THYROSIM App for Education and Research Predicts Potential Health Risks of Over-the-Counter Thyroid Supplements

A Systematic Review of Telehealth Applications in Endocrinology

Introduction

The prevalence of telehealth has witnessed a significant increase in various medical domains, especially in endocrinology. Telehealth brings about considerable advantages for both patients and health care professionals. However, despite these positive aspects, the growing prominence of telehealth is accompanied by certain challenges. This systematic review aims to assess the role of telehealth in endocrinology, including its applications, effectiveness, challenges, and implications for patient care.

Methods

This study involved a thorough search using comprehensive techniques across databases such as PubMed/Medline, Embase, and Scopus. The studies were selected for a tailored adaptation of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to enhance the clarity of our systematic review's reporting.

Results

This systematic review explores global telemedicine applications in endocrinology. Addressing various endocrine conditions, interventions utilize technology tools such as smartphones and applications, offering multifaceted utility from education and data gathering to screening and treatment. Notably, these interventions demonstrate adaptability during the COVID-19 pandemic. Positive outcomes include enhanced patient education, disease self-management, reduced complications, and improved glycemic control. However, drawbacks include the need for technical proficiency, perceived lower care quality, and potential privacy risks. These nuanced findings contribute to the discourse on telemedicine efficacy and limitations.

Conclusion

In conclusion, telehealth holds significant potential in transforming endocrine care. While there are challenges to its implementation, the benefits it offers underscore its value as a health care delivery model.

Thyroidkeeper: a healthcare management system for patients with thyroid diseases

Thyroid diseases, especially thyroid tumors, have a huge population in China. The postoperative patients, under China's incomplete tertiary diagnosis and treatment system, will frequently go to tertiary hospitals for follow-up and medication adjustment, resulting in heavy burdens on both specialists and patients. To help postoperative patients recover better against the above adverse conditions, a novel mobile application ThyroidKeeper is proposed as a collaborative AI-based platform that benefits both patients and doctors. In addition to routine health records and management functions, ThyroidKeeper has achieved several innovative points. First, it can automatically adjust medication dosage for patients during their rehabilitation based on their medical history, laboratory indicators, physical health status, and current medication. Second, it can comprehensively predict the possible complications based on the patient's health status and the health status of similar groups utilizing graph neural networks. Finally, the employing of graph neural network models can improve the efficiency of online communication between doctors and patients, help doctors obtain medical information for patients more quickly and precisely, and make more accurate diagnoses. The preliminary evaluation in both laboratory and real-world environments shows the advantages of the proposed ThyroidKeeper system.

Automatic Levothyroxine Dosing Algorithm for Patients Suffering from Hashimoto's Thyroiditis

Hypothyroidism is a condition where the patient's thyroid gland cannot produce sufficient thyroid hormones (mainly triiodothyronine and thyroxine). The primary cause of hypothyroidism is autoimmune-mediated destruction of the thyroid gland, referred to as Hashimoto's thyroiditis. A patient's desired thyroid hormone concentration is achieved by oral administration of thyroid hormone, usually levothyroxine. Establishing individual levothyroxine doses to achieve desired thyroid hormone concentrations requires several patient visits. Additionally, clear guidance for the dosing regimen is lacking, and significant inter-individual differences exist. This study aims to design a digital automatic dosing algorithm for patients suffering from Hashimoto's thyroiditis. The dynamic behaviour of the relevant thyroid function is mathematically modelled. Methods of automatic control are exploited for the design of the proposed robust model-based levothyroxine dosing algorithm. Numerical simulations are performed to evaluate the mathematical model and the dosing algorithm. With the help of the developed controller thyroid hormone concentrations of patients, emulated using Thyrosim, have been regulated under the euthyroid state. The proposed concept demonstrates reliable responses amidst varying patient parameters. Our developed model provides a useful basis for the design of automatic levothyroxine dosing algorithms. The proposed robust feedback loop contributes to the first results for computer-assisted thyroid dosing algorithms.

In silico dose adjustment of levothyroxine after total thyroidectomy using fuzzy logic methodology: A proof-of-concept study

Thyroid hormone replacement therapy is used to raise undesirably low concentrations of natural thyroid hormones, commonly by administrating levothyroxine (LT4). Finding the appropriate LT4 dose regime, particularly for patients undergone thyroidectomy, is still demanding more effort, and much research has been conducted. Providing a new fuzzy logic system, a useful control algorithm, we aim to introduce a proper LT4 dosing regimen for every thyroidectomized patient in a computerized environment. Consequently, we contrast the differences between our proposed dose regime and conventional monotherapy methods using THYROSIM, a thyroid simulation application. Considering our nine defined comparative criteria, results reveal that the FLS dose regime is dominant in terms of six indexes, while the discrepancies are not noticeable in the other three indexes. A great superiority of FLS dose regime is its ability to reduce the time to reach desirable thyrotropin (Thyroid Stimulating Hormone, TSH) serum concentration to 6 days post-thyroidectomy, and keep the T4, T3, and TSH values in the normal window afterward. The proposed FLS could be an applicable decision support system for physicians as they can define their intended Individual Target Value of TSH for each patient to optimize LT4 dose adjustment.

Optimized Replacement T4 and T4+T3 Dosing in Male and Female Hypothyroid Patients With Different BMIs Using a Personalized Mechanistic Model of Thyroid Hormone Regulation Dynamics

OBJECTIVE

A personalized simulation tool, p-THYROSIM, was developed (1) to better optimize replacement LT4 and LT4+LT3 dosing for hypothyroid patients, based on individual hormone levels, BMIs, and gender; and (2) to better understand how gender and BMI impact thyroid dynamical regulation over time in these patients.

METHODS

p-THYROSIM was developed by (1) modifying and refining THYROSIM, an established physiologically based mechanistic model of the system regulating serum T3, T4, and TSH level dynamics; (2) incorporating sex and BMI of individual patients into the model; and (3) quantifying it with 3 experimental datasets and validating it with a fourth containing data from distinct male and female patients across a wide range of BMIs. For validation, we compared our optimized predictions with previously published results on optimized LT4 monotherapies. We also optimized combination T3+T4 dosing and computed unmeasured residual thyroid function (RTF) across a wide range of BMIs from male and female patient data.

RESULTS

Compared with 3 other dosing methods, the accuracy of p-THYROSIM optimized dosages for LT4 monotherapy was better overall (53% vs. 44%, 43%, and 38%) and for extreme BMI patients (63% vs. ~51% low BMI, 48% vs. ~36% and 22% for high BMI). Optimal dosing for combination LT4+LT3 therapy and unmeasured RTFs was predictively computed with p-THYROSIM for male and female patients in low, normal, and high BMI ranges, yielding daily T3 doses of 5 to 7.5 μg of LT3 combined with 62.5-100 μg of LT4 for women or 75-125 μg of LT4 for men. Also, graphs of steady-state serum T3, T4, and TSH concentrations vs. RTF (range 0%-50%) for untreated patients showed that neither BMI nor gender had any effect on RTF predictions for our patient cohort data. Notably, the graphs provide a means for estimating unmeasurable RTFs for individual patients from their hormone measurements before treatment.

CONCLUSIONS

p-THYROSIM can provide accurate monotherapies for male and female hypothyroid patients, personalized with their BMIs. Where combination therapy is warranted, our results predict that not much LT3 is needed in addition to LT4 to restore euthyroid levels, suggesting opportunities for further research exploring combination therapy with lower T3 doses and slow-releasing T3 formulations.

Mathematical Modeling of Free Thyroxine Concentrations During Methimazole Treatment for Graves' Disease: Development and Validation of a Computer-Aided Thyroid Treatment Method

BACKGROUND

Methimazole (MMI) is the first-line treatment for patients with Graves' disease (GD). While there are empirical recommendations for initial MMI doses, there is no clear guidance for subsequent MMI dose titrations. We aimed to (a) develop a mathematical model capturing the dynamics of free thyroxine (FT4) during MMI treatment (b), validate this model by use of numerical simulation in comparison with real-life patient data (c), develop the software application Digital Thyroid (DigiThy) serving either as a practice tool for treating virtual patients or as a decision support system with dosing recommendations for MMI, and (d) validate this software framework by comparing the efficacy of its MMI dosing recommendations with that from clinical endocrinologists.

METHODS

Based on concepts of automatic control and by use of optimization techniques, we developed two first order ordinary differential equations for modeling FT4 dynamics during MMI treatment. Clinical data from patients with GD derived from the outpatient clinic of Endocrinology at the Medical University of Graz, Austria, were used to develop and validate this model. It was subsequently used to create the web-based software application DigiThy as a simulation environment for treating virtual patients and an autonomous computer-aided thyroid treatment (CATT) method providing MMI dosing recommendations.

RESULTS

Based on MMI doses, concentrations of FT4, thyroid-stimulating hormone (TSH), and TSH-receptor antibodies (TRAb), a mathematical model with 8 patient-specific constants was developed. Predicted FT4 concentrations were not significantly different compared to the available consecutively measured FT4 concentrations in 9 patients with GD (52 data pairs, p=0.607). Treatment success of MMI dosing recommendations in 41 virtually generated patients defined by achieved target FT4 concentrations preferably with low required MMI doses was similar between CATT and usual care. Statistically, CATT was significantly superior (p<0.001).

CONCLUSIONS

Our mathematical model produced valid FT4 predictions during MMI treatment in GD and provided the basis for the DigiThy application already serving as a training tool for treating virtual patients. Clinical trial data are required to evaluate whether DigiThy can be approved as a decision support system with automatically generated MMI dosing recommendations.

The Association Between Chronic Lymphocytic Thyroiditis and the Progress of Papillary Thyroid Cancer

BACKGROUND

Whether chronic lymphocytic thyroiditis (CLT) influences the risk of development and the progression of papillary thyroid cancer (PTC) remains uncertain. We investigated the effects of CLT on the clinicopathologic features and prognosis of PTC.

METHODS

Two thousand nine hundred twenty-eight consecutive patients with PTC treated between 2009 and 2017 were divided into two groups: one with chronic lymphocytic thyroiditis and one without; 1174 (40%) of the patients had coincident CLT.

RESULTS

In univariate analysis, CLT correlated positively with small tumor size, frequent extrathyroidal extension, multifocal diseases, and p53 but negatively with central lymph node (LN) metastasis and BRAF mutation. In multivariate analysis, CLT was associated with extrathyroidal extension and multifocal disease; however, it was not a prognostic factor for recurrence even though it was associated with two aggressive factors. Compared with patients with PTC alone, there were more retrieved central LNs in the PTC + CLT group, and these patients also underwent more invasive diagnostic tests such as fine needle aspiration cytology and frozen biopsy of LN.

CONCLUSIONS

The CLT patients with PTC had better behavior features and prognoses than did those with PTC alone despite frequent multifocality and extrathyroidal extension. However, precaution may be necessary to avoid performing invasive diagnostic procedures for lateral LN metastasis and to manage the patients appropriately.

Different stability of miRNAs and endogenous control genes in archival specimens of papillary thyroid carcinoma

BACKGROUND

The most popular miRNA quantitation technique is RQ-PCR with relative gene expression method that requires an endogenous control (EC) gene for data normalization. However, there are insufficient data and selection criteria on the most suitable ECs for miRNA expression studies in many cancer types including papillary thyroid carcinoma (PTC). Therefore, in this study we evaluated the impact of chosen EC and archival formalin-fixed, paraffin-embedded (FFPE) PTC tissue age on estimated target miRNA expression.

METHODS

RQ-PCR was used to determine expression levels of five miRNAs (miR-146b, miR-222, miR-21, miR-221 and miR-181b) and three different endogenous controls (RNU48, let-7a, miR-16), which were used to normalize the data. In total, 400 FFPE PTC tissues were analyzed that have been stored from 1 to 15 years.

RESULTS

The stability of commonly used ECs RNU48 and let-7a significantly differs from the stability of target miRNA in archival FFPE PTC tissues. Moreover, these differences have a great impact on miRNA expression results when FFPE tissue samples have been stored for a different period of time.

CONCLUSIONS

It is important to select an ECs not only stable in the tissue of interest but also with similar stability to target miRNA, especially when working with samples of different age.

OFF-LABEL USE AND MISUSE OF TESTOSTERONE, GROWTH HORMONE, THYROID HORMONE, AND ADRENAL SUPPLEMENTS: RISKS AND COSTS OF A GROWING PROBLEM

Over the past few decades, there has been an unprecedented rise in off-label use and misuse of testosterone, growth hormone, thyroid hormone, and adrenal supplements. Testosterone therapy is often promoted to men for the treatment of low energy, lower libido, erectile dysfunction, and other symptoms. Growth hormone is used in attempts to improve athletic performance in athletes and to attenuate aging in older adults. Thyroid hormone and/or thyroid supplements or boosters are taken to treat fatigue, obesity, depression, cognitive impairment, impaired physical performance, and infertility. Adrenal supplements are used to treat common nonspecific symptoms due to "adrenal fatigue," an entity that has not been recognized as a legitimate medical diagnosis. Several factors have contributed to the surge in off-label use and misuse of these hormones and supplements: direct-to-consumer advertising, websites claiming to provide legitimate medical information, and for-profit facilities promoting therapies for men's health and anti-aging. The off-label use and misuse of hormones and supplements in individuals without an established endocrine diagnosis carries known and unknown risks. For example, the risks of growth hormone abuse in athletes and older adults are unknown due to a paucity of studies and because those who abuse this hormone often take supraphysiologic doses in sporadic intervals. In addition to the health risks, off-label use of these hormones and supplements generates billions of dollars of unnecessary costs to patients and to the overall health-care system. It is important that patients honestly disclose to their providers off-label hormone use, as it may affect their health and treatment plan. General medical practitioners and adult endocrinologists should be able to begin a discussion with their patients regarding the unfavorable balance between the risks and benefits associated with off-label use of testosterone, growth hormone, thyroid hormone, and adrenal supplements. Abbreviations: DHEA = dehydroepiandrosterone; FDA = U.S. Food and Drug Administration; GH = growth hormone; IGF-1 = insulin-like growth factor 1; LT3 = L-triiodothyronine; LT4 = levothyroxine; T3 = total triiodothyronine; T4 = thyroxine; TSH = thyroid-stimulating hormone.

Predicting Optimal Combination LT4 + LT3 Therapy for Hypothyroidism Based on Residual Thyroid Function

Objective: To gain insight into the mixed results of reported combination therapy studies conducted with levothyroxine (LT4) and liothyronine (LT3) between 1999 and 2016. Methods: We defined trial success as improved clinical outcome measures and/or patient preference for added LT3. We hypothesized that success depends strongly on residual thyroid function (RTF) as well as the LT3 added to sufficient LT4 dosing to normalize serum T4 and TSH, all rendering T3 levels to at least middle-normal range. The THYROSIM app was used to simulate "what-if" experiments in patients and study designs corresponding to the study trials. The app graphically provided serum total (T4) and free (FT4) thyroxine, total (T3) and free (FT3) triiodothyronine, and TSH responses over time, to different simulated LT4 and combination LT4 + LT3 dosage inputs in patients with primary hypothyroidism. We compared simulation results with available study response data, computed RTF values that matched the data, classified and compared them with trial success measures, and also generated nomograms for optimizing dosages based on RTF estimates. Results: Simulation results generated three categories of patients with different RTFs and T3 and T4 levels at trial endpoints. Four trial groups had >20%, four <10%, and five 10-20% RTF. Four trials were predicted to achieve high, seven medium, and two low T3 levels. From these attributes, we were able to correctly predict 12 of 13 trials deemed successful or not. We generated an algorithm for optimizing dosage combinations suitable for different RTF categories, with the goal of achieving mid-range normal T4, T3 and TSH levels. RTF is estimated from TSH, T4 or T3 measurements prior to any hormone therapy treatment, using three new nonlinear nomograms for computing RTFs from these measurements. Recommended once-daily starting doses are: 100 μg LT4 + 10-12.5 μg LT3; 100 μg LT4 + 7.5-10 μg LT3; and 87.5 μg LT4 + 7.5 μg LT3; for <10%, 10-20%, and >20% RTF, respectively. Conclusion: Unmeasured and variable RTF is a complicating factor in assessing effectiveness of combination LT4 + T3 therapy. We have estimated and partially validated RTFs for most existing trial data, using THYROSIM, and provided an algorithm for estimating RTF from accessible data, and optimizing patient dosing of LT4 + LT3 combinations for future combination therapy trials.

Calculated Parameters of Thyroid Homeostasis: Emerging Tools for Differential Diagnosis and Clinical Research

Although technical problems of thyroid testing have largely been resolved by modern assay technology, biological variation remains a challenge. This applies to subclinical thyroid disease, non-thyroidal illness syndrome, and those 10% of hypothyroid patients, who report impaired quality of life, despite normal thyrotropin (TSH) concentrations under levothyroxine (L-T4) replacement. Among multiple explanations for this condition, inadequate treatment dosage and monotherapy with L-T4 in subjects with impaired deiodination have received major attention. Translation to clinical practice is difficult, however, since univariate reference ranges for TSH and thyroid hormones fail to deliver robust decision algorithms for therapeutic interventions in patients with more subtle thyroid dysfunctions. Advances in mathematical and simulative modeling of pituitary-thyroid feedback control have improved our understanding of physiological mechanisms governing the homeostatic behavior. From multiple cybernetic models developed since 1956, four examples have also been translated to applications in medical decision-making and clinical trials. Structure parameters representing fundamental properties of the processing structure include the calculated secretory capacity of the thyroid gland (SPINA-GT), sum activity of peripheral deiodinases (SPINA-GD) and Jostel's TSH index for assessment of thyrotropic pituitary function, supplemented by a recently published algorithm for reconstructing the personal set point of thyroid homeostasis. In addition, a family of integrated models (University of California-Los Angeles platform) provides advanced methods for bioequivalence studies. This perspective article delivers an overview of current clinical research on the basis of mathematical thyroid models. In addition to a summary of large clinical trials, it provides previously unpublished results of validation studies based on simulation and clinical samples.