Impact of Deferred Clinic Visits on Patients With Cardiovascular Comorbidities: A Prospective Cohort Study
NCT ID: NCT07050407
Last Updated: 2025-07-03
Study Results
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Basic Information
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COMPLETED
458 participants
OBSERVATIONAL
2020-04-01
2024-06-30
Brief Summary
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Detailed Description
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Method This single-centre, prospective cohort study compared CVRF control between patients who deferred their physical clinic visit and those who attended as scheduled. The study protocol was approved by the Jointed Chinese University of Hong Kong and North Territory East Cluster Clinical Research Ethic Committee. All patients provided written informed consent data collection. This study followed The Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines for cohort studies reporting.
Setting This study was conducted at the Medical Specialist Outpatient Clinics of the Prince of Wales Hospital, a tertiary regional teaching hospital in Hong Kong, from April 2020 to January 2022. This timeframe was selected to coincide with the implementation of the Drug Refilling Clinic Scheme during the COVID-19 pandemic, which allowed patients to voluntarily defer their scheduled clinic visits while receiving medications from their last prescription for their chronic conditions via postal delivery. Data was collected from clinical notes and the electronic health records.
Participants Patients were recruited if they have at least one of three CVRF: diabetes, hypertension, or dyslipidaemia. Patient newly diagnosed with these conditions were excluded. Additionally, unstable patients defined as those with a history of hospitalization or emergency department visit within the preceding three months, those with complex medical problems indicated by a Charlson Comorbidity Index (CCI)(11) of equal or greater than five, or those whose primary medical issues were unrelated to cardiovascular disease - were excluded. Patients who defaulted their subsequent follow-up appointments with no recorded clinic visit by the end of the study period were also excluded. The study flow is summarized in figure 1.
Patients who deferred their appointment were categorized into the 'deferred' group, while those who attended their appointment as scheduled were placed in the 'control' group. Patients in the deferred group received a prescription refill by post along with a new appointment date. They were instructed to seek medical attention if they experienced any health concerns between follow-up intervals. Routine Blood test including lipid profile, HbA1c and other standard assessments, were conducted at the time of their next clinic visit. Additionally, they were instructed to monitor and record their blood pressure and glucose level at home with these records reviewed during the new follow-up appointments. Patients in the control group followed the standard local practice of clinic visits at intervals of 3 to 6 months. These patients were randomly selected from the list of clinic attendees and screened for eligibility at a 2:1 ratio to the 'deferred' group. A 2:1 ratio was used as more patients attended their scheduled visits than deferring. Similar blood test was performed during each clinic visit, as in the deferred group.
Variables Information on medications, blood tests result, and office blood pressure readings were recorded during each clinic visits. The baseline for subject in the control group was established at the time of the scheduled clinic visit (time 0). Since only subjects in the control group attended the clinic, the baseline for subjects in the deferred group was derived from their last recorded clinic visit before recruitment. Data from two subsequent physical clinic visits were collected in both groups (time 1 and time 2). Two follow-up visits were used instead of one for both groups to allow the second clinic visit to serve as an internal control.
Outcome measures The primary outcome was uncontrolled CVRF, defined as the presence of any of the following: uncontrolled DM with HbA1c \>7%, uncontrolled hypertension with office systolic blood pressure (SBP)\>130mmHg and/or diastolic blood pressure (DBP) \>80mmHg, or uncontrolled dyslipidaemia defined as low-density-lipoprotein (LDL) \>1.8mmol/L. The primary safety outcomes are the composite endpoints of unscheduled hospitalization, hospitalization due to cardiovascular events, and/or major adverse cardiovascular events (MACE) which included acute coronary syndrome, myocardial infarction, ischemic stroke and death within the study period. The secondary endpoints are changes in HbA1c level, Low density lipid (LDL) level and office blood pressure reading from baseline (time 0) to time 1 and to time 2. In addition, a clinic satisfaction questionnaire (CSQ) was administered to a subset of patients, and satisfaction scores were compared between the two groups.
Sample Size and Statistical Method We based the sample size calculation on establishing non-inferiority of deferred group over control group. The prevalence of uncontrolled HbA1c, LDL and hypertension was estimated to be 60%, 30%, and 60% respectively (12-14). Assuming 80% of power and one-side α = 0.025, a sample size of 432 patients- with 288 patients in the control group and 144 patients in the deferred group - would be required to demonstrate non-inferiority in the deferred group, with inferior margin set at an absolute difference of 5% point.
Continuous variables will be reported using descriptive statistics i.e. mean, median, and standard deviation. Qualitative variable will be summarized in frequency and percentage. T-test or sign rank test will be used for comparison between continuous variables, and chi-square or Fisher's exact test will be used for comparison of categorical variables between groups.
Kaplan-Meier method will be used for primary safety outcomes analysis and estimate time-to-event distributions between the two arms. The log-rank test will be used for comparison. Time 0 was set as the baseline clinic visit in the control group, or last recorded clinic visit in the deferred group. Follow-up end date was set at the occurrence of primary safety outcomes or 1 year from time 2, whichever occurs earlier.
Univariate logistic regression will first be performed to identified individual variable associated with primary outcomes and primary safety outcomes. Those variables with significant association with the primary outcome (defined as a two-tailed p value \<0.05) was entered into the Multivariate logistic regression analysis. The final multivariate model was then constructed by backward deletion of the least significant characteristic, until all remaining variables were significantly associated with the endpoint (p \< 0.05). This final model will be then assessed in a separate validation cohort which by calculating the area under the receiver-operating-characteristic (ROC) curve (AUC). A perfect model will have an AUC =1, while a worthless model will have an AUC of 0.5. Statistic analysis was performed using STATA and R software.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Deferred
Patients who deferred their appointment
No interventions assigned to this group
Control
patients who attended their appointment as scheduled
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
2. Patients who are followed up at the clinics for at least 1 CV risk factors, namely diabetes, hypertension, dyslipidaemia, or history of vascular events including cerebrovascular accidence, ischemic heart disease or peripheral vascular disease.
Exclusion Criteria
2. Unstable patients such as patients with recent hospitalization within 3 months to the interviewing date
3. Patients with complex medical problems indicated by Charlson Comorbidity Index of equal or more than 5
4. Patients whose active medical problems are not cardiovascular related
5. Patient who are taking vitamin K antagonist
6. Patients who defaulted their follow-up appointment with no new appointment on record.
19 Years
ALL
No
Sponsors
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Chinese University of Hong Kong
OTHER
Responsible Party
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GuangMing Tan
assistant professor
Locations
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Prince of Wales Hospital
Hong Kong, Shatin, Hong Kong
Countries
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References
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Singh GM, Danaei G, Farzadfar F, Stevens GA, Woodward M, Wormser D, Kaptoge S, Whitlock G, Qiao Q, Lewington S, Di Angelantonio E, Vander Hoorn S, Lawes CM, Ali MK, Mozaffarian D, Ezzati M; Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group; Asia-Pacific Cohort Studies Collaboration (APCSC); Diabetes Epidemiology: Collaborative analysis of Diagnostic criteria in Europe (DECODE); Emerging Risk Factor Collaboration (ERFC); Prospective Studies Collaboration (PSC). The age-specific quantitative effects of metabolic risk factors on cardiovascular diseases and diabetes: a pooled analysis. PLoS One. 2013 Jul 30;8(7):e65174. doi: 10.1371/journal.pone.0065174. Print 2013.
Global Burden of Metabolic Risk Factors for Chronic Diseases Collaboration. Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factors from 1980 to 2010: a comparative risk assessment. Lancet Diabetes Endocrinol. 2014 Aug;2(8):634-47. doi: 10.1016/S2213-8587(14)70102-0. Epub 2014 May 16.
Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, de Ferranti S, Faiella-Tommasino J, Forman DE, Goldberg R, Heidenreich PA, Hlatky MA, Jones DW, Lloyd-Jones D, Lopez-Pajares N, Ndumele CE, Orringer CE, Peralta CA, Saseen JJ, Smith SC Jr, Sperling L, Virani SS, Yeboah J. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019 Jun 18;139(25):e1082-e1143. doi: 10.1161/CIR.0000000000000625. Epub 2018 Nov 10.
Davies MJ, D'Alessio DA, Fradkin J, Kernan WN, Mathieu C, Mingrone G, Rossing P, Tsapas A, Wexler DJ, Buse JB. Management of Hyperglycemia in Type 2 Diabetes, 2018. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care. 2018 Dec;41(12):2669-2701. doi: 10.2337/dci18-0033. Epub 2018 Oct 4.
Whelton PK, Carey RM, Aronow WS, Casey DE Jr, Collins KJ, Dennison Himmelfarb C, DePalma SM, Gidding S, Jamerson KA, Jones DW, MacLaughlin EJ, Muntner P, Ovbiagele B, Smith SC Jr, Spencer CC, Stafford RS, Taler SJ, Thomas RJ, Williams KA Sr, Williamson JD, Wright JT Jr. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol. 2018 May 15;71(19):e127-e248. doi: 10.1016/j.jacc.2017.11.006. Epub 2017 Nov 13. No abstract available.
Sherman L, Pelter MA, Deamer RL, Duan L, Batech M. Association between encounter frequency and time to blood pressure control among patients with newly diagnosed hypertension: a retrospective cohort study. J Clin Hypertens (Greenwich). 2018 Mar;20(3):429-437. doi: 10.1111/jch.13223. Epub 2018 Feb 16.
Morrison F, Shubina M, Turchin A. Encounter frequency and serum glucose level, blood pressure, and cholesterol level control in patients with diabetes mellitus. Arch Intern Med. 2011 Sep 26;171(17):1542-50. doi: 10.1001/archinternmed.2011.400.
Related Links
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WHO Director-General's opening remarks at the Mission briefing on COVID-19 - 12 March 2020
Other Identifiers
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CUHK-NTEC CREC
Identifier Type: OTHER
Identifier Source: secondary_id
2020.159
Identifier Type: -
Identifier Source: org_study_id
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