The Endocrine Pathology Society working group included 24 experienced thyroid pathologists (representing 7 countries and 4 continents), 2 endocrinologists, 1 surgeon, and 1 psychiatrist. In addition, a molecular pathologist, a biostatistician, and a thyroid cancer survivor/patient advocate participated in the study.
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Endocrinologists
Endocrinologists
Endocrinologists are medical professionals who specialize in diagnosing and treating disorders of the endocrine system, which includes the glands and hormones that regulate vital bodly functions.
They utilize advanced knowledge of hormonal pathways and metabolism to manage conditions like diabetes, thyroid disorders, growth and sexual development issues, and more.
Endocrinologists play a crucial role in optimizing patient care through precision medicine, cutting-edge research, and personalized treatment plans.
With their expertise in endocrinology, they help patients achieve optimal health and wellbeing.
PubCompare.ai is an invaluable tool that empowers endocrinologists to streamline their research protocols, enhancing the reproducibility and accuracy of their important work.
They utilize advanced knowledge of hormonal pathways and metabolism to manage conditions like diabetes, thyroid disorders, growth and sexual development issues, and more.
Endocrinologists play a crucial role in optimizing patient care through precision medicine, cutting-edge research, and personalized treatment plans.
With their expertise in endocrinology, they help patients achieve optimal health and wellbeing.
PubCompare.ai is an invaluable tool that empowers endocrinologists to streamline their research protocols, enhancing the reproducibility and accuracy of their important work.
Most cited protocols related to «Endocrinologists»
Cancer Survivors
Carcinoma, Thyroid
Endocrinologists
Pathologists
Patients
Psychiatrist
Surgeons
Survivors
System, Endocrine
Thyroid Gland
Youth and their parents were recruited from an ambulatory diabetes program at a tertiary academic pediatric hospital. The hospital serves an urban and rural population of 1.3 million in Eastern Ontario, Canada; the diabetes program provides care for 850 children and youth with T1D. At the time of the study in 2013–2015, MDI was rarely used by children or youth in our centre. Since then, MDI has become the usual insulin delivery method from diagnosis onwards.
We recruited youth and parents who had told either their pediatric endocrinologist or pediatric diabetes physician during their regular diabetes clinic visit that they were considering a change in insulin delivery method, were capable of participating in the decision making process and were scheduled for decision coaching by one of our diabetes social workers which is a step in the process for youth in our clinic who are considering a change in insulin delivery method. To be eligible for this study, youth had to be under 18 years old with type 1 diabetes duration of at least 10 months, and they and their parents had to be able to read and speak English or French. No lower age limit was set for youth participants, as required by our Research Ethics Boards, provided the youth and parent(s) could participate in the consent or assent process. Family dyads (youth and one parent) and family triads (youth and two parents) were included. The study was introduced to youth and parents being scheduled for decision coaching by the administrative assistant for the diabetes team. A research assistant contacted those who expressed interest in the study. This contact was by telephone to assess study eligibility and explain the study in detail. Youth and parents, regardless of the youth’s age, who agreed to participate provided written informed consent, and assent by the youth if necessary, prior to the decision coaching.
We recruited youth and parents who had told either their pediatric endocrinologist or pediatric diabetes physician during their regular diabetes clinic visit that they were considering a change in insulin delivery method, were capable of participating in the decision making process and were scheduled for decision coaching by one of our diabetes social workers which is a step in the process for youth in our clinic who are considering a change in insulin delivery method. To be eligible for this study, youth had to be under 18 years old with type 1 diabetes duration of at least 10 months, and they and their parents had to be able to read and speak English or French. No lower age limit was set for youth participants, as required by our Research Ethics Boards, provided the youth and parent(s) could participate in the consent or assent process. Family dyads (youth and one parent) and family triads (youth and two parents) were included. The study was introduced to youth and parents being scheduled for decision coaching by the administrative assistant for the diabetes team. A research assistant contacted those who expressed interest in the study. This contact was by telephone to assess study eligibility and explain the study in detail. Youth and parents, regardless of the youth’s age, who agreed to participate provided written informed consent, and assent by the youth if necessary, prior to the decision coaching.
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Child
Diabetes Mellitus
Diabetes Mellitus, Insulin-Dependent
Diagnosis
Eligibility Determination
Endocrinologists
Insulin
Obstetric Delivery
Parent
Physicians
Rural Population
Triad resin
Youth
Bariatric Surgery
Clinical Protocols
Endocrinologists
Obesity
Patients
ARID1A protein, human
Beckwith-Wiedemann Syndrome
Conferences
Diagnosis
Endocrinologists
Face
Molecular Diagnostics
Nephrologists
Oncologists
Patient Representatives
Patients
Surgeons
We then began an iterative process to distinguish between type 1 and type 2 diabetes within the population of patients flagged by the general diabetes algorithm in Table 1 . We started with a “straw man” algorithm designed to coarsely divide the population into pools of patients more likely to have type 1 and patients more likely to have type 2. We began with this preliminary algorithm in order to make chart reviews more efficient: type 1 diabetes is so rare compared with type 2 diabetes that random sampling of unselected patients yields very few type 1 cases. The straw man algorithm allowed us to enrich a study population with type 1 diabetes. A case of type 1 was defined as any patient with ICD-9 250.x1 or 250.x3 on two or more occasions, a current prescription for insulin, and no prescriptions for oral hypoglycemics at any time. A case of type 2 was defined as any patient with ICD-9 250.x0 or 250.x2 on two or more occasions or a prescription for an oral hypoglycemic at any time.
We randomly selected 210 charts classified by the straw man algorithm for review: 70 patients classified as type 1, 60 classified as type 2, and 80 left unclassified by the straw man algorithm. Charts were reviewed for diabetes using ADA diagnostic criteria and for diabetes type (8 (link)). We used the following rules to assign “true” diabetes type (applied sequentially): endocrinologist diagnosis if available, never on insulin (classify as type 2), C-peptide negative or diabetes autoantibodies present (classify as type 1), currently on insulin but prior history of prolonged treatment with oral hypoglycemic alone (classify as type 2), and nonendocrinologist physician diagnosis.
We then created a series of candidate algorithms based on ICD-9 code frequencies, laboratory test results, and suggestive prescriptions to optimize sensitivity for chart-confirmed type 1 diabetes while maintaining high positive predictive values. Patients who did not fulfill algorithm criteria for type 1 diabetes were presumptively classified as type 2. The study endocrinologist (E.E.) and internist (M.K.) created the candidate algorithms based on clinical knowledge of diabetes management practices.
We calculated the sensitivity and positive predictive value of all candidate algorithms using inverse-probability weighting to correct for the sampling strategy. We generated 95% CIs for these estimates using Monte Carlo simulations. Specifically, we simulated the number of true type 1 and type 2 patients among reviewed charts for each sampling strata (straw man type 1, straw man type 2, and straw man unclassified) using multinomial distributions and probabilities estimated from the observed data. We repeated this process 1 million times and derived 95% CIs from the resulting 2.5 and 97.5 percentiles. Calculations were executed using SAS version 9.3 (SAS Institute, Cary, NC).
We then created a final algorithm with optimized sensitivity and positive predictive value for type 1 diabetes by combining the candidate algorithms with the highest positive predictive values using “or” statements. We focused the optimized algorithm on sensitivity to type 1 diabetes because even slight misclassification of type 1 patients as type 2 is substantially magnified after weighting for the greater size of the type 2 population and therefore exerts considerable cost in net sensitivity for type 1.
We randomly selected 210 charts classified by the straw man algorithm for review: 70 patients classified as type 1, 60 classified as type 2, and 80 left unclassified by the straw man algorithm. Charts were reviewed for diabetes using ADA diagnostic criteria and for diabetes type (8 (link)). We used the following rules to assign “true” diabetes type (applied sequentially): endocrinologist diagnosis if available, never on insulin (classify as type 2), C-peptide negative or diabetes autoantibodies present (classify as type 1), currently on insulin but prior history of prolonged treatment with oral hypoglycemic alone (classify as type 2), and nonendocrinologist physician diagnosis.
We then created a series of candidate algorithms based on ICD-9 code frequencies, laboratory test results, and suggestive prescriptions to optimize sensitivity for chart-confirmed type 1 diabetes while maintaining high positive predictive values. Patients who did not fulfill algorithm criteria for type 1 diabetes were presumptively classified as type 2. The study endocrinologist (E.E.) and internist (M.K.) created the candidate algorithms based on clinical knowledge of diabetes management practices.
We calculated the sensitivity and positive predictive value of all candidate algorithms using inverse-probability weighting to correct for the sampling strategy. We generated 95% CIs for these estimates using Monte Carlo simulations. Specifically, we simulated the number of true type 1 and type 2 patients among reviewed charts for each sampling strata (straw man type 1, straw man type 2, and straw man unclassified) using multinomial distributions and probabilities estimated from the observed data. We repeated this process 1 million times and derived 95% CIs from the resulting 2.5 and 97.5 percentiles. Calculations were executed using SAS version 9.3 (SAS Institute, Cary, NC).
We then created a final algorithm with optimized sensitivity and positive predictive value for type 1 diabetes by combining the candidate algorithms with the highest positive predictive values using “or” statements. We focused the optimized algorithm on sensitivity to type 1 diabetes because even slight misclassification of type 1 patients as type 2 is substantially magnified after weighting for the greater size of the type 2 population and therefore exerts considerable cost in net sensitivity for type 1.
Autoantibodies
C-Peptide
Diabetes Mellitus
Diabetes Mellitus, Insulin-Dependent
Diabetes Mellitus, Non-Insulin-Dependent
Diagnosis
Endocrinologists
Hypersensitivity
Hypoglycemic Agents
Insulin
Multiple Endocrine Neoplasia Type 1
Multiple Endocrine Neoplasia Type 2a
Patients
Physicians
Prescriptions
SOCS2 protein, human
Most recents protocols related to «Endocrinologists»
Two hundred and ten individuals were willing to join this study (May 10, 2021, to July 1, 2022). The exclusion criteria for the two groups were as follows: type 1 diabetes mellitus, impaired fasting glucose or impaired glucose tolerance58 (link), hypertension, hypoglycemia (blood sugar levels < 3.9 mmol/L), hyperlipidemia, serious eye diseases (e.g., blindness), symptoms of neurological conditions (e.g., cerebral infarction or hemorrhage), history of neurological abnormality (e.g., Parkinson’s disease), severe head injuries or chronic head discomfort (e.g., migraine), BMI > 31 kg/m2, left- or mixed-handedness, substance (tobacco, alcohol, or psychoactive drug) abuse, taking medications that may affect cognition and memory within 6 months, specific abnormalities detected on conventional MRI scans or any other factors that may influence brain structure or function (e.g., extreme physical weakness, chronic infections, and other endocrine diseases). Patients with T2DM were diagnosed by two experienced endocrinologists following international clinical standards59 . MCI was evaluated via Mini-Mental State Examination (MMSE) and MoCA-B (21 ≤ MoCA-B score < 26, and MMSE score > 24 were diagnosed with MCI)60 ,61 (link).
Participants with brain tumors (n = 3), neuropsychiatric diseases (n = 4) (e.g., major depression or schizophrenia), or developmental disorders (n = 4) were excluded. Finally, 37 patients with T2DM-MCI, 93 patients with T2DM-NCI, and 69 NC were enrolled in this study. The source of patients with T2DM and NC corresponded with our previous study37 (link). This study was approved by the ethics committee of The First Affiliated Hospital of Guangzhou University of Chinese Medicine (ID: NO. JY [2020] 288). Written informed consent was obtained from all participants. In addition, the study was conducted following approved guidelines.
Participants with brain tumors (n = 3), neuropsychiatric diseases (n = 4) (e.g., major depression or schizophrenia), or developmental disorders (n = 4) were excluded. Finally, 37 patients with T2DM-MCI, 93 patients with T2DM-NCI, and 69 NC were enrolled in this study. The source of patients with T2DM and NC corresponded with our previous study37 (link). This study was approved by the ethics committee of The First Affiliated Hospital of Guangzhou University of Chinese Medicine (ID: NO. JY [2020] 288). Written informed consent was obtained from all participants. In addition, the study was conducted following approved guidelines.
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Asthenia
Blindness
Blood Glucose
Brain
Brain Neoplasms
Cerebral Infarction
Chinese
Chronic Infection
Cognition
Congenital Abnormality
Craniocerebral Trauma
Developmental Disabilities
Diabetes Mellitus, Insulin-Dependent
Drug Abuse
Endocrine System Diseases
Endocrinologists
Ethanol
Ethics Committees, Clinical
Eye Disorders
Glucose
Head
Hemorrhage
High Blood Pressures
Hyperlipidemia
Hypoglycemia
Major Depressive Disorder
Memory
Migraine Disorders
Mini Mental State Examination
MRI Scans
Nervous System Abnormality
Nervous System Disorder
Patients
Pharmaceutical Preparations
Physical Examination
Psychotropic Drugs
Schizophrenia
Tobacco Products
The diagnosis of anal fistula is based on the German S3 guidelines: anal abscess and fistula (23 (link)). All patients were diagnosed with anal fistula by anal finger examination, anoscope examination, radiographic examination (including rectal endoluminal ultrasound, pelvic CT, or MRI), or intraoperative probe/methylene blue staining, and the number of internal orifices was counted by these techniques. The diagnostic criteria for T2DM were based on the latest Chinese guidelines for the prevention and treatment of T2DM set by the Chinese Diabetes Society (24 (link), 25 (link)). And the diagnosis was assigned by an endocrinologist. Relevant data were collected on the cases, including demographic characteristics, clinical features, laboratory and ancillary tests at admission, anal fistula-related information (e.g., previous surgical history, anal fistula types, number of internal orifices, etc.), pre- and post-surgical treatments, and surgical modalities. Non-healing (refractory) group refers to trauma that cannot be repaired in time with conventional therapy or wounds that can not achieve functional recovery and anatomical integrity (26 (link)). The last routine dressing change time in the outpatient clinic was collected as the outcome indicator. Judged by the specialist anorectologist and the definition of the relevant literature, patients were divided into the non-healing (refractory) group or healing group according to whether its recovery period is longer than 35 days (27 (link)–29 (link)).
Among the underlying diseases, hypertensive disease and non-alcoholic fatty liver diseases are listed independently. Chronic cardiovascular diseases included coronary atherosclerotic heart disease and lacunar cerebral infarction. Chronic lung diseases included tuberculosis, chronic obstructive pulmonary disease, and chronic pulmonary heart disease. Chronic liver diseases included chronic viral hepatitis B, cirrhosis of the liver, hepatic hemangioma, etc.
Among the underlying diseases, hypertensive disease and non-alcoholic fatty liver diseases are listed independently. Chronic cardiovascular diseases included coronary atherosclerotic heart disease and lacunar cerebral infarction. Chronic lung diseases included tuberculosis, chronic obstructive pulmonary disease, and chronic pulmonary heart disease. Chronic liver diseases included chronic viral hepatitis B, cirrhosis of the liver, hepatic hemangioma, etc.
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Abscess
Anal Fistula
Anus
Cardiovascular Diseases
Cardiovascular System
Chinese
Chronic Obstructive Airway Disease
Coronary Arteriosclerosis
Cor Pulmonale
Diabetes Mellitus
Diagnosis
Disease, Chronic
Endocrinologists
Fingers
Fistula
Heart
Hemangioma
Hepatitis B, Chronic
High Blood Pressures
Hospital Admission Tests
Liver
Liver Cirrhosis
Liver Diseases
Lung
Lung Diseases
Methylene Blue
Non-alcoholic Fatty Liver Disease
Operative Surgical Procedures
Patients
Pelvis
Recovery of Function
Rectum
Stroke, Lacunar
Therapeutics
Tuberculosis
Ultrasonics
Wounds
Wounds and Injuries
X-Rays, Diagnostic
Based on institutional protocol, DM patients were prepared at preoperative admission period by 1) endocrinologist consultation if random BG >250 or <70 mg/dL on admission, 2) nothing per oral (NPO) order after midnight for case scheduled at 8.30 am, 3) discontinuation of oral hypoglycemic drugs (OHG) in the morning of the surgery day, and 4) insulin would be given if POCT-glucose >300 mg/dL in the morning of the surgery day, and 5) 5% dextrose solution infusion if surgery delay after 10 am.
Endocrinologists
Glucose
Hypoglycemic Agents
Insulin
Operative Surgical Procedures
Patients
Surgery, Day
The structured pre-coded questionnaire was built in Arabic language by an expert endocrine researcher. The questionnaire was available in both a paper form and an electronic Google form. The latter was used whenever possible; this was achieved either by sending the QR code through social media or through its direct scanning. The questionnaire was pilot tested through initial enrollment of 100 subjects and then revised by the endocrinologist, dietician, and a statistician member of the research team.
The first section of the questionnaire consisted of questions concerning sociodemographic data (age and marital status), smoking, menstrual and obstetric history, history of osteoporosis or fractures, vitamin D deficiency or previous intake of vitamin D and/or calcium, and family history of osteoporosis and/or fractures.
The second section included the type and frequency of different physical activities (including walking, running, using the stairs, home activities, cycling, moderate- and high-intensity sports, and self-defense and body-building sports). This section also asked about the time spent sitting or lying down while socializing, watching TV, or using smartphones or computers.
The third section was concerned with food consumption questions for dairy products. Participants gave the frequency of their daily intake of milk, yogurt, and/or natural or processed cheese. Less than three daily servings of dairy products were considered a low intake (as per the Dietary Guidelines Advisory Committee).8
The first section of the questionnaire consisted of questions concerning sociodemographic data (age and marital status), smoking, menstrual and obstetric history, history of osteoporosis or fractures, vitamin D deficiency or previous intake of vitamin D and/or calcium, and family history of osteoporosis and/or fractures.
The second section included the type and frequency of different physical activities (including walking, running, using the stairs, home activities, cycling, moderate- and high-intensity sports, and self-defense and body-building sports). This section also asked about the time spent sitting or lying down while socializing, watching TV, or using smartphones or computers.
The third section was concerned with food consumption questions for dairy products. Participants gave the frequency of their daily intake of milk, yogurt, and/or natural or processed cheese. Less than three daily servings of dairy products were considered a low intake (as per the Dietary Guidelines Advisory Committee).8
Calcium, Dietary
Cheese
Dairy Products
Dietitian
Endocrinologists
Ergocalciferol
Food
Fracture, Bone
Menstruation
Milk, Cow's
Osteoporosis
System, Endocrine
Vitamin D Deficiency
Yogurt
A broad sample of health facilities, patients and health workers was purposively recruited to capture maximum variation of the phenomenon under study [42 ]. Participating health facilities involved three public hospitals (one primary, one tertiary and one specialized teaching hospitals), one private general hospital and two private specialized clinics that provide long-term NCDs care.
Nineteen patient participants with two or more chronic NCDs were purposively selected with the aim to satisfy maximum variation sampling method based on the nature of chronic conditions the patients are living with, sex, age and residence (Table1 ). For the service providers, six medical doctors (2 GPs, 1 internist, 1 cardiologist, 1 endocrinologist and 1 internal medicine resident) and three nurses working in chronic outpatient care departments were recruited. The two sub-specialists (cardiologist and endocrinologist) and one nurse were working in both public and private health facilities, while the rest were working in public hospitals only.
Nineteen patient participants with two or more chronic NCDs were purposively selected with the aim to satisfy maximum variation sampling method based on the nature of chronic conditions the patients are living with, sex, age and residence (Table
Characteristics of patient participants Bahir Dar, Ethiopia
| Sex | Age | Facility | Number and types of conditions | Duration of living with the disease/s (years) |
|---|---|---|---|---|
| Female | 50 | Public specialized teaching hospital | 3 (HPN, KD, Gastritis) | 13 |
| Female | 75 | Public specialized teaching hospital | 3(HPN, heart problem and RA) | 16 |
| Male | 50 | Public specialized hospital | 2(DM, HPN) | 6 |
| Female | 55 | Public specialized hospital | 3(HPN, DM and hypercholesteremia) | 7 |
| Male | 79 | Public specialized hospital | 3(HPN,DM &KD) | 30 |
| Male | 74 | Public specialized hospital | 3(HPN, DM and hypercholesteremia) | 17 |
| Female | 39 | Public specialized teaching hospital | 3(HPN, HD, TB) | 2.5 |
| Female | 50 | Public specialized teaching hospital | 4(HPN, HF, RA, Asthma | 2 |
| Male | 66 | Public specialized teaching hospital | 3(DM,HPN, HD) | 15 |
| Male | 52 | Public primary level hospital | 2(HPN, BPH) | 8 |
| Male | 48 | Private general hospital | 3(HPN, DM, RF) | 24 |
| Female | 50 | Public primary level hospital | 2(HPN, DM) | 1 |
| Female | 66 | Public primary level hospital | 2(HPN, DM) | 4 |
| Male | 45 | Private general hospital | 2(HPN,DM) | 5 |
| Female | 54 | Private specialized medical center | 3(DM, HPN and hypercholestremia) | 21 |
| Female | 60 | Private specialized medical center | 2(HPN, DM) | 18 |
| Male | 75 | Private specialized clinic | 2(HPN, HD) | 7 |
| Male | 45 | Public specialized hospital | 2(HPN, DM) | 8 |
| Male | 58 | Public specialized hospital | 2(HPN, DM) | 3 |
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Cardiologists
Chronic Condition
Endocrinologists
Follow-Up Care
Gastritis
Health Personnel
Heart
Hypercholesterolemia
Long-Term Care
Nurses
Outpatients
Patients
Physicians
Specialists
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More about "Endocrinologists"
Endocrinologists are highly specialized medical professionals who focus on diagnosing, managing, and treating disorders related to the endocrine system.
This complex system of glands and hormones plays a crucial role in regulating vital bodily functions such as metabolism, growth, development, and sexual function.
With their advanced knowledge of hormonal pathways and metabolic processes, endocrinologists utilize cutting-edge diagnostic tools like the Harpenden stadiometer, Optium Xceed Blood Glucose and Ketone Monitoring System, Acuson Antares, and HDI 5000 to precisely evaluate and monitor their patients' conditions.
They leverage data analysis software like SAS version 9.4 and SAS statistical software to inform their personalized treatment plans, which may involve medication management, lifestyle interventions, and the latest advancements in endocrine-related therapies.
Endocrinologists play a vital role in managing a wide range of hormonal disorders, including diabetes, thyroid conditions, growth and sexual development issues, and more.
By optimizing patient care through precision medicine and evidence-based practices, they help individuals achieve optimal health and wellbeing.
Tools like PubCompare.ai empower endocrinologists to streamline their research protocols, enhancing the reproducibility and accuracy of their important work, which is crucial for advancing the field of endocrinology and improving patient outcomes.
Whether using a Standard scale or the MyLab Twice system, endocrinologists leverage the latest technologies and techniques to provide comprehensive, personalized care for their patients, always striving to help them reach their optimal health and wellness goals.
This complex system of glands and hormones plays a crucial role in regulating vital bodily functions such as metabolism, growth, development, and sexual function.
With their advanced knowledge of hormonal pathways and metabolic processes, endocrinologists utilize cutting-edge diagnostic tools like the Harpenden stadiometer, Optium Xceed Blood Glucose and Ketone Monitoring System, Acuson Antares, and HDI 5000 to precisely evaluate and monitor their patients' conditions.
They leverage data analysis software like SAS version 9.4 and SAS statistical software to inform their personalized treatment plans, which may involve medication management, lifestyle interventions, and the latest advancements in endocrine-related therapies.
Endocrinologists play a vital role in managing a wide range of hormonal disorders, including diabetes, thyroid conditions, growth and sexual development issues, and more.
By optimizing patient care through precision medicine and evidence-based practices, they help individuals achieve optimal health and wellbeing.
Tools like PubCompare.ai empower endocrinologists to streamline their research protocols, enhancing the reproducibility and accuracy of their important work, which is crucial for advancing the field of endocrinology and improving patient outcomes.
Whether using a Standard scale or the MyLab Twice system, endocrinologists leverage the latest technologies and techniques to provide comprehensive, personalized care for their patients, always striving to help them reach their optimal health and wellness goals.