Effect of Ramadan fasting on thyroid functions in hypothyroid patients taking levothyroxine: a systematic review and meta-analysis.

BACKGROUND: The major changes in the timing of meals during Ramadan may be challenging for hypothyroid patients on levothyroxine. We aimed to study the effect of Ramadan fasting on thyroid functions in hypothyroid patients taking levothyroxine. METHODS: We did a comprehensive search of 8 databases for Randomized controlled studies (RCTs) and observational studies investigating the effect of Ramadan fasting on thyroid functions in hypothyroid individuals taking levothyroxine. Relevant data was extracted and analyzed. Mean difference (MD) and standard deviation (SD) were used to evaluate the continuous data. Risk ratios (RR) with a 95% confidence interval were used for outcomes constituting dichotomous data. National Institutes of Health (NIH) tools were used to assess the risk of bias. RESULTS: Fourteen studies met our inclusion criteria, 3 RCTs, and 11 observational studies, all designed as pre-post studies. Ramadan fasting was associated with a statistically significant increase in TSH in patients who were euthyroid before Ramadan (MD = -0.76 [95% CI; -1.27, -0.25]). However, free thyroxine (FT4) was found to be stable (MD = 0.01, [95% CI; -0.03, 0.06]). All timing points were associated with a significant increase in TSH levels after Ramadan, pre-iftar (MD = -0.69 [95% CI; -1.03, -0.36]), post-iftar (MD = -0.76 [95% CI; -1.12, -0.39]), and pre-suhoor (MD = -1.19 [95% CI; -2.18, -0.19]). CONCLUSION: TSH increases significantly after Ramadan. No timing point has superiority in maintaining thyroid control. However, choosing the timing should be individualized according to the patient's preference to guarantee the most possible compliance.

Efficacy and safety of polyethylene glycol loxenatide in type 2 diabetic patients: a systematic review and meta-analysis of randomized controlled trials.

Polyethylene glycol loxenatide (PEX168) is a novel glucagon-like peptide-1 receptor agonist with a longer half-life developed by modifying the chemical structure of exenatide. This study aims to assess the efficacy and safety of PEX168 and determine the best dose. We searched PubMed, Scopus, Cochrane Library, and Web of Science databases from inception to April 25, 2023, for randomized controlled trials (RCTs) comparing PEX168 therapy alone or in combination with metformin versus other therapies. We used the risk ratio (RR) for dichotomous outcomes and the mean difference (MD) for continuous outcomes, both with 95% confidence intervals (CI). Six RCTs, including 1248 participants, were included. PEX168 added to metformin was significantly better than metformin alone regarding fasting blood glucose (MD = -1.20, 95% CI (-1.78, - 0.62), p < 0.0001), HbA1c (MD = -1.01, 95% CI (-1.48, - 0.53), p < 0.0001), and postprandial glycemia (MD = -1.94, 95% CI (-2.99, - 0.90), p = 0.0003). Similarly, for glycemic control, PEX168 monotherapy was superior to placebo (P < 0.05). No significant effects were noticed in terms of triglycerides, low-density lipoprotein, or high-density lipoprotein (p > 0.05). Body weight was significantly reduced in obese diabetic patients receiving PEX168 compared to the control group (MD = -5.46, 95% CI (-7.90, - 3.01), p < 0.0001) but not in non-obese patients (MD = 0.06, 95% CI (-0.47, 0.59), p = 0.83). People who received PEX168 alone or with metformin showed more common gastrointestinal adverse effects, especially nausea and vomiting (p < 0.05). PEX168 100, 200, and 300 ug monotherapy demonstrated comparable safety and diabetes control to metformin, but when combined with metformin, PEX168 100 and 200 ug showed significant effects on diabetes control; however, only the latter showed a significantly higher incidence of nausea and vomiting (p < 0.05). PEX168 could be a viable option for treating diabetic patients whose metformin control is inadequate or who cannot tolerate metformin. PEX168 at 100 ug in combination with metformin was found to be safe and more effective compared to metformin; however, due to the small number of trials included, these findings should be interpreted with caution, and additional trials are required.

The efficacy of oxytocin gel in postmenopausal women with vaginal atrophy: an updated systematic review and meta-analysis.

BACKGROUND: Genitourinary syndrome of menopause (GSM) is a common and disturbing issue in the postmenopausal period. Unlike vasomotor symptoms, it has a progressive trend. Our study aims to evaluate the efficacy and safety of oxytocin gel versus placebo gel in postmenopausal women with GSM. METHODS: A systematic review and meta-analysis synthesizing randomized controlled trials (RCTs) from Web of Science, SCOPUS, PubMed, and Cochrane Central Register of Controlled Trials databases on January 18, 2023. Keywords such as "oxytocin," "intravaginal," "vaginal," "atrophic," and "atrophy" were used. We used Review Manager (RevMan) version 5.4 in our analysis. We used the risk ratio (RR) for dichotomous outcomes and the mean difference (MD) for continuous outcomes; both were presented with the corresponding 95% confidence interval (CI) and were calculated with the Mantel-Haenszel or inverse variance statistical method. Cochrane's Q test and the I2 statistic were used as measures of statistical inconsistency and heterogeneity. The Cochrane Risk of Bias Tool for RCTs was used for the quality assessment of the included studies. RESULTS: Seven studies with 631 patients were included. Regarding the maturation index, there was a statistically insignificant increase in the oxytocin arm (MD = 12.34, 95% CI (-12.52-37.19), P = 0.33). Clinically assessed vaginal atrophy showed a statistically significant reduction in the oxytocin group (RR = 0.32, 95% CI (0.23 - 0.10), P < 0.00001). For dyspareunia, vaginal pH, and histological evaluation of vaginal atrophy, there was a statistically insignificant difference between the two groups (RR = 1.02, 95% CI (0.82-1.27), P = 0.84), (MD = -0.74, 95% CI (-1.58-0.10), P = 0.08), and (MD = -0.38, 95% CI (-0.82-0.06), P = 0.09), respectively. There was no significant difference in the safety profile between the two groups as measured by endometrial thickness (MD = 0.00, 95% CI (-0.23-0.23), P = 0.99). CONCLUSIONS: Although oxytocin has been proposed as a viable alternative to estrogen in the treatment of GSM, our findings show the opposite. Larger, high-quality RCTs are needed to confirm or refute our results. TRIAL REGISTRATION: PROSPERO registration number CRD42022334357.

Strengths and challenges of the artificial intelligence in the assessment of dense breasts.

Objectives: High breast density is a risk factor for breast cancer and overlapping of glandular tissue can mask lesions thus lowering mammographic sensitivity. Also, dense breasts are more vulnerable to increase recall rate and false-positive results. New generations of artificial intelligence (AI) have been introduced to the realm of mammography. We aimed to assess the strengths and challenges of adopting artificial intelligence in reading mammograms of dense breasts. Methods: This study included 6600 mammograms of dense patterns "c" and "d" and presented 4061 breast abnormalities. All the patients were subjected to full-field digital mammography, breast ultrasound, and their mammographic images were scanned by AI software (Lunit INSIGHT MMG). Results: Diagnostic indices of the sono-mammography: a sensitivity of 98.71%, a specificity of 88.04%, a positive-predictive value of 80.16%, a negative-predictive value of 99.29%, and a diagnostic accuracy of 91.5%. AI-aided mammograms presented sensitivity of 88.29%, a specificity of 96.34%, a positive-predictive value of 92.2%, a negative-predictive value of 94.4%, and a diagnostic accuracy of 94.5% in its ability to read dense mammograms. Conclusion: Dense breasts scanned with AI showed a notable reduction of mammographic misdiagnosis. Knowledge of such software challenges would enhance its application as a decision support tool to mammography in the diagnosis of cancer. Advances in knowledge: Dense breast is challenging for radiologists and renders low sensitivity mammogram. Mammogram scanned by AI could be used to overcome such limitation, enhance the discrimination between benign and malignant breast abnormalities and the early detection of breast cancer.