The Probability of A1C Goal Attainment in Patients with Uncontrolled Type-2 Diabetes in a Large Integrated Delivery System: A Prediction Model

2020 ◽  
Author(s):  
Kevin M Pantalone ◽  
Anita D Misra-Hebert ◽  
Todd M Hobbs ◽  
Sheldon X Kong ◽  
Xinge Ji ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Goal Attainment ◽  
Index Date ◽  
Cleveland Clinic ◽  
Patient Characteristics ◽  
Psychiatric Disease ◽  
Lower Probability ◽  
Factors Associated ◽  
One Year

<b>Objective:</b> To assess patient characteristics and treatment factors associated with uncontrolled type 2 diabetes (T2D) and the probability of A1C goal attainment. <p><b>Research Design and Methods</b>: Retrospective cohort study using the electronic health record at Cleveland Clinic. Patients with uncontrolled T2D (A1C>9%) were identified on the index date of 12/31/2016 (n=6,973), grouped by attainment (n=1,653 [24.7%) or non-attainment (n=5,320 [76.3%]) of A1C<8% by 12/31/2017, and subgroups compared on a number of demographic and clinical variables. Based on these variables, a nomogram was created for predicting probability of A1C goal attainment. </p> <p><b>Results:</b> For the entire population, median age at index date was 57.7 years (53.3% male), and the majority were white (67.2%). Median A1C was 10.2%. Obesity (50.6%), cardiovascular disease (46.9%) and psychiatric disease (61.1%) were the most common comorbidities. Metformin (62.7%) and sulfonylureas (38.7%) were the most common anti-diabetes medications. Only 1,653 (24%) patients achieved an A1C <8%. Predictors of increased probability of A1C goal attainment were older age, white/non-Hispanic race/ethnicity, Medicare health insurance, lower baseline A1C, higher frequency of endocrinology/primary care visits, DPP-4i use, thiazolidinedione use, metformin use, GLP-1RA use, and fewer classes of anti-diabetes drugs. Factors associated with lower probability included insulin use and longer time in the T2D database (both presumed as likely surrogates for duration of T2D). </p> <p><b>Conclusions:</b> A minority of patients with an A1C>9% achieved an A1C<8% at one year. While most identified predictive factors are non-modifiable by the clinician, pursuit of frequent patient engagement and tailored drug regimens may help improve A1C goal attainment. </p>

scholarly journals The Probability of A1C Goal Attainment in Patients with Uncontrolled Type-2 Diabetes in a Large Integrated Delivery System: A Prediction Model

2020 ◽  
Author(s):  
Kevin M Pantalone ◽  
Anita D Misra-Hebert ◽  
Todd M Hobbs ◽  
Sheldon X Kong ◽  
Xinge Ji ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Goal Attainment ◽  
Index Date ◽  
Cleveland Clinic ◽  
Patient Characteristics ◽  
Psychiatric Disease ◽  
Lower Probability ◽  
Factors Associated ◽  
One Year

<b>Objective:</b> To assess patient characteristics and treatment factors associated with uncontrolled type 2 diabetes (T2D) and the probability of A1C goal attainment. <p><b>Research Design and Methods</b>: Retrospective cohort study using the electronic health record at Cleveland Clinic. Patients with uncontrolled T2D (A1C>9%) were identified on the index date of 12/31/2016 (n=6,973), grouped by attainment (n=1,653 [24.7%) or non-attainment (n=5,320 [76.3%]) of A1C<8% by 12/31/2017, and subgroups compared on a number of demographic and clinical variables. Based on these variables, a nomogram was created for predicting probability of A1C goal attainment. </p> <p><b>Results:</b> For the entire population, median age at index date was 57.7 years (53.3% male), and the majority were white (67.2%). Median A1C was 10.2%. Obesity (50.6%), cardiovascular disease (46.9%) and psychiatric disease (61.1%) were the most common comorbidities. Metformin (62.7%) and sulfonylureas (38.7%) were the most common anti-diabetes medications. Only 1,653 (24%) patients achieved an A1C <8%. Predictors of increased probability of A1C goal attainment were older age, white/non-Hispanic race/ethnicity, Medicare health insurance, lower baseline A1C, higher frequency of endocrinology/primary care visits, DPP-4i use, thiazolidinedione use, metformin use, GLP-1RA use, and fewer classes of anti-diabetes drugs. Factors associated with lower probability included insulin use and longer time in the T2D database (both presumed as likely surrogates for duration of T2D). </p> <p><b>Conclusions:</b> A minority of patients with an A1C>9% achieved an A1C<8% at one year. While most identified predictive factors are non-modifiable by the clinician, pursuit of frequent patient engagement and tailored drug regimens may help improve A1C goal attainment. </p>

scholarly journals The Probability of A1C Goal Attainment in Patients with Uncontrolled Type-2 Diabetes in a Large Integrated Delivery System: A Prediction Model

2020 ◽  
Author(s):  
Kevin M Pantalone ◽  
Anita D Misra-Hebert ◽  
Todd M Hobbs ◽  
Sheldon X Kong ◽  
Xinge Ji ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Goal Attainment ◽  
Index Date ◽  
Cleveland Clinic ◽  
Patient Characteristics ◽  
Psychiatric Disease ◽  
Lower Probability ◽  
Factors Associated ◽  
One Year

<b>Objective:</b> To assess patient characteristics and treatment factors associated with uncontrolled type 2 diabetes (T2D) and the probability of A1C goal attainment. <p><b>Research Design and Methods</b>: Retrospective cohort study using the electronic health record at Cleveland Clinic. Patients with uncontrolled T2D (A1C>9%) were identified on the index date of 12/31/2016 (n=6,973), grouped by attainment (n=1,653 [24.7%) or non-attainment (n=5,320 [76.3%]) of A1C<8% by 12/31/2017, and subgroups compared on a number of demographic and clinical variables. Based on these variables, a nomogram was created for predicting probability of A1C goal attainment. </p> <p><b>Results:</b> For the entire population, median age at index date was 57.7 years (53.3% male), and the majority were white (67.2%). Median A1C was 10.2%. Obesity (50.6%), cardiovascular disease (46.9%) and psychiatric disease (61.1%) were the most common comorbidities. Metformin (62.7%) and sulfonylureas (38.7%) were the most common anti-diabetes medications. Only 1,653 (24%) patients achieved an A1C <8%. Predictors of increased probability of A1C goal attainment were older age, white/non-Hispanic race/ethnicity, Medicare health insurance, lower baseline A1C, higher frequency of endocrinology/primary care visits, DPP-4i use, thiazolidinedione use, metformin use, GLP-1RA use, and fewer classes of anti-diabetes drugs. Factors associated with lower probability included insulin use and longer time in the T2D database (both presumed as likely surrogates for duration of T2D). </p> <p><b>Conclusions:</b> A minority of patients with an A1C>9% achieved an A1C<8% at one year. While most identified predictive factors are non-modifiable by the clinician, pursuit of frequent patient engagement and tailored drug regimens may help improve A1C goal attainment. </p>

scholarly journals Polypharmacy and oral antidiabetic treatment for type 2 diabetes characterised by drug class and patient characteristics: A Japanese database analysis

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Takeshi Horii ◽  
Makiko Iwasawa ◽  
Yusuke Kabeya ◽  
Koichiro Atuda
Keyword(s):  
Type 2 Diabetes ◽  
Medication Adherence ◽  
Patient Characteristics ◽  
Factors Associated ◽  
Antidiabetic Treatment ◽  
Proportion Of Days Covered ◽  
Hypoglycaemic Agent ◽  
Poor Medication Adherence ◽  
Observation Period

Abstract Polypharmacy (PP) occurs in patients with type 2 diabetes (T2DM) owing to multimorbidity. We evaluated concomitant PP and medication adherence in T2DM 3 years after initiation of administration of a hypoglycaemic agent using a nationwide claim-based database in Japan. Factors associated with medication PP and imperfect adherence were identified using multivariable logistic regression. PP was defined as using ≥6 medications. Patients with proportion of days covered (PDC) of <80% were defined as having poor medication adherence. A total of 884 patients were analysed. Multivariate analysis revealed that age, total number of consultations and body mass index (BMI) are factors that influence PP. Factors associated with PDC < 80% were 2–3, 4–5 and ≥ 6 medications compared with 1 medication, male sex, <17 consultations and age 50–59 and ≥ 60 years compared with <40 years. In conclusion, older age, high total number of consultations and BMI ≥ 25 kg/m2 are risk factors for PP. PP influenced good medication adherence at the end of the observation period.

Healing and Mortality Rates Following Toe Amputation in Type 2 Diabetes Mellitus

2019 ◽  
Author(s):  
Ian Mario Vassallo ◽  
Alfred Gatt ◽  
Kevin Cassar ◽  
Nikolaos Papanas ◽  
Cynthia Formosa
Keyword(s):  
Type 2 Diabetes ◽  
Patient Characteristics ◽  
Peripheral Circulation ◽  
Mortality Rates ◽  
Study Cohort ◽  
Included Patient ◽  
Single Centre Study ◽  
One Year ◽  
Toe Amputation

Abstract Background and Aim This single-centre study aimed to determine healing, re-ulceration, re-amputation and mortality rates at one year after toe amputations in patients with type 2 diabetes (T2DM). Patients and Methods Eighty-one participants with T2DM admitted for toe amputation were included. Patient characteristics, peripheral circulation and neuropathy status were recorded. Subjects were then followed every 3 months post-amputation for a year. Results Overall, 59.3% of participants underwent further surgery (n=31 to revise the original amputation site and n=17 to amputate a new site). During 12 months, 45.7% of participants presented with a new ulcer at a different site. Mortality was 7.4%. In 12.4% of participants, the amputation site remained incompletely healed. Only 20.9% had no complications in 12 months. At 12 months, 80.2% of study cohort had a completely healed amputation site. Conclusion In conclusion, this study highlighted high re-intervention, re-amputation and new ulceration rates. Strategies to improves these outcomes in such high-risk patients are warranted.

scholarly journals Factors associated with physician prescribing behavior of dipeptidyl peptidase-4 inhibitors for type 2 diabetes in the US outpatient population

2017 ◽  
Vol 6 (2) ◽  
pp. 59
Author(s):  
Xiaojing Ma ◽  
Chanhyun Park ◽  
Hsien-Chang Lin ◽  
Sweta Andrews ◽  
Jongwha Chang
Keyword(s):  
Type 2 Diabetes ◽  
Primary Care Physicians ◽  
Patient Characteristics ◽  
Prescribing Pattern ◽  
Dipeptidyl Peptidase 4 ◽  
Prescribing Behavior ◽  
Factors Associated ◽  
Physician Characteristics ◽  
Physician Prescribing

Objective: Although the use of dipeptidyl peptidase-4 (DPP-4) inhibitors has been increasing after their first approval in 2006, little is known about their prescribing pattern. Therefore, the objective of this study is to evaluate the prescribing pattern of the DPP-4 inhibitors for the treatment of type 2 diabetes mellitus (T2DM) and examine sociological factors associated with physician prescribing behavior in the U.S. outpatient setting.Methods: This cross-sectional study was conducted utilizing data from the 2006-2010 National Ambulatory Medical Care Survey (NAMCS) and employed the Eisenberg model that explains physician decision making in the context of sociologic influences. For independent variables, the following characteristics were determined based on the Eisenberg model: patient characteristics, physician characteristics, the physician-health care system interaction, and the physician-patient relationship. The dependent variable was the use of DPP-4 inhibitors. Multivariate logistic regressions were used for analyses.Results: The estimated population size was 535,158,796 patients during five years, and 3.85% of them were prescribed DPP-4 inhibitors. Among the patient characteristic-related factors, the odds of the use of DPP-4 inhibitors was 73% lower in patients with Medicaid compared to patients with private insurance (OR = 0.27; 95% CI, 0.08-0.88; p = .030). For the physician characteristic-related factor, the odds of prescribing DPP-4 inhibitors for primary care physicians are about 86% higher than the odds for non-primary care physicians (OR = 1.86; 95% CI, 1.17-2.95; p = .008). In addition, physicians in private offices were 3.01 times more likely to prescribe DPP-4 inhibitors than physicians in the health maintenance organizations (HMO) (OR = 3.01; 95% CI, 1.03-8.78; p = .043).Conclusions: Patient characteristics, physician characteristics, and the physician’s relationship with the health care system were associated with an increased use of DPP-4 inhibitors. However, the physician’s relationship with the patient was not associated with an increased use of DPP-4 inhibitors.

Heart failure with reduced, mid-range and preserved left ventricular ejection fraction in Chinese with type 2 diabetes: risk factors and prognosis from time of first index hospitalization

2021 ◽  
Author(s):  
Andrea O.Y Luk ◽  
Xinge Zhang ◽  
Erik Fung ◽  
Hongjiang Wu ◽  
Eric S.H Lau ◽  
...  
Keyword(s):  
Heart Failure ◽  
Type 2 Diabetes ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Clinical Factors ◽  
Ventricular Ejection Fraction ◽  
Factors Associated ◽  
One Year

Abstract BackgroundThe clinical predictors and prognosis of heart failure (HF) by categories of left ventricular ejection fraction (LVEF) have not been well studied in people with diabetes. In a retrospective cohort of Chinese with type 2 diabetes, we examined 1) clinical factors associated with incident decompensated HF, and 2) mortality post-HF, stratified by LVEF.MethodsWe conducted a retrospective analysis of the Hong Kong Diabetes Register comprising 23,348 people with type 2 diabetes without history of HF enrolled between 1993–2015, followed for incident decompensated HF until 2017. Heart failure subtypes were defined according to LVEF on echocardiography. Multivariate Cox proportional hazards models were used to identify clinical factors associated with incident HF versus no HF, stratified by HF subtypes. All-cause mortality rates were compared by HF subtypes.ResultsOver median follow-up of 7.1 years from enrolment, 1,195 (5.1%) people developed decompensated HF. Among 611 (51.1%) people with echocardiography, 24.1% had HF with reduced LVEF (HFrEF) (LVEF < 40%), 15.2% had HF with mid-range LVEF (HFmrEF) (LVEF 41–49%), and 60.7% had HF with preserved LVEF (HFpEF) (LVEF ≥ 50%). Old age, low GFR, albuminuria and coronary artery disease were associated with increased hazards for all HF subtypes. During median follow-up of 2.1 years post-HF, 760 (63.6%) people died. One-year mortality rate was lower in people with HFpEF (16.2%) than those with HFmrEF (vs 26.9%,p = 0.034) and HFrEF (vs 31.3%,p < 0.001). At 10 years, mortality rates in HFpEF group (58.0%) remained lower than HFmrEF group (vs 71.0%,p = 0.38), but similar to HFrEF group (vs 55.8%,p = 0.651).ConclusionsIn Chinese with type 2 diabetes, HFpEF was the predominant HF subtype. One-year mortality following decompensated HF was lowest in HFpEF group but 10-year mortality was similar between HFpEF and HFrEF.

scholarly journals Factors associated with missed appointments by adults with type 2 diabetes mellitus: a systematic review

2021 ◽  
Vol 9 (1) ◽  
pp. e001819
Author(s):  
Chun-An Sun ◽  
Kathryn Taylor ◽  
Scott Levin ◽  
Susan M Renda ◽  
Hae-Ra Han
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Significant Proportion ◽  
Patient Characteristics ◽  
Future Research ◽  
Missed Appointments ◽  
Factors Associated ◽  
Interpersonal Factors

Keeping regular medical appointments is a key indicator of patient engagement in diabetes care. Nevertheless, a significant proportion of adults with type 2 diabetes mellitus (T2DM) miss their regular medical appointments. In order to prevent and delay diabetes-related complications, it is essential to understand the factors associated with missed appointments among adults with T2DM. We synthesized evidence concerning factors associated with missed appointments among adults with T2DM. Using five electronic databases, including PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, PsycINFO and Web of Science, a systematic literature search was done to identify studies that describe factors related to missed appointments by adults with T2DM. A total of 18 articles met the inclusion criteria. The majority of studies included in this review were cohort studies using medical records. While more than half of the studies were of high quality, the operational definitions of missed appointments varied greatly across studies. Factors associated with missed appointments were categorized as patient characteristics, healthcare system and provider factors and interpersonal factors with inconsistent findings. Patient characteristics was the most commonly addressed category, followed by health system and provider factors. Only three studies addressed interpersonal factors, two of which were qualitative. An increasing number of people live with one or more chronic conditions which require more careful attention to patient-centered care and support. Future research is warranted to address interpersonal factors from patient perspectives to better understand the underlying causes of missed appointments among adults with T2DM.

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