Category: Nevin Manimala

ACS Appl Mater Interfaces. 2023 Dec 28. doi: 10.1021/acsami.3c14246. Online ahead of print.

ABSTRACT

Opioids are considered to be a global threat, and we are facing the worst opioid crisis of the decade. Synthetic opioids like fentanyl are highly potent and deadly toward human body, and hence its detection is an inevitable requirement globally. Naloxone is known for its antagonist property toward fentanyl, and we performed computational simulations to find their interactions and use this principle to build the first of a kind impedimetric sensor device, transduced by 3D-ZIF-8 with in situ encapsulated naloxone-gold nanoparticles. The probe is synthesized using a unique encapsulation strategy, thoroughly characterized by various physicochemical and microscopic tools. The sensor is highly selective toward fentanyl and can detect fentanyl up to 100 ppm in a synthetic sample. A prototype device is also built based on the synthetic calibration and applied to the spiked urine sample, and the performance is evaluated using statistical and machine learning tools.

PMID:38153905 | DOI:10.1021/acsami.3c14246

Vestn Otorinolaringol. 2023;88(6):42-47. doi: 10.17116/otorino20238806142.

ABSTRACT

OBJECTIVE: The study of the population and subpopulation content of lymphocytes and immunoglobulins and their associations in IgE-mediated CRS relative to other CRS and the control group.

MATERIAL AND METHODS: 23 patients with IgE-mediated chronic rhinusinusitis and 67 patients with normal IgE blood levels were examined. For analysis, flow cytometry (Cytomics FC500, Beckman Coulter, USA), using monoclonal antibodies CD3⁺, CD4⁺, CD8⁺, CD16⁺, CD19⁺ and enzyme immunoassay (Thermo Scientific Multiskan FC, Thermo Fisher Scientific, USA), using IgA, IgM, IgE and IgG in serum, statistical processing was performed using Statistica 7.0.

RESULTS: In patients with CRS and IgE-mediated CRS, hyperactivation was revealed in both T- and B-cell immunity, manifested by an increase in the level of T-lymphocytes, NK-lymphocytes and B-lymphocytes. More pronounced disorders in the immune status are detected in patients with IgE – mediated CRS, there is a more pronounced activation of the T-cell immune link due to an increase in T-helper cells, T-killer/suppressor cells, an imbalance in their number is accompanied by a decrease in their ratio in the immunoregulatory index. Activation of the immune system in patients with CRS is also associated with an increase in the content of mature B-lymphocytes (CD19⁺), while only in patients with IgE-mediated CRS, hypergammaglobulinemia of classes A and M was detected.

CONCLUSION: Changes in the immune status indicate a violation of immune regulation, confirmed by the revealed correlations between the subpopulations of lymphocytes and immunoglobulins that implement the immune response in this condition. The greatest number of violations in the regulation is associated with mature T-lymphocytes in both CRS and IgE-mediated CRS, while only IgA fully retains its function.

PMID:38153892 | DOI:10.17116/otorino20238806142

Vestn Otorinolaringol. 2023;88(6):30-37. doi: 10.17116/otorino20238806130.

ABSTRACT

OBJECTIVE: To evaluate the features of voice disorders associated with novel coronavirus infection and to develop the clinical algorithm for diagnostic and treatment these patients.

MATERIAL AND METHODS: A prospective observational study was conducted in patients with dysphonia after COVID-19 (n=60). All patients underwent a comprehensive voice assessment before and after the proposed treatment. The follow-up period was 1 month.

RESULTS: Functional dysphonia or aphonia with a stable (refractory) or recurrent course was diagnosed in 58 (97%) patients. A tendency to an increase in the value of the latent period of the P300 and MMN in patients with voice disorder was revealed. There was a significant decrease in supraglottic constriction and glottal insufficiency before and after the treatment. The mean VHI-10 decreased from 25.4 before treatment to 15.3 after treatment. The DSI which is based on the set of voice measurements, statistically significant improved from -5.2 to 2.6 in patients as a result of treatment. The average value of MFI-20 improved from 65.4 (8.7) at the beginning of the study to 20.3 (5.3) after treatment.

CONCLUSION: In patients with dysphonia or aphonia associated with COVID-19 are indicated a refractory type of dysphonia. This was indicated by the study of AEPs of the brain. The clinical algorithm for treatment and diagnostic patients with voice disorders after COVID-19 has been developed. The treatment of this group of patients should be adjunct by the drug therapy, kinesiotaping method and psychotherapy.

PMID:38153890 | DOI:10.17116/otorino20238806130

J Magn Reson Imaging. 2023 Dec 28. doi: 10.1002/jmri.29208. Online ahead of print.

ABSTRACT

BACKGROUND: Vesical Imaging-Reporting and Data System (VI-RADS) has been developed for assessing bladder cancer from multiparametric (mp) MRI but its performance in diagnosing muscle-invasive bladder cancer (MIBC) is suboptimal.

PURPOSE: To investigate associations between normalized apparent diffusion coefficient (NADC) and clinicopathological characteristics and to determine whether the inclusion of NADC can improve the performance of VI-RADS in diagnosing MIBC.

STUDY TYPE: Retrospective.

POPULATION: Two hundred seventy-five patients with pathologically confirmed bladder cancer (101 MIBC and 174 non-MIBC [NMIBC]) underwent preoperative mpMRI (233 male, 42 female).

FIELD STRENGTH/SEQUENCE: 3-T, T2-weighted imaging (turbo spin-echo), diffusion-weighted imaging (free-breathing spin-echo), and dynamic contrast-enhanced imaging (gradient-echo).

ASSESSMENT: NADC was the mean ADC of tumor divided by that of the iliopsoas muscles in trans caput femoris plane. Associations between NADC and clinicopathological characteristics were evaluated. Models were established for differentiating MIBC and NMIBC: VI-RADS model; VN model (VI-RADS and NADC), Images model (significant variables from imaging associated with MIBC), LN model (Images model without NADC), and Full model (all significant variables associated with MIBC).

STATISTICAL TESTS: Variables for model development were based on logistic regression. Models were evaluated by receiver operating characteristic (ROC) curve. Comparison of the area under the curves (AUCs) for the models used DeLong’s test. A P value <0.05 was considered statistically significant.

RESULTS: NADC was significantly lower in lesions with diameter ≥ 3 cm, MIBC, histological high grade, lymph node metastasis, and lymphovascular invasion. Compared with VI-RADS model, the AUCs for VN model (VI-RADS score and NADC), Images model (VI-RADS score, NADC and tumor size) and Full model (VI-RADS score, NADC, tumor size and histological grade) were significantly higher. No significant differences were observed between the AUCs for VN model and Images model (P = 0.051).

DATA CONCLUSION: NADC reflects information about the aggressiveness of bladder cancer. Combining VI-RADS with NADC can improve performance in diagnosing MIBC.

EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

PMID:38153874 | DOI:10.1002/jmri.29208

J Manag Care Spec Pharm. 2024 Jan;30(1):43-51. doi: 10.18553/jmcp.2024.30.1.43.

ABSTRACT

BACKGROUND: Improving medication adherence remains an important goal to improve therapeutic outcomes and lower health care costs. Point-of-sale prescription costs and forgetfulness remain top reasons why patients do not adhere to medications. Programs using both text message-based reminders and financial incentives may encourage patients to refill their prescriptions on time by reducing copays through discounts at the point of sale. Sempre Health, the subject of our analysis, provides both text message refill reminders and a dynamic discount incentive program to improve medication adherence.

OBJECTIVE: To evaluate the impact of a financial incentive/refill reminder program on medication adherence and total cost of care for patients taking the antithrombotic agents ticagrelor, apixaban, or rivaroxaban in a large regional health plan.

METHODS: After propensity-score matching on demographics, socioeconomic status, baseline copay, prior pharmacy/medical spend, and morbidity, we compared-using a difference-in-differences analytic approach-adherence (measured by proportion of days covered), unplanned health care utilization, and costs (total cost of care, medical, and pharmacy cost) of health plan members who did and did not enroll in the financial incentive/refill reminder program between February 1, 2019, and October 31, 2021, over 1 and 2 years. Because of differences in patient characteristics, we analyzed patients on ticagrelor (the antiplatelet group), apixaban, and rivaroxaban (the anticoagulant group) separately.

RESULTS: There were a total of 1,292 one-to-one program and control propensity-matched patients: 166 each for the antiplatelet group and 480 each for the anticoagulant group. The average age of the anticoagulant group was 62 years; more than 60% were male, and approximately 45% had no prior unplanned care events. In contrast, the average age of the antiplatelet group was 57 years; more than 70% were male, and approximately 21% had no prior unplanned care events. In the antiplatelet group, the proportions adherent (proportion of days covered ≥80%) were 63.3% vs 42.8% (P = 0.0002) for program vs controls. Similarly, in the anticoagulant group, the proportion adherent was 77.9% vs 60.2% (P < 0.0001) for program vs controls. Reflecting improved adherence, costs of apixaban and rivaroxaban increased by $79 per member per month (PMPM) (P < 0.0001), with no statistically significant differences in other costs. Similarly, the cost of ticagrelor increased by $77 PMPM (P = 0.0102) with no statistically significant differences in other costs. Finally, there was a 16% (P = 0.032) reduction in emergency department use for those in the program.

CONCLUSIONS: The financial incentive and refill reminder program was associated with improved adherence to antithrombotic medications, reduced emergency department use, and increased medication costs, but not in total pharmacy, medical, or total cost of care in both subgroups.

PMID:38153862 | DOI:10.18553/jmcp.2024.30.1.43

J Magn Reson Imaging. 2023 Dec 28. doi: 10.1002/jmri.29186. Online ahead of print.

ABSTRACT

BACKGROUND: TP53 mutations are associated with prostate cancer (PCa) prognosis and therapy.

PURPOSE: To develop TP53 mutation classification models for PCa using MRI radiomics and clinicopathological features.

STUDY TYPE: Retrospective.

POPULATION: 388 patients with PCa from two centers (Center 1: 281 patients; Center 2: 107 patients). Cases from Center 1 were randomly divided into training and internal validation sets (7:3). Cases from Center 2 were used for external validation.

FIELD STRENGTH/SEQUENCE: 3.0T/T2-weighted imaging, dynamic contrast-enhanced imaging, diffusion-weighted imaging.

ASSESSMENT: Each patient’s index tumor lesion was manually delineated on the above MRI images. Five clinicopathological and 428 radiomics features were obtained from each lesion. Radiomics features were selected by least absolute shrinkage and selection operator and binary logistic regression (LR) analysis, while clinicopathological features were selected using Mann-Whitney U test. Radiomics models were constructed using LR, support vector machine (SVM), and random forest (RF) classifiers. Clinicopathological-radiomics combined models were constructed using the selected radiomics and clinicopathological features with the aforementioned classifiers.

STATISTICAL TESTS: Mann-Whitney U test. Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC). P value <0.05 indicates statistically significant.

RESULTS: In the internal validation set, the radiomics model had an AUC of 0.74 with the RF classifier, which was significantly higher than LR (AUC = 0.61), but similar to SVM (AUC = 0.69; P = 0.422). For the combined model, the AUC of RF model was 0.84, which was significantly higher than LR (0.64), but similar to SVM (0.80; P = 0.548). Both the combined RF and combined SVM models showed significantly higher AUCs than the radiomics models. In the external validation set, the combined RF and combined SVM models showed AUCs of 0.83 and 0.82.

DATA CONCLUSION: Pathological-radiomics combined models with RF, SVM show the association of TP53 mutations and pathological-radiomics features of PCa.

EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

PMID:38153859 | DOI:10.1002/jmri.29186

JMIR Form Res. 2023 Dec 28;7:e53619. doi: 10.2196/53619.

ABSTRACT

BACKGROUND: Digital weight management interventions have the potential to increase access to novel pharmacotherapy for people living with obesity. At present, there is limited real-world evidence on the effectiveness, feasibility, and acceptability of this type of intervention.

OBJECTIVE: This retrospective service evaluation examines real-world data to evaluate the preliminary impact of Second Nature’s 24-month, remotely delivered, semaglutide-supported weight management intervention for adults living with obesity at 12 weeks.

METHODS: Retrospective data were extracted in October 2023 for participants who started the intervention between June 8, 2023, and July 22, 2023. The primary outcomes were weight change (kg) and percentage of weight change at 12 weeks. The secondary outcomes were the proportion of participants who achieved ≥5% and ≥10% weight loss and the feasibility and acceptability of this type of intervention. Descriptive statistics were used to evaluate the baseline characteristics, retention, engagement, prevalence of side effects, and weight change. A paired 2-tailed t test was used to determine the significance of weight change. Content analysis was used to analyze the free-text questionnaire responses.

RESULTS: A total of 113 participants with a mean baseline BMI of 38.4 kg/m² (SD 7.3) were included in the analysis (n=102, 90.4% women, mean age 46.6, SD 11.1 years). Over 12 weeks, 23% (n=26) of participants withdrew from the intervention. A total of 70.8% (n=80) of participants provided weight data at 12 weeks. The average weight loss observed over this 12-week period was 6.5 (SD 4.4) kg (P<.001) or 6.4% (SD 4.2%) of their starting weight (P<.001). Of the 80 participants who recorded weight readings, 62.5% (n=50) achieved ≥5% weight loss, and 11.3% (n=9) achieved ≥10% weight loss. Engagement with the app-based program declined from a mean of 131 (SD 142.6) home screen views in week 0 to 35 (SD 57.1) in week 11. Common side effects reported over 12 weeks included feeling more tired than usual, constipation, and feeling sick. However, a significant proportion of participants reported no side effects. Most participants (n=106, 93.8%) did not experience any difficulties in medication administration. Qualitative data showed that most participants had a positive or neutral experience of the intervention, with some reporting perceived benefits as early as 4 weeks. Most participants did not feel that improvements in the intervention were needed; however, some participants faced issues with medication shipping or logistics.

CONCLUSIONS: This retrospective preliminary service evaluation suggests that a remotely delivered semaglutide-supported weight management intervention has the potential to be effective, feasible, and acceptable for self-paying consumer adults with obesity in the United Kingdom. Areas for further improvement were highlighted, including user engagement in an app-based program. A full-service evaluation at the end of the 24-month intervention with a larger sample size is required to support these early findings.

PMID:38153780 | DOI:10.2196/53619

JMIR Form Res. 2023 Dec 28;7:e51798. doi: 10.2196/51798.

ABSTRACT

BACKGROUND: Refractive surgery research aims to optimally precategorize patients by their suitability for various types of surgery. Recent advances have led to the development of artificial intelligence-powered algorithms, including machine learning approaches, to assess risks and enhance workflow. Large language models (LLMs) like ChatGPT-4 (OpenAI LP) have emerged as potential general artificial intelligence tools that can assist across various disciplines, possibly including refractive surgery decision-making. However, their actual capabilities in precategorizing refractive surgery patients based on real-world parameters remain unexplored.

OBJECTIVE: This exploratory study aimed to validate ChatGPT-4’s capabilities in precategorizing refractive surgery patients based on commonly used clinical parameters. The goal was to assess whether ChatGPT-4’s performance when categorizing batch inputs is comparable to those made by a refractive surgeon. A simple binary set of categories (patient suitable for laser refractive surgery or not) as well as a more detailed set were compared.

METHODS: Data from 100 consecutive patients from a refractive clinic were anonymized and analyzed. Parameters included age, sex, manifest refraction, visual acuity, and various corneal measurements and indices from Scheimpflug imaging. This study compared ChatGPT-4’s performance with a clinician’s categorizations using Cohen κ coefficient, a chi-square test, a confusion matrix, accuracy, precision, recall, F₁-score, and receiver operating characteristic area under the curve.

RESULTS: A statistically significant noncoincidental accordance was found between ChatGPT-4 and the clinician’s categorizations with a Cohen κ coefficient of 0.399 for 6 categories (95% CI 0.256-0.537) and 0.610 for binary categorization (95% CI 0.372-0.792). The model showed temporal instability and response variability, however. The chi-square test on 6 categories indicated an association between the 2 raters’ distributions (χ²₅=94.7, P<.001). Here, the accuracy was 0.68, precision 0.75, recall 0.68, and F₁-score 0.70. For 2 categories, the accuracy was 0.88, precision 0.88, recall 0.88, F₁-score 0.88, and area under the curve 0.79.

CONCLUSIONS: This study revealed that ChatGPT-4 exhibits potential as a precategorization tool in refractive surgery, showing promising agreement with clinician categorizations. However, its main limitations include, among others, dependency on solely one human rater, small sample size, the instability and variability of ChatGPT’s (OpenAI LP) output between iterations and nontransparency of the underlying models. The results encourage further exploration into the application of LLMs like ChatGPT-4 in health care, particularly in decision-making processes that require understanding vast clinical data. Future research should focus on defining the model’s accuracy with prompt and vignette standardization, detecting confounding factors, and comparing to other versions of ChatGPT-4 and other LLMs to pave the way for larger-scale validation and real-world implementation.

PMID:38153777 | DOI:10.2196/51798

Health Policy Plan. 2023 Dec 28:czad122. doi: 10.1093/heapol/czad122. Online ahead of print.

ABSTRACT

INTRODUCTION: Diabetes prevalence is rising globally, especially in low- and middle-income countries like Mexico, posing challenges for healthcare systems that require efficient primary care to manage the disease. However, healthcare efficiency is influenced by factors beyond decision-makers, including socioeconomic and political conditions. This study aims to evaluate the technical efficiency of primary health care for diabetes patients in Mexico over a 12-year period and explore the impact of contextual variables on efficiency.

METHODOLOGY: A longitudinal analysis was conducted using administrative and socio-demographic data from 242 health jurisdictions between 2009 and 2020. Data envelopment analysis with bootstrapping and output orientation was used to measure the technical efficiency, health resources in infrastructure and human resources were used as inputs. As outcome, the number of patients receiving treatment for diabetes and the number of patients with controlled diabetes were considered. Machine learning algorithms were employed to analyze multiple factors affecting the provision of diabetes health services and assess heterogeneity and trends in efficiency across different health jurisdictions.

RESULTS: The average technical efficiency in primary health care for diabetes patients was 0.44 (CI: 0.41-0.46) in 2009, reaching a peak of 0.71 (CI: 0.69-0.72) in 2016, and moderately declining to 0.60 (CI: 0.57-0.62) in 2020, these differences were statistically significant. The random forest analysis identified the marginalization index, primary health care coverage, proportion of indigenous population, and demand for health services as the most influential variables in predicting efficiency levels.

CONCLUSION: This research underscores the crucial need for the formulation of targeted public policies aimed at extending the scope of primary healthcare services, with a particular focus on addressing the unique challenges faced by marginalized and indigenous populations. According to our results, it is necessary that medical care management adjust to the specific demands and needs of these populations to guarantee equitable care in Mexico.

PMID:38153766 | DOI:10.1093/heapol/czad122

Int J Qual Health Care. 2023 Dec 28:mzad107. doi: 10.1093/intqhc/mzad107. Online ahead of print.

ABSTRACT

Background In 2018, the Ministry of Health (MoH) in Saudi Arabia developed a clinical excellence strategy. An objective was to reduce variation in clinical practices in MoH hospitals, particularly for conditions with high mortality in Saudi Arabia, by applying best practice clinical standards and using the clinical audit process to measure clinical practice. The strategy included working with multi-professional teams in hospitals to implement improvements needed in clinical practice. To test the feasibility of carrying out national clinical audits in MoH hospitals, audits were carried out in 16 MoH hospitals on four clinical subjects – acute myocardial infarction, major trauma, sepsis and stroke. Methods Clinical expert groups, including Saudi clinicians and an international clinical expert, developed clinical care standards for the four conditions from analyses of international and Saudi clinical guidelines. The audits were designed with the expert groups. Multi-professional teams were appointed to carry out the audits in designated MoH hospitals. Data collectors in each hospital were trained to collect data. Workshops were held with the teams on the clinical care standards and how data would be collected for the audits, and later, on the findings of data collection and how to use the improvement process to implement changes to improve compliance with the standards. After four months, data collection was repeated to determine if compliance with the clinical care standards had improved. Data collected from each hospital for both cycles of data collection were independently reliably tested. Results All designated hospitals participated in the audits, collecting and submitting data for two rounds of data collection and implementing improvement plans after the first round of data collection. All hospitals made substantial improvements in clinical practices. Of a total of 84 measures used to assess compliance with a total of 52 clinical care standards for the four clinical conditions, improvements were made by hospital teams in 58 (69.1%) of the measures. Improvements were statistically significant for 34 (40.5%) of the measures. Conclusion The project demonstrated that well-designed and executed audits using evidence-based clinical care standards can result in substantial improvements in clinical practices in MoH hospitals in Saudi Arabia. Keys to success were the improvement methodology built into the audit process and the requirement for hospitals to appoint multi-professional teams to carry out the audits. The approach adds to evidence on the effectiveness of clinical audits in achieving improvements in clinical quality and can be replicated in national audit programmes.

PMID:38153764 | DOI:10.1093/intqhc/mzad107