COVID-19 vaccine hesitancy prevalence in Mexico: A systematic review and metanalysis.

Background: Vaccine hesitancy (VH) is a recognized threat to public health that undermines efforts to mitigate disease burden. This study aims to gather available evidence regarding COVID-19 VH in Mexico, estimate the prevalence of VH, and its determinants to inform policymaking in this country. Methods: Following PRISMA guidelines, a systematic review of the MEDLINE literature, articles that estimated the prevalence of COVID-19 VH in Mexico were included in the analysis to obtain a pooled estimate. We used a binomial-normal model for meta-analysis of proportions (i.e., generalized linear mixed model) to perform the metanalysis. We then performed a narrative review of COVID-19 VH in Mexican subpopulations. Results: Seven studies met inclusion criteria. We estimated a pooled prevalence of COVID-19 VH of 16 % (95 % CI: 11-23 %) in Mexico. We found an association between VH and demographic characteristics, intrinsic vaccine factors, and beliefs. Subgroup analyses from specific studies suggested that patients with clinical conditions such as breast cancer or rheumatologic diseases had a higher prevalence of VH. Conclusions: VH is a highly complex and dynamic phenomenon in Mexico. Characterizing and understanding COVID-19 vaccine hesitancy in the Mexican population helps target future policy interventions to mitigate the spread and impact of infectious diseases. The implications of VH differ among groups that may be at higher risk of severe disease, underscoring the importance of prompt research among these groups as well as targeted interventions to address VH.

Application of machine learning and artificial intelligence in the diagnosis and classification of polycystic ovarian syndrome: a systematic review.

Introduction: Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity. Artificial intelligence (AI) and machine learning (ML) hold promise in improving diagnostics. Thus, we performed a systematic review of literature to identify the utility of AI/ML in the diagnosis or classification of PCOS. Methods: We applied a search strategy using the following databases MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, the Web of Science, and the IEEE Xplore Digital Library using relevant keywords. Eligible studies were identified, and results were extracted for their synthesis from inception until January 1, 2022. Results: 135 studies were screened and ultimately, 31 studies were included in this study. Data sources used by the AI/ML interventions included clinical data, electronic health records, and genetic and proteomic data. Ten studies (32%) employed standardized criteria (NIH, Rotterdam, or Revised International PCOS classification), while 17 (55%) used clinical information with/without imaging. The most common AI techniques employed were support vector machine (42% studies), K-nearest neighbor (26%), and regression models (23%) were the commonest AI/ML. Receiver operating curves (ROC) were employed to compare AI/ML with clinical diagnosis. Area under the ROC ranged from 73% to 100% (n=7 studies), diagnostic accuracy from 89% to 100% (n=4 studies), sensitivity from 41% to 100% (n=10 studies), specificity from 75% to 100% (n=10 studies), positive predictive value (PPV) from 68% to 95% (n=4 studies), and negative predictive value (NPV) from 94% to 99% (n=2 studies). Conclusion: Artificial intelligence and machine learning provide a high diagnostic and classification performance in detecting PCOS, thereby providing an avenue for early diagnosis of this disorder. However, AI-based studies should use standardized PCOS diagnostic criteria to enhance the clinical applicability of AI/ML in PCOS and improve adherence to methodological and reporting guidelines for maximum diagnostic utility. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42022295287.

Clinical characterization of patients with bipolar disorder and a history of asthma: An exploratory study.

INTRODUCTION: Bipolar disorder (BD) and asthma are leading causes of morbidity in the US and frequently co-occur. OBJECTIVES: We evaluated the clinical features and comorbidities of patients with BD and a history of asthma. METHODS: In a cross-sectional analysis from the Mayo Clinic Bipolar Biobank, we explored the clinical characteristics of the BD and an asthma phenotype and fitted a multivariable regression model to identify risk factors for asthma. RESULTS: A total of 721 individuals with BD were included. From these, 140 (19%) had a history of asthma. In a multivariable model only sex and evening chronotype were significant predictors of asthma with the odds ratios and 95% confidence intervals being 1.65 (1.00, 2.72; p=0.05) and 1.99 (1.25, 3.17; p < 0.01), respectively. Individuals with asthma had higher odds of having other medical comorbidities after adjusting for age, sex, and site including hypertension (OR = 2.29 (95% CI 1.42, 3.71); p < 0.01), fibromyalgia (2.29 (1.16, 4.51); p=0.02), obstructive sleep apnea (2.03 (1.18, 3.50); p=0.01), migraine (1.98 (1.31, 3.00); p < 0.01), osteoarthritis (2.08 (1.20, 3.61); p < 0.01), and COPD (2.80 (1.14, 6.84); p=0.02). Finally, individuals currently on lithium were less likely to have a history of asthma (0.48 (0.32, 0.71); p < 0.01). CONCLUSION: A history of asthma is common among patients with BD and is associated with being female and having an evening chronotype, as well as with increased odds of having other medical comorbidities. A lower likelihood of a history of asthma among those currently on lithium is an intriguing finding with potential clinical implications that warrants further study.

Clinical impact of immunotherapy in Merkel cell carcinoma patients: A systematic review and meta-analysis.

BACKGROUND: Immunotherapy is emerging as an alternative treatment for Merkel cell carcinoma, but its long-term effects on response, survival, and safety are not well established. High-quality evidence is needed to estimate the efficacy of this treatment and to review the characteristics of patients and tumors that might improve outcomes. OBJECTIVE: To summarize efficacy and safety of immunotherapy in patients with Merkel cell carcinoma. METHODS: A systematic review was performed for studies published in MEDLINE, Web of Science, Scopus, and EMBASE. Two reviewers examined the literature and data extraction in duplicate. We estimated the proportions for objective responses, progression-free survival, overall survival, and treatment-related adverse events. Associations between objective response rate and immunobiologic markers were analyzed. RESULTS: Six clinical trials of 201 patients treated with immunotherapy were included. The objective response rate was 51% (95% confidence interval, 0.40-0.62; I2 = 37.1%) and grade ≥3 treatment-related adverse events were observed in 18% (95% confidence interval, 0.11-0.29; I2 = 49.5%) of patients. No significant difference was observed between response rates and immunobiologic characteristics. CONCLUSIONS: A significantly reduced tumor diameter with durable response rates and a safe profile are obtained with immunotherapy. Similar response rates achieved on either subgroup of viral status or programmed death ligand 1 expression suggests that it might act on multiple, unexplored pathways.

Fixed-bearing unicompartmental knee arthroplasty provides a lower failure rate than mobile-bearing unicompartimental knee arthroplasty when used after a failed high tibial osteotomy: a systematic review and meta-analysis.

Despite the fact that the choice of bearing design has been thought to influence the functional outcomes and longevity of unicompartimental knee arthroplasty (UKA), there is a lack of clinical evidence supporting the decision-making process in patients who have undergone high tibial osteotomy (HTO). A systematic review of studies was carried out that reported the outcomes of fixed-bearing (FB) or mobile-bearing (MB) medial UKA in patients with a previous HTO. A random effect meta-analysis using a generalized linear mixed-effects model to calculate revision rates was done. Seven retrospective cohort studies were included for this study. Regarding the fixation method, 40 were the FB-UKA and 47 were MB-UKA. For both groups, the mean post-operative follow-up was 5.8 years. The survival rates were 92% for the FB-UKA with a mean follow-up of 10 years. For the MB-UKA, it ranged from 35.7 to 93%, with a mean follow-up of 4.2 years. For the FB, the time to revision was reported as 9.3 years, while 1.2, 2.5 and 2.91 years was reported for the MB. The results of the meta-analysis showed that the revision rate for the patients receiving a FB-UKA after failed HTO was 8%, compared to 17% in those who received an MB-UKA. The results of the review suggest that the use of the FB-UKA is associated with lower revision rates and a longer survival time than the MB-UKA and have similar functional ability scores.Level of evidence: III (systematic review of level-III studies).

Interventions supporting cost conversations between patients and clinicians: A systematic review.

BACKGROUND AND AIM: Discussing cost during medical encounters may decrease the financial impact of medical care on patients and align their treatment plans with their financial capacities. We aimed to examine which interventions exist and quantify their effectiveness to support cost conversations. METHODS: Several databases were queried (Embase; Ovid MEDLINE(R); Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily; the Cochrane databases; and Scopus) from their inception until January 31, 2020 using terms such as "clinician*", "patient*", "cost*", and "conversation*". Eligibility assessment, data extraction and risk of bias assessment were performed independently and in duplicate. We extracted study setting, design, intervention characteristics and outcomes related to patients, clinicians and quality metrics. RESULTS: We identified four studies (1327 patients) meeting our inclusion criteria. All studies were non-randomised and conducted in the United States. Three were performed in a primary care setting and the fourth in an oncology. Two studies used decision aids that included cost information; one used a training session for health care staff about cost conversations, and the other directly delivered information regarding cost conversations to patients. All interventions increased cost-conversation frequency. There was no effect on out-of-pocket costs, satisfaction, medication adherence or understanding of costs of care. CONCLUSION: The body of evidence is small and comprised of studies at high risk of bias. However, an increase in the frequency of cost conversations is consistent. Studies with higher quality are needed to ascertain the effects of these interventions on the acceptability, frequency and quality of cost conversations.