottir M, Hagström E, Norhammar A, Hag E, Jernberg T, et al. The SWEDEHEART secondary prevention and cardiac rehabilitation registry (SWEDEHEART CR registry). Eur Heart J Qual Care Clin Outcomes. 2021;7(5):431-7. Ritsinger V, Lagerqvist B, Lundman P, Hagström E, Norhammar A. Diabetes, metformin and glucose lowering therapies after myocardial infarction: Insights from the SWEDEHEART registry. Diab Vasc Dis Res. 2020;17(6):1479164120973676. Michelsen H, Henriksson P, Wallert J, Bäck M, Sjölin I, Schlyter M, et al. Organizational and patient-level predictors for attaining key risk factor targets in cardiac rehabilitation after myocardial infarction: The Perfect-CR study. Int J Cardiol. 2023;371:40-8. Kitabchi AE, Temprosa M, Knowler WC, Kahn SE, Fowler SE, Haffner SM, et al. Role of insulin secretion and sensitivity in the evolution of type 2 diabetes in the diabetes prevention program: effects of lifestyle intervention and metformin. Diabetes. 2005;54(8):2404-14. Rubin D. Multiple imputation for non-response in surveys. New York: John Wiley & Sons; 1987. Standl E, Schnell O, McGuire DK, Ceriello A, Rydén L. Integration of recent evidence into management of patients with atherosclerotic cardiovascular disease and type 2 diabetes. Lancet Diabetes Endocrinol. 2017;5(5):391-402. Zinman B, Wanner C, Lachin JM, Fitchett D, Bluhmki E, Hantel S, et al. Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes. N Engl J Med. 2015;373(22):2117-28. Giugliano D, Longo M, Signoriello S, Maiorino MI, Solerte B, Chiodini P, Esposito K. The effect of DPP-4 inhibitors, GLP-1 receptor agonists and SGLT-2 inhibitors on cardiorenal outcomes: a network meta-analysis of 23 CVOTs. Cardiovasc Diabetol. 2022;21(1):42. Standl E. Does using HbA1c inform diagnosis of diabetes in patients with coronary artery disease? Eur Heart J. 2015;36(19):1149-51. Beulens J, Rutters F, Rydén L, Schnell O, Mellbin L, Hart HE, Vos RC. Risk and management of pre-diabetes. Eur J Prev Cardiol. 2019;26(2_suppl):47-54. Ritsinger V, Tanoglidi E, Malmberg K, Näsman P, Rydén L, Tenerz Å, Norhammar A. Sustained prognostic implications of newly detected glucose abnormalities in patients with acute myocardial infarction: Long-term follow-up of the Glucose Tolerance in Patients with Acute Myocardial Infarction cohort. Diabetes and Vascular Disease Research. 2015;12(1):23-32. Musuuza J, Sutherland BL, Kurter S, Balasubramanian P, Bartels CM, Brennan MB. A systematic review of multidisciplinary teams to reduce major amputations for patients with diabetic foot ulcers. J Vasc Surg. 2020;71(4):1433-46.e3. Chava R, Karki N, Ketlogetswe K, Ayala T. Multidisciplinary rounds in prevention of 30-day readmissions and decreasing length of stay in heart failure patients: A community hospital based retrospective study. Medicine (Baltimore). 2019;98(27):e16233. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4554688","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":317688814,"identity":"c0b0be98-727c-4bc3-94df-d1b01b917c92","order_by":0,"name":"Bashaaer Sharad","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIiWNgGAWjYBACAwYGNiiTB0Qwy4EFH5CixRgsmECKlsQGQlrM2Y8/e/Cjxiafgf/swc8VNdbpa9ubNzAktjHY8+PQYtmTY27YcyzNskEiL1nyzLH03G1njhWAtCTObMDhsAM5bBI8bIcNGCR4DCQb2A7nbruRYwDSkmBwAIeW88+fSf7599+Agf+M8c+Gf4fTze6/AWuxt8el5UaCmTRv2wFgMOSYSTa2HU4wu8ED1sK4AZdfZrwxk5btSzZgk8gxs2zsSzfcdiat4EDCOYnEGThsMedPfyb55pudAT/QYTcbvlnLmx0/vPHBhzIbe34c3ocDNmQO0HwJAupHwSgYBaNgFOADALSfWOZcf8UgAAAAAElFTkSuQmCC","orcid":"","institution":"Lund University","correspondingAuthor":true,"prefix":"","firstName":"Bashaaer","middleName":"","lastName":"Sharad","suffix":""},{"id":317688815,"identity":"48d07ffc-01c8-46db-9980-dd826f5558d4","order_by":1,"name":"Nils Eckerdal","email":"","orcid":"","institution":"Uppsala 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University","correspondingAuthor":false,"prefix":"","firstName":"Amra","middleName":"","lastName":"Jujic","suffix":""},{"id":317688819,"identity":"5e16601b-e778-4040-b9ff-32e341e82602","order_by":5,"name":"Matthias Lidin","email":"","orcid":"","institution":"Karolinska Institute","correspondingAuthor":false,"prefix":"","firstName":"Matthias","middleName":"","lastName":"Lidin","suffix":""},{"id":317688820,"identity":"7b648315-28d2-4a0b-8136-6b0f09554e30","order_by":6,"name":"Linda Mellbin","email":"","orcid":"","institution":"Karolinska Institute","correspondingAuthor":false,"prefix":"","firstName":"Linda","middleName":"","lastName":"Mellbin","suffix":""},{"id":317688821,"identity":"f1befcef-815d-42ba-bb82-458d9153e3e0","order_by":7,"name":"Nael Shaat","email":"","orcid":"","institution":"Lund 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University","correspondingAuthor":false,"prefix":"","firstName":"Emil","middleName":"","lastName":"Hagström","suffix":""},{"id":317688825,"identity":"05a2c11e-7d49-4bbe-9891-d1c33411b868","order_by":11,"name":"Margret Leosdottir","email":"","orcid":"","institution":"Lund University","correspondingAuthor":false,"prefix":"","firstName":"Margret","middleName":"","lastName":"Leosdottir","suffix":""}],"badges":[],"createdAt":"2024-06-09 17:51:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4554688/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4554688/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12933-024-02425-6","type":"published","date":"2024-09-03T15:57:36+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59433909,"identity":"82aeff07-cfe0-4d0d-80b1-ad8cdecafe8c","added_by":"auto","created_at":"2024-07-01 18:56:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":97394,"visible":true,"origin":"","legend":"\u003cp\u003eIncidence change and confidence intervals for the number of routines followed, from one to four routines, no routine followed being the reference group. Diabetes incidence is shown above (\u003cstrong\u003eA\u003c/strong\u003e) and oral glucose-lowering treatment below (\u003cstrong\u003eB\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4554688/v1/a7d66c691fe1a73d6cbba3b9.png"},{"id":64185998,"identity":"dc5947b7-cf05-443d-965c-fab13774840f","added_by":"auto","created_at":"2024-09-09 16:23:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":880736,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4554688/v1/f163468e-dd94-4277-b6c6-247a6c899bee.pdf"},{"id":59433912,"identity":"5a114520-b008-4e34-9441-cfc23cfe90f3","added_by":"auto","created_at":"2024-07-01 18:56:03","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":389857,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-4554688/v1/15962ecd4eb46ec0731ab485.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Structured diabetes care routines in cardiac rehabilitation are associated with increased diabetes detection and improved treatment after myocardial infarction: a nationwide observational study","fulltext":[{"header":"Background","content":"\u003cp\u003eAbnormal glucose metabolism is common in patients with ischemic heart disease, and is associated with a considerably higher risk of mortality and recurrent cardiovascular events (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The reported prevalence of diabetes mellitus in patients with myocardial infarction (MI) is 20\u0026ndash;25% (\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Further two-thirds of patients with MI without known diabetes have undiagnosed diabetes or pre-diabetes (impaired fasting glucose or impaired glucose tolerance) diagnosed by fasting glucose, hemoglobin A1c (HbA1c) or with an oral glucose tolerance test (OGTT) (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Both patients with diabetes and those with pre-diabetes have a worse prognosis than patients with normal glucose metabolism (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite improvements in diagnostic methods, a considerable proportion of MI patients with diabetes and pre-diabetes remain undiagnosed and are therefore untreated (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In recent years, new treatments (e.g., glucagon-like peptide-1 receptor agonists [GLP-1RA] and sodium-glucose cotransporter-2 [SGLT-2] inhibitors provide additional prognostic benefit beyond optimal metabolic and risk factor control (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Given this background, there is a need to improve screening for, and treatment of, abnormal glucose metabolism in patients with MI to improve long-term prognosis.\u003c/p\u003e \u003cp\u003eAccording to international guidelines on diabetes and cardiovascular disease, fasting glucose and HbA1c should be routinely measured in all patients with MI to confirm or exclude a diabetes diagnosis (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). An OGTT may be considered in cases where a diabetes diagnosis is still unclear (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). If abnormal glucose metabolism is identified, management of risk factors including lifestyle modification, adequate secondary preventive treatment and glycemic control should be applied to decrease the risk for recurrent cardiovascular events (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite guideline recommendations, follow-up at many cardiac rehabilitation (CR) centers for post-MI patients does not routinely include assessment of glucose metabolism (\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Also, pharmaceutical treatment and lifestyle modifications in patients with concomitant MI and diabetes are insufficient (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). In Sweden, CR for post-MI patients is well integrated into routine healthcare and holds a high international standard (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). However, there is considerable variation in both target attainment and the work routines applied at Swedish CR centers to reach treatment targets for risk factors (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). It is unknown to which extent structured routines for diabetes care are integrated into CR in Sweden, and whether having such routines implemented within CR improves detection and treatment of glucometabolic abnormalities for post-MI patients.\u003c/p\u003e \u003cp\u003eThe main purpose of this study was to 1) describe how screening and management of glucometabolic abnormalities is organized at CR centers in Sweden and 2) explore associations between work routines for management of glucometabolic abnormalities at center-level and diabetes incidence and treatment at patient-level at one-year post-MI.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis was an observational survey- and registry-based cohort study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eThree databases were used in this study: the Perfect-CR study, the national MI registry SWEDEHEART (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) and The Statistics Sweden registry (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Perfect-CR study was a survey-based study which evaluated the work routines followed at CR centers in Sweden in 2016 (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). All 78 centers actively following post-MI patients in Sweden at the time completed the survey and missing data was minimal (\u0026lt;\u0026thinsp;3%). Details of the study procedure have previously been published (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In the current study we focused on the part of the survey exploring work routines pertaining to diabetes management during CR. These included four work routines, defined as the study exposures: 1) routine assessment of fasting glucose and/or HbA1c values by a nurse at the start of the CR program (laboratory measures performed at index MI hospitalization or prior to CR start), 2) routine use of OGTT during follow-up, 3) having regular joint case rounds with diabetologists, and 4) initiation and/or adjustment of glucose-lowering medication by the CR center\u0026rsquo;s physicians. The use of OGTT could be performed in all patients without known diabetes or on a selection of patients (high normal HbA1c/fasting glucose). Out of the 78 CR centers participating in Perfect-CR, two centers had no follow-up data and were excluded from further analysis.\u003c/p\u003e \u003cp\u003ePatient baseline and outcome data were extracted from the SWEDEHEART and Statistics Sweden registries. SWEDEHEART is a nationwide registry for cardiac disease. The registry includes patient data from all hospitals in Sweden that treat and follow up patients with acute MI. Data on acute care is collected at coronary care units and follow-up data is collected at CR centers at 2-months and one-year post-MI (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). All coronary care units and CR centers in the country report to SWEDEHEART. The registry data includes information on comorbidities, previous medical history and medications, laboratory analyses, risk factors, psychosocial- and lifestyle variables, and readmissions (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Patient inclusion is shown in \u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e. Inclusion criteria were: 1) discharged alive after hospitalization for type-1 MI, 2) age 18\u0026ndash;74 years, and 3) attending CR in the year preceding administration of the Perfect-CR survey. The timeframe was chosen to match the time in which patients attended CR with the time reflected in the Perfect-CR survey answers. There were no exclusion criteria.\u003c/p\u003e \u003cp\u003ePrevalent and incident diabetes (type 1 or 2) in SWEDEHEART is defined as a diagnosis in medical records and/or by the patient being prescribed glucose-lowering medication. A diagnosis of pre-diabetes is not registered in SWEDEHEART. At the time of the study, variables reflecting diabetes treatment were \"Treatment with insulin (yes/no)\u0026rdquo; and \u0026ldquo;Treatment with other oral glucose-lowering medications (yes/no)\u0026rdquo;. Further classification of glucose-lowering medication was not registered at the time in SWEDEHEART and injection therapy other than insulin was uncommon (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStatistics Sweden is the Swedish government agency responsible for producing official statistics including data from Swedish health care units (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Data from Statistics Sweden used in this study included baseline data on socioeconomic status including country of birth, disposable household income, marital status, occupational status, and level of education (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCenter-level data were merged with patient-level data by linking each patient to the specific CR center where the patient underwent their follow-up (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The final dataset used in the current study included all patients (n\u0026thinsp;=\u0026thinsp;7601) discharged with an MI diagnosis (ICD-10 codes I21) between Nov 2015 and Oct 2016 and subsequently followed at the 76 included CR centers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eOutcome definition\u003c/h2\u003e \u003cp\u003eThe outcomes were 1) diabetes incidence and 2) the proportion of patients receiving glucose lowering treatment other than insulin at a one-year follow-up visit registered in SWEDEHEART. If one-year data was missing, data from the 2-month follow-up visit was used. Only diabetes was included in the incidence outcome as pre-diabetes is not registered in SWEDEHEART. Also, as it is uncommon for CR physicians to initiate or adjust insulin, we only included treatment with oral glucose-lowering medication in the treatment outcome. All patients irrespective of diabetes diagnosis were included in the diabetes treatment outcome analysis to ascertain inclusion of patients with pre-diabetes, that might be treated with oral glucose-lowering medication (mostly metformin) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eBaseline data are reported in frequencies (%), medians and interquartile ranges (Q1, Q3), means and standard deviations (SD) as appropriate. Exposures were modelled in three different ways: i) having two to four routines implemented defined as exposure versus having no or one routine implemented defined as reference; ii) each working routine defined as a separate exposure with not having that routine implemented defined as the reference; and iii) the number of implemented routines from zero to four, with zero being the reference. The association between the exposures and the outcomes were estimated as incidence changes (risk differences) and incidence ratios (risk ratios). Both measures were based on a mixed-effects linear model, with random intercepts for each CR center. The risk ratio was estimated as the sum of the crude control-group incidence and the risk difference, divided by the control-group incidence. The variance of the risk ratio estimate was calculated using the delta method. Patient- and center-level covariates included in the models were selected based on clinical expertise and predictors identified as meaningful for the attainment of lipid- and blood pressure treatment targets as identified in a previous publication from the Perfect-CR study (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Selected covariates are portrayed in a Directed Acyclic Graph (DAG) in \u003cb\u003eFigure S2\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eTo handle missing data and avoid biasing of estimates from using only complete cases, multiple imputation was implemented. With the overall rate of missingness among covariates being only 1.3%, simple hot deck imputation was used. Missing values on individual-level covariates were replaced by the value of a randomly selected individual from the same CR center. Missing values on CR center-level covariates were replaced by the value of a randomly selected CR center. 30 imputed data sets were created, and the results were combined using Rubin\u0026rsquo;s rules.\u003c/p\u003e \u003cp\u003e(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Statistical significance was set to p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Data was analyzed using IBM SPSS (version 27, Chicago, Illinois, USA) and R version 4.2.2.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCenter-level baseline characteristics\u003c/h2\u003e \u003cp\u003eOut of the 76 CR centers participating in Perfect-CR where follow-up data on patient-level was available, nine centers (11.8%) were based at university hospitals. The median number of patients eligible for follow-up per center in 2016 was 101 (68, 164). Fasting glucose and/or HbA1c were routinely evaluated at CR program initiation at 63.2% (n\u0026thinsp;=\u0026thinsp;48) of the CR centers, while 38.2% (n\u0026thinsp;=\u0026thinsp;29) of the centers reported routinely performing OGTT. At 17.1% (n\u0026thinsp;=\u0026thinsp;13) of the CR centers the physicians independently initiated and/or adjusted glucose-lowering medication and 9.2% (n\u0026thinsp;=\u0026thinsp;7) reported having regular joint case rounds with diabetologists. Most centers had none (23.7%, n\u0026thinsp;=\u0026thinsp;18) or one (36.8%, n\u0026thinsp;=\u0026thinsp;28) of the work routines for structured diabetes care in place, while 39.4% (n\u0026thinsp;=\u0026thinsp;30) of the CR centers reported having two or more routines implemented. Only 2.6% (n\u0026thinsp;=\u0026thinsp;2) of the centers reported having all four work routines implemented. Further details can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiabetes care work routines applied at cardiac rehabilitation centers in Sweden as surveyed in the Perfect-CR survey.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eQuestionnaire item\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCR centers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFasting glucose and/or HbA1c levels are routinely evaluated at the start of the CR program\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eUse of OGTT*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOGTT is performed on all patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c7\" namest=\"c6\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOGTT is performed on a selection of patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22 (28.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWe do not perform OGTT on our patients post-MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46 (60.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGlucose-lowering medication is initiated and/or adjusted by the CR center physicians\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eRegular joint case rounds with diabetologists at the CR center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*In patients without previous diabetes diagnosis. HbA1c: hemoglobin A1c; CR: cardiac rehabilitation; OGTT: oral glucose tolerance test; MI: myocardial infarction.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePatient-level baseline characteristics\u003c/h2\u003e \u003cp\u003eIn total, 7601 patients followed at the 76 CR centers were included. Mean age of the patients was 62.6\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;8.7 years and 76% were male. The proportion of patients with previously known or newly detected diabetes during hospitalization was 22.5% (n\u0026thinsp;=\u0026thinsp;1710), out of which 80.8% were treated with any glucose-lowering agent (oral or injection) at discharge. Diabetes prevalence at one-year follow-up was 26.5% (n\u0026thinsp;=\u0026thinsp;2013) with 86.3% of the patients being treated with any glucose-lowering agent. Further patient-level baseline characteristics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics at patient-level.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026ndash;1 routines followed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u0026ndash;4 routines followed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMissing, n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7601 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4947 (65.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2654 (35.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5744 (76.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3770 (76.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2004 (75.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.6\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.7\u0026thinsp;+\u0026thinsp;8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.5\u0026thinsp;+\u0026thinsp;8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRisk factors and previous disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevalent diabetes, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1522 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1005 (20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e517 (19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18 (0.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive smoker, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2119 (27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1331 (27.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e788 (30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e186 (2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic heart failure, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e364 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e217 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e147 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e184 (2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3576 (47.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2340 (47.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1236 (47.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34 (0.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior myocardial infarction, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1426 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e876 (17.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e550 (20.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27 (0.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003ePhysiological and laboratory measures at baseline\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting plasma glucose, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.0 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.0 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.1\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e724 (9.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1c, mmol/mol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.0 (14.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.9 (14.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.1\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5406 (71.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eType of myocardial infarction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTEMI, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2966 (39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1093 (22.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1063 (40.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNSTEMI, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4635 (61.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3044 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1591 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eGlucose-lowering treatment on hospital admission\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment with insulin, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e681 (9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e457 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e224 (8.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e118 (1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment with oral glucose lowering medication, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e974 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e646 (13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e328 (12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e124 (1.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlucose-lowering treatment at hospital discharge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment with insulin, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e722 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e490 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e232 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment with oral glucose-lowering medication, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1080 (14.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e686 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e394 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eData are presented as count (%) or decimal mean (SD). HbA1c: hemoglobin A1c; DM: diabetes mellitus; STEMI: ST elevation myocardial infarction; NSTEMI: non-ST elevation myocardial infarction.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of routines\u003c/h2\u003e \u003cp\u003eRoutinely performing OGTT was the work routine which implementation differed the most between the dichotomized groups 0\u0026ndash;1 routines (11%) vs. 2\u0026ndash;4 routines (87%) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Also, none of the CR centers where 0\u0026ndash;1 routines were followed reported CR physicians to initiate and/or adjust glucose-lowering medication. Routine composition for individual routine exposures, by the number of patients per routine and the percentage of patients exposed/not exposed to other routines are shown in \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe number and percentage of patients followed at CR centers applying the surveyed diabetes care work routines, by advancing number of routines (0\u0026ndash;4 routines) and dichotomized (0\u0026ndash;1 vs. 2\u0026ndash;4 routines).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003cp\u003eof routines\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFG/HbA1c measured\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOGTT routinely performed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eJoint case rounds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGlucose lowering medication adjusted\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2161 (74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e529 (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e229 (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1686 (89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1546 (82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e256 (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e292 (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e478 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e478 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e170 (36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e308 (64)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e284 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e284 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e284 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e284 (100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2161 (44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e529 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e229 (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2448 (92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2308 (87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e710 (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e884 (33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eData are presented as counts (%). FG: fasting glucose; HbA1c: hemoglobin A1c; OGTT: oral glucose tolerance test.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eOutcome analyses\u003c/h2\u003e \u003cp\u003eOutcome data on diabetes incidence was available for 7595 (99.9%) patients. During the first year post-MI 303 patients were diagnosed with diabetes, resulting in a diabetes incidence during follow-up of 4.0%. The diabetes incidence for patients followed at centers where 0, 1, 2, 3 and 4 routines were implemented was 2.7%, 3.7%, 5.1%. 5.4% and 6.3%. Further details on incidence rates are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Outcome data was available on 7594 (99.9%) patients for oral glucose-lowering treatment. Glucose-lowering medication other than insulin was prescribed to 1080 (14.2%) patients at discharge and 17.9% at one-year follow-up. Almost all these patients had a diabetes diagnosis (96.6%). The percentage of treated patients followed at centers where 0, 1, 2, 3 and 4 routines were implemented was 16.8%, 17.3%, 17.1%, 20.4% and 32.4%. The results from the mixed-effect modelling are shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, displaying the adjusted incidence changes and risk ratios with confidence intervals for the exposures dichotomized as 0\u0026ndash;1 versus 2\u0026ndash;4 routines and each routine separately. Having 2\u0026ndash;4 routines in place was associated with a higher diabetes incidence (adjusted incidence change 1.79%, risk ratio (RR) [95% confidence interval]: 1.54 [1.20, 1.88], p\u0026thinsp;=\u0026thinsp;0.0017). The proportion of patients being treated with oral glucose-lowering medication was marginally higher for patients exposed to 2\u0026ndash;4 routines compared to those exposed to 0\u0026ndash;1 routines (adjusted difference 2.12%) without reaching statistical significance (RR 1.12 [0.98, 1.27], p\u0026thinsp;=\u0026thinsp;0.0974). When examining each routine separately, routinely performing OGTT was associated with both outcomes, with an adjusted difference in diabetes incidence of 2.00% (RR 1.62 [1.26, 1.98], (p\u0026thinsp;=\u0026thinsp;0.0007) and a higher probability of patients receiving diabetes treatment at one-year (adjusted difference 3.64%, RR 1.22 [1.07, 1.37], p\u0026thinsp;=\u0026thinsp;0.0046). The proportion of patients receiving oral glucose-lowering treatment at one-year post-MI was also higher when such medication was reported to be adjusted by the CR physicians (adjusted difference 5.34%, RR 1.31 [1.06, 1.56], p\u0026thinsp;=\u0026thinsp;0.0155). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, compared to having no work routines for diabetes care in place, the more routines implemented the higher the diabetes incidence (p for trend\u0026thinsp;=\u0026thinsp;0.0014).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe proportion of patients with incident diabetes (left) and proportion of patients treated with oral glucose-lowering medication (right) as registered at follow-up visits within CR during the first year post-MI.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eDiabetes incidence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eGlucose-lowering treatment\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExposed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-exposed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExposed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNon-exposed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFG/HbA1c measured\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOGTT routinely performed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral glucose-lowering medication adjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJoint case rounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eExposed/non-exposed refers to patients followed at CR centers where the respective routine was applied/not applied. FG: fasting glucose; HbA1c: hemoglobin A1c; OGTT: oral glucose tolerance test.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAdjusted differences and relative risks (confidence intervals) in diabetes incidence and proportion receiving oral glucose-lowering treatment for patients followed at centers applying 0\u0026ndash;1 vs 2\u0026ndash;4 routines, as well as for each routine separately.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eDiabetes incidence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e \u003cp\u003eProportion receiving glucose-lowering medication\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdjusted difference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRelative risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdjusted difference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRelative risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExposure definition\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;1 vs. 2\u0026ndash;4 routines\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.79% (0.70%, 2.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.54 (1.20, 1.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.0017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.12% (-0.38%, 4.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.12 (0.98, 1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0974\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEach routine separately\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFG/HbA1c measured\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.71% (-0.6, 2.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.22 (0.81, 1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.2890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.91% (-1.98%, 3.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.05 (0.89, 1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.5360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOGTT routinely performed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.00% (0.88%, 3.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.62 (1.26, 1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.0007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.64% (1.13%, 6.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.22 (1.07, 1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral glucose-lowering medication adjusted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.12% (-0.92%, 3.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.30 (0.76, 1.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.2830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.34% (1.02%, 9.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.31 (1.06, 1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0155\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJoint case rounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.39% (-0.77%, 3.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.36 (0.80, 1.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.2080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.70% (-0.82%, 8.22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.21 (0.95, 1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1090\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eFG: fasting glucose; HbA1c: hemoglobin A1c; OGTT: oral glucose tolerance test.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study we observed that having structured work routines for diabetes care in CR was associated with a higher diabetes incidence and a higher proportion of patients being treated with oral glucose-lowering medication at one-year post-MI. Out of the four diabetes care routines examined, using OGTT during follow-up was most strongly associated with both outcomes, followed by glucose-lowering medication being initiated and/or adjusted by the CR physicians. Also, we observed a dose-response incremental benefit with a greater number of implemented routines.\u003c/p\u003e \u003cp\u003e Although CR programs are overall relatively comprehensive in Sweden, our study indicates considerable variation in how work routines for screening and treatment of diabetes in post-MI patients are applied across CR sites. In the European Society of Cardiology guidelines for diabetes and cardiovascular disease and the American Diabetes Association update (both from 2023), screening for potential diabetes among patients who have suffered a cardiovascular event is highly recommended (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). It has previously been shown that by analyzing fasting glucose, HbA1c and/or performing OGTT, two-thirds of patients with acute coronary syndromes without known diabetes are found to have undiagnosed diabetes or other abnormalities in glucose metabolism (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). This highlights the importance of early screening for glucometabolic abnormalities in patients with MI to enable adequate treatment, which in turn improves long-term prognosis reducing cardiovascular disease- and diabetes complications. Only 63% of the CR centers reported routinely evaluating fasting glucose and HbA1c at the start of the CR program, a percentage that should be closer to 100%. Also, only 40% reported routinely using OGTT, most of whom reported screening only a selection of patients. The results indicate ample room for improvement in screening for glucometabolic abnormalities within CR in Sweden.\u003c/p\u003e \u003cp\u003eAdequate diabetes treatment post-MI is strongly recommended (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Our findings showed that 80.8% of patients with diabetes were treated with glucose-lowering agents (oral or insulin) at discharge and 86.3% at one-year follow-up. Initiating or adjusting glucose-lowering treatment was, however, not consistently carried out by physicians at CR centers, with only one in six centers reporting to follow this routine. As indicated by the latest EUROASPIRE survey, conducted during the same time as the Perfect-CR study (2016\u0026ndash;2017), there also seemed to be room for improvement in adequate diabetes treatment among patients with coronary artery disease in Europe. The authors showed that 75% of patients with established diabetes were treated with glucose-lowering medication, most commonly metformin (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The importance of identifying diabetes post-MI holds even more true with recent advancements of glucose-lowering treatment with cardioprotective capacity, specifically SGLT-2 inhibitors, and GLP-1RA (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The use of SGLT-2 inhibitors and/or GLP-1RA has exhibited positive outcomes in terms of reducing the risk of cardiovascular death, hospitalization for heart failure, and renal complications (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Recent data from the SWEDEHEART registry has shown a marked increase in the use of SGLT-2 inhibitors and GLP-1RA in recent years, with more than 60% of post-MI patients being treated with either or both classes of drugs in 2023 (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Still there is room for improvement, especially for GLP-1RA which were only used in ~\u0026thinsp;10% of patients in the same year. Combined, these results indicate that CR physicians need to take a larger responsibility for adequate diabetes treatment post-MI. As such, this aspect of the risk factor treatment arsenal should to a larger extent be included in comprehensive CR care, analogous to treatment for hypertension and dyslipidemia.\u003c/p\u003e \u003cp\u003eThe optimal laboratory assessments to detect glucometabolic abnormalities in patients with cardiovascular disease is still debated. Two of the diabetes care work routines examined in our study were evaluating fasting glucose and/or HbA1c values at the start of the CR program and routinely performing OGTT for detecting glucometabolic abnormalities during post-MI follow-up. Out of the two routines, performing OGTT was associated with an increased diabetes incidence at one-year post-MI. Karayiannides et al. recently showed that performing OGTT identified 10% more patients with undetected diabetes at the time of MI, compared to using fasting glucose and HbA1c alone (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Similarly, EUROASPIRE V demonstrated that if OGTT was not conducted, 30% of patients diagnosed with type 2 diabetes and 70% of individuals with impaired glucose tolerance would have remained undetected (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Combined, these results support recommendations from the European Society of Cardiology and American Diabetes Association guidelines on complementing diabetes screening with fasting glucose and HbA1c with OGTT in unclear cases (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). OGTT is also necessary to diagnose patients with impaired glucose tolerance (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) which is estimated to carry the same high risk for cardiovascular disease as newly detected diabetes (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHaving joint case rounds with diabetologists was the work routine surveyed in the Perfect-CR study most seldom implemented at CR centers. The importance of the multidisciplinary team has been recognized to improve patient care and prevent disease complications and premature mortality in several different disease states (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In a review by Muuza, the risk of amputation in patients with diabetes-related foot ulcers after initiation a multidisciplinary approach was investigated (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). While the team composition varied, in 94% of the included studies major amputations were reduced. Also, patients under the care of multidisciplinary teams consistently demonstrated improved glycemic control, management of vascular and infection diseases, and a lower incidence of major amputations (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Chava et al demonstrated the benefit of having a multidisciplinary team in caring for patients with congestive heart failure, showing a significant decrease in both readmission rates and length of hospital stay (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). While falling short of statistical significance, we observed that at centers reporting to have joint case rounds with diabetologists for managing post-MI patients with diabetes, the chance of diagnosing more patients with diabetes and the proportion of patients being prescribed oral glucose-lowering medication was numerically higher. Combined, others\u0026acute; and our results suggest that multidisciplinary team collaboration may contribute to better identification, treatment, and outcomes in several disease states.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eOur study focused on the association of CR work routines for diabetes care at center-level and detection and treatment of diabetes on patient-level, an aspect that to our knowledge has not been previously studied. Data was used from the nationwide SWEDEHEART registry and the Perfect-CR cohort, both having a center-level coverage of 100%. Missing data at center-level was minimal, increasing representativity and minimizing selection bias. All the same, some limitations should be mentioned. Classification of glucose-lowering medication in the SWEDEHEART registry at the time of study was limited to insulin and oral glucose-lowering agents. Data on fasting glucose and HbA1c was often missing and could thus not be included as an individual outcome of diabetes treatment quality. Finally, residual confounding cannot be excluded because this was an observational study and caution is required with respect to causal interpretation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, this study provides supporting evidence to the advantage of structured follow-up for identifying and managing patients with abnormal glucose metabolism post-MI. Our results particularly encourage the use of OGTT as a routine diagnostic work-up.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCR \u0026ndash; Cardiac rehabilitation\u003c/p\u003e\n\u003cp\u003eGLP-1RA \u0026ndash; Glucagon-like peptide-1 receptor agonist\u003c/p\u003e\n\u003cp\u003eHbA1c \u0026ndash; Hemoglobin A1C\u003c/p\u003e\n\u003cp\u003eMI \u0026ndash; Myocardial infarction\u003c/p\u003e\n\u003cp\u003eOGTT \u0026ndash; Oral glucose tolerance test\u003c/p\u003e\n\u003cp\u003eSWEDEHEART \u0026ndash;\u0026nbsp;The Swedish Web system for Enhancement and Development of Evidence-based care in Heart Disease Evaluated According to Recommended Therapies\u003c/p\u003e\n\u003cp\u003eSGLT-2 \u0026ndash; Sodium-glucose cotransporter-2\u0026nbsp;\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthical approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe need for signed consent by patients for inclusion in Swedish quality registries and waived. Upon hospital admission, patients with MI are informed verbally and in writing by a nurse or physician about SWEDEHEART and their unrestricted ability to opt out of the registry at any time (extremely rare, 0-5 individuals/year).\u0026nbsp;The study\u0026nbsp;complied with the Helsinki Declaration\u0026nbsp;and was reviewed and approved by the Ethics Committee at Lund University (2018-55).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccess to data from the SWEDEHEART registry needs to be applied for and third-party data usage is not allowed. Instead, given ethical study approval from the Swedish Ethical Review Authority, access to SWEDEHEART data supporting the present findings can be applied for from the Uppsala Clinical Research Center in Sweden. Further information can be found on the UCR www.ucr.uu.se/en/ and Swedish Ethical Review Authority etikprovningsmyndigheten.se/ websites. Aggregated data used in the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by\u0026nbsp;The Swedish Research Council for Health, Working Life and Welfare (FORTE, grant number 2019-00365); The Swedish Heart and Lung Association (grant number 20190431); and the Region of Skane, Sweden.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026rsquo; contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEH and MLe conceived and designed the study. H\u0026Ouml;M and MLe were involved in data acquisition. BS, MLe, NE, RP, and JW conducted the statistical analyses. BS and MLe drafted the manuscript. MM, EH and MLe provided supervision and mentorship. MLe provided funding and administrated the project. All authors reviewed and revised the manuscript, gave final approval, and agreed to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBartnik M, Norhammar A, Ryd\u0026eacute;n L. Hyperglycaemia and cardiovascular disease. J Intern Med. 2007;262(2):145-56.\u003c/li\u003e\n\u003cli\u003eJacoby RM, Nesto RW. Acute myocardial infarction in the diabetic patient: pathophysiology, clinical course and prognosis. J Am Coll Cardiol. 1992;20(3):736-44.\u003c/li\u003e\n\u003cli\u003eGyberg V, De Bacquer D, De Backer G, Jennings C, Kotseva K, Mellbin L, et al. Patients with coronary artery disease and diabetes need improved management: a report from the EUROASPIRE IV survey: a registry from the EuroObservational Research Programme of the European Society of Cardiology. Cardiovasc Diabetol. 2015;14:133.\u003c/li\u003e\n\u003cli\u003eVasko P AJ, B\u0026auml;ck M, et al. SWEDEHEART 2023 Annual Report. In: Center UCR, editor. Uppsala, Sweden2024.\u003c/li\u003e\n\u003cli\u003eMarx N, Federici M, Sch\u0026uuml;tt K, M\u0026uuml;ller-Wieland D, Ajjan RA, Antunes MJ, et al. 2023 ESC Guidelines for the management of cardiovascular disease in patients with diabetes. Eur Heart J. 2023.\u003c/li\u003e\n\u003cli\u003eNorhammar A, Tenerz A, Nilsson G, Hamsten A, Efend\u0026iacute;c S, Ryd\u0026eacute;n L, Malmberg K. Glucose metabolism in patients with acute myocardial infarction and no previous diagnosis of diabetes mellitus: a prospective study. Lancet. 2002;359(9324):2140-4.\u003c/li\u003e\n\u003cli\u003eKarayiannides S, Djupsjo C, Kuhl J, Hofman-Bang C, Norhammar A, Holzmann MJ, Lundman P. Long-term prognosis in patients with acute myocardial infarction and newly detected glucose abnormalities: predictive value of oral glucose tolerance test and HbA1c. Cardiovasc Diabetol. 2021;20(1):122.\u003c/li\u003e\n\u003cli\u003eSarwar N, Gao P, Seshasai SR, Gobin R, Kaptoge S, Di Angelantonio E, et al. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet. 2010;375(9733):2215-22.\u003c/li\u003e\n\u003cli\u003eZelniker TA, Wiviott SD, Raz I, Im K, Goodrich EL, Furtado RHM, et al. Comparison of the Effects of Glucagon-Like Peptide Receptor Agonists and Sodium-Glucose Cotransporter 2 Inhibitors for Prevention of Major Adverse Cardiovascular and Renal Outcomes in Type 2 Diabetes Mellitus. Circulation. 2019;139(17):2022-31.\u003c/li\u003e\n\u003cli\u003eElSayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D, et al. 2. Classification and Diagnosis of Diabetes: Standards of Care in Diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S19-s40.\u003c/li\u003e\n\u003cli\u003eFerrannini G, De Bacquer D, De Backer G, Kotseva K, Mellbin L, Wood D, Ryd\u0026eacute;n L. Screening for Glucose Perturbations and Risk Factor Management in Dysglycemic Patients With Coronary Artery Disease-A Persistent Challenge in Need of Substantial Improvement: A Report From ESC EORP EUROASPIRE V. Diabetes Care. 2020;43(4):726-33.\u003c/li\u003e\n\u003cli\u003e\u0026Ouml;gmundsdottir Michelsen H, Sj\u0026ouml;lin I, Schlyter M, Hagstr\u0026ouml;m E, Kiessling A, Henriksson P, et al. Cardiac rehabilitation after acute myocardial infarction in Sweden \u0026ndash; evaluation of programme characteristics and adherence to European guidelines: The Perfect Cardiac Rehabilitation (Perfect-CR) study. European Journal of Preventive Cardiology. 2020;27(1):18-27.\u003c/li\u003e\n\u003cli\u003ePiepoli MF, Corr\u0026agrave; U, Adamopoulos S, Benzer W, Bjarnason-Wehrens B, Cupples M, et al. Secondary prevention in the clinical management of patients with cardiovascular diseases. Core components, standards and outcome measures for referral and delivery: A Policy Statement from the Cardiac Rehabilitation Section of the European Association for Cardiovascular Prevention \u0026amp;amp; Rehabilitation. Endorsed by the Committee for Practice Guidelines of the European Society of Cardiology. European Journal of Preventive Cardiology. 2020;21(6):664-81.\u003c/li\u003e\n\u003cli\u003eVisseren FLJ, Mach F, Smulders YM, Carballo D, Koskinas KC, Back M, et al. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J. 2021;42(34):3227-337.\u003c/li\u003e\n\u003cli\u003eLudvigsson JF, Svedberg P, Ol\u0026eacute;n O, Bruze G, Neovius M. The longitudinal integrated database for health insurance and labour market studies (LISA) and its use in medical research. Eur J Epidemiol. 2019;34(4):423-37.\u003c/li\u003e\n\u003cli\u003eJernberg T, Attebring MF, Hambraeus K, Ivert T, James S, Jeppsson A, et al. The Swedish Web-system for enhancement and development of evidence-based care in heart disease evaluated according to recommended therapies (SWEDEHEART). Heart. 2010;96(20):1617-21.\u003c/li\u003e\n\u003cli\u003eB\u0026auml;ck M, Leosdottir M, Hagstr\u0026ouml;m E, Norhammar A, Hag E, Jernberg T, et al. The SWEDEHEART secondary prevention and cardiac rehabilitation registry (SWEDEHEART CR registry). Eur Heart J Qual Care Clin Outcomes. 2021;7(5):431-7.\u003c/li\u003e\n\u003cli\u003eRitsinger V, Lagerqvist B, Lundman P, Hagstr\u0026ouml;m E, Norhammar A. Diabetes, metformin and glucose lowering therapies after myocardial infarction: Insights from the SWEDEHEART registry. Diab Vasc Dis Res. 2020;17(6):1479164120973676.\u003c/li\u003e\n\u003cli\u003eMichelsen H, Henriksson P, Wallert J, B\u0026auml;ck M, Sj\u0026ouml;lin I, Schlyter M, et al. Organizational and patient-level predictors for attaining key risk factor targets in cardiac rehabilitation after myocardial infarction: The Perfect-CR study. Int J Cardiol. 2023;371:40-8.\u003c/li\u003e\n\u003cli\u003eKitabchi AE, Temprosa M, Knowler WC, Kahn SE, Fowler SE, Haffner SM, et al. Role of insulin secretion and sensitivity in the evolution of type 2 diabetes in the diabetes prevention program: effects of lifestyle intervention and metformin. Diabetes. 2005;54(8):2404-14.\u003c/li\u003e\n\u003cli\u003eRubin D. Multiple imputation for non-response in surveys. New York: John Wiley \u0026amp; Sons; 1987.\u003c/li\u003e\n\u003cli\u003eStandl E, Schnell O, McGuire DK, Ceriello A, Ryd\u0026eacute;n L. Integration of recent evidence into management of patients with atherosclerotic cardiovascular disease and type 2 diabetes. Lancet Diabetes Endocrinol. 2017;5(5):391-402.\u003c/li\u003e\n\u003cli\u003eZinman B, Wanner C, Lachin JM, Fitchett D, Bluhmki E, Hantel S, et al. Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes. N Engl J Med. 2015;373(22):2117-28.\u003c/li\u003e\n\u003cli\u003eGiugliano D, Longo M, Signoriello S, Maiorino MI, Solerte B, Chiodini P, Esposito K. The effect of DPP-4 inhibitors, GLP-1 receptor agonists and SGLT-2 inhibitors on cardiorenal outcomes: a network meta-analysis of 23 CVOTs. Cardiovasc Diabetol. 2022;21(1):42.\u003c/li\u003e\n\u003cli\u003eStandl E. Does using HbA1c inform diagnosis of diabetes in patients with coronary artery disease? Eur Heart J. 2015;36(19):1149-51.\u003c/li\u003e\n\u003cli\u003eBeulens J, Rutters F, Ryd\u0026eacute;n L, Schnell O, Mellbin L, Hart HE, Vos RC. Risk and management of pre-diabetes. Eur J Prev Cardiol. 2019;26(2_suppl):47-54.\u003c/li\u003e\n\u003cli\u003eRitsinger V, Tanoglidi E, Malmberg K, N\u0026auml;sman P, Ryd\u0026eacute;n L, Tenerz \u0026Aring;, Norhammar A. Sustained prognostic implications of newly detected glucose abnormalities in patients with acute myocardial infarction: Long-term follow-up of the Glucose Tolerance in Patients with Acute Myocardial Infarction cohort. Diabetes and Vascular Disease Research. 2015;12(1):23-32.\u003c/li\u003e\n\u003cli\u003eMusuuza J, Sutherland BL, Kurter S, Balasubramanian P, Bartels CM, Brennan MB. A systematic review of multidisciplinary teams to reduce major amputations for patients with diabetic foot ulcers. J Vasc Surg. 2020;71(4):1433-46.e3.\u003c/li\u003e\n\u003cli\u003eChava R, Karki N, Ketlogetswe K, Ayala T. Multidisciplinary rounds in prevention of 30-day readmissions and decreasing length of stay in heart failure patients: A community hospital based retrospective study. Medicine (Baltimore). 2019;98(27):e16233.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cardiovascular-diabetology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cvdb","sideBox":"Learn more about [Cardiovascular Diabetology](http://cardiab.biomedcentral.com/)","snPcode":"12933","submissionUrl":"https://submission.nature.com/new-submission/12933/3","title":"Cardiovascular Diabetology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"cardiac rehabilitation, myocardial infarction, diabetes, secondary prevention","lastPublishedDoi":"10.21203/rs.3.rs-4554688/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4554688/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDespite the detrimental impact of abnormal glucose metabolism on cardiovascular prognosis after myocardial infarction (MI), diabetes is both underdiagnosed and undertreated. We aimed to investigate associations between structured diabetes care routines in cardiac rehabilitation (CR) and detection and treatment of diabetes at one-year post-MI.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eCenter-level data was derived from the Perfect-CR survey, which evaluated work routines applied at Swedish CR centers (n\u0026thinsp;=\u0026thinsp;76). Work routines involving diabetes care included: 1) routine assessment of fasting glucose and/or HbA1c, 2) routine use of oral glucose tolerance test (OGTT), 3) having regular case rounds with diabetologists, and 4) whether glucose-lowering medication was adjusted by CR physicians. Patient-level data was obtained from the national MI registry SWEDEHEART (n\u0026thinsp;=\u0026thinsp;7601, 76% male, mean age 62.6 years) and included all post-MI patients irrespective of diabetes diagnosis. Using mixed-effects regression we estimated differences between patients exposed vs. not exposed to the four above-mentioned diabetes care routines. Outcomes were diabetes incidence and the proportion of patients receiving oral glucose-lowering medication at one-year post-MI.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eRoutine assessment of fasting glucose/HbA1c was performed at 63.2% (n\u0026thinsp;=\u0026thinsp;48) of the centers, while 38.2% (n\u0026thinsp;=\u0026thinsp;29) reported using OGTT for detecting glucose abnormalities. Glucose-lowering medication adjusted by CR physicians (n\u0026thinsp;=\u0026thinsp;13, 17.1%) or regular case rounds with diabetologists (n\u0026thinsp;=\u0026thinsp;7, 9.2%) were less frequently reported. In total, 4.0% of all patients (n\u0026thinsp;=\u0026thinsp;304) were diagnosed with diabetes during follow-up and 17.9% (n\u0026thinsp;=\u0026thinsp;1361) were on oral glucose-lowering treatment one-year post-MI. Routine use of OGTT was associated with higher diabetes incidence at one-year (adjusted incidence change 2.00%, risk ratio [95% confidence interval]: 1.62 [1.26, 1.98], p\u0026thinsp;=\u0026thinsp;0.0007). At one-year a higher proportion of patients were receiving oral glucose-lowering medication at centers routinely using OGTT (1.22 [1.07, 1.37], p\u0026thinsp;=\u0026thinsp;0.0046) and where such medication was adjusted by CR physicians (1.31 [1.06, 1.56], p\u0026thinsp;=\u0026thinsp;0.0155). Compared to having none of the structured diabetes care routines, the more routines implemented the higher the diabetes incidence (from 0 routines: 2.7% to 4 routines: 6.3%; p for trend\u0026thinsp;=\u0026thinsp;0.0014).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eHaving structured routines for diabetes care implemented within CR can improve detection and treatment of diabetes post-MI. 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