Tag: pubmed

J Asthma. 2023 Nov 24:1-21. doi: 10.1080/02770903.2023.2288325. Online ahead of print.

ABSTRACT

INTRODUCTION: Asthma is the most common chronic disease among children. The management of asthma in children requires ongoing effort and is heavily dependent on the effectiveness of family management. This study aimed to evaluate the validity and reliability of the Family Management Scale for Children with Asthma (FMSCA) by adapting it to Turkish.

METHODS: This methodological research comprised 293 parents between December 2020 and May 2021. Inclusion criteria were having a child with a diagnosis of asthma for more than 6 months, being literate, and not having problems in communication. FMSCA was examined for language, content and construct validity. Internal consistency was calculated using Cronbach’s α coefficient, item-total correlation, and test-retest equivalence. Ethical principles were adhered to.

RESULTS: The content validity index scores of the items in the FMSCA ranged from 0.90 to 1.0. The Kaiser-Meyer-Olkin value was determined to be 0.965 and the Bartlett’s Test of Sphericity value was χ² = 18296.335 (p ≤ 0.001). Many indices were used to examine the fit of the FMSCA model. Of these, the χ^2/SD value was determined to be 1.61. The total FMSCA Cronbach α coefficient was 0.981. The relationship between the test-retest results was statistically significant, high, and positive (p <0.05).

CONCLUSION: FMSCA is a valid and reliable tool that can be used to objectively evaluate family management in families with children with asthma and to determine the effectiveness of interventions.

PMID:37999987 | DOI:10.1080/02770903.2023.2288325

JMIR Med Educ. 2023 Nov 24;9:e49013. doi: 10.2196/49013.

ABSTRACT

BACKGROUND: UK medical graduates can apply for specialty training after completing a 2-year internship (foundation training). Postfoundation training application requirements vary depending on specialty but fundamentally require key skills such as teaching, research, and leadership.

OBJECTIVE: This study investigated whether medical student demographics impact their self-reported familiarity with the Post-Foundation Training Pathways (PFTPs) and Post-Foundation Application Process (PFAP).

METHODS: This was a cross-sectional study using a Bristol Online Survey. We invited all UK medical students to answer a range of questions about their demographics. Students were then asked to rank their familiarity with PFTPs and PFAP on a scale of 1 to 5 (1=least familiar and 5=most familiar). The responses were collected between March 2022 and April 2022 and exported for further analysis. Statistical analysis was conducted in Stata (version 17.1; StataCorp) using chi-square tests.

RESULTS: A total of 850 students from 31 UK medical schools took part. There was a significant difference between gender and self-reported familiarity with PFTPs (P<.001) and PFAP (P<.001), with male students expressing higher familiarity. Similarly, there was a difference between ethnicity and self-reported familiarity with PFTPs (P=.02) and PFAP (P<.001), with White students more likely to express higher familiarity than their Black, Asian, or Mixed Ethnic counterparts. Lastly, there was an overall difference between medical background and age and self-reported familiarity with PFTPs and PFAP (all P<.001), with students from medical backgrounds and older students being more likely to express higher familiarity.

CONCLUSIONS: The impact of gender, ethnicity, age, and medical background on students’ self-reported familiarity with PFTPs and PFAP is significant. Further studies are required to evaluate the impact of these factors on tested knowledge of PFTPs and PFAP and whether this impacts the success rate of postfoundation applications.

PMID:37999951 | DOI:10.2196/49013

J Med Internet Res. 2023 Nov 24;25:e43034. doi: 10.2196/43034.

ABSTRACT

BACKGROUND: Nonspecific low back pain (LBP) is a leading contributor to disability worldwide, and its socioeconomic burden is substantial. Self-management support is an important recommendation in clinical guidelines for the physiotherapy treatment of patients with LBP and may support cost-effective management. However, providing adequate individually tailored self-management support is difficult. The integration of web-based applications into face-to-face care (ie, blended care) seems promising to optimize tailored treatment and enhance patients’ self-management and, consequently, may reduce LBP-related costs.

OBJECTIVE: We aimed to evaluate the long-term effectiveness and cost-effectiveness of stratified blended physiotherapy (e-Exercise LBP) compared with face-to-face physiotherapy in patients with nonspecific LBP.

METHODS: An economic evaluation was conducted alongside a prospective, multicenter, cluster randomized controlled trial in primary care physiotherapy. Patients with nonspecific LBP were treated with either stratified blended physiotherapy (e-Exercise LBP) (n=104) or face-to-face physiotherapy (n=104). The content of both interventions was based on the Dutch physiotherapy guidelines for nonspecific LBP. Blended physiotherapy was stratified according to the patients’ risk of developing persistent LBP using the STarT Back Screening Tool. The primary clinical outcome was physical functioning (Oswestry Disability Index version 2.1a). For the economic evaluation, quality-adjusted life years (QALYs; EQ-5D-5L) and physical functioning were the primary outcomes. Secondary clinical outcomes included fear avoidance beliefs and self-reported adherence. Costs were measured from societal and health care perspectives using self-report questionnaires. Effectiveness was estimated using linear mixed models. Seemingly unrelated regression analyses were conducted to estimate total cost and effect differences for the economic evaluation.

RESULTS: Neither clinically relevant nor statistically substantial differences were found between stratified blended physiotherapy and face-to-face physiotherapy regarding physical functioning (mean difference [MD] -1.1, 95% CI -3.9 to 1.7) and QALYs (MD 0.026, 95% CI -0.020 to 0.072) over 12 months. Regarding the secondary outcomes, fear avoidance beliefs showed a statistically significant improvement in favor of stratified blended physiotherapy (MD -4.3, 95% CI -7.3 to -1.3). Societal and health care costs were higher for stratified blended physiotherapy than for face-to-face physiotherapy, but the differences were not statistically significant (societal: €972 [US $1027], 95% CI -€1090 to €3264 [US -$1151 to $3448]; health care: €73 [US $77], 95% CI -€59 to €225 [US -$62 to $238]). Among the disaggregated cost categories, only unpaid productivity costs were significantly higher for stratified blended physiotherapy. From both perspectives, a considerable amount of money must be paid per additional QALY or 1-point improvement in physical functioning to reach a relatively low to moderate probability (ie, 0.23-0.81) of stratified blended physiotherapy being cost-effective compared with face-to-face physiotherapy.

CONCLUSIONS: The stratified blended physiotherapy intervention e-Exercise LBP is neither more effective for improving physical functioning nor more cost-effective from societal or health care perspectives compared with face-to-face physiotherapy for patients with nonspecific LBP.

TRIAL REGISTRATION: ISRCTN 94074203; https://www.isrctn.com/ISRCTN94074203.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12891-020-3174-z.

PMID:37999947 | DOI:10.2196/43034

JMIR Diabetes. 2023 Nov 24;8:e49113. doi: 10.2196/49113.

ABSTRACT

BACKGROUND: Over the past few decades, diabetes has become a serious public health concern worldwide, particularly in Bangladesh. The advancement of artificial intelligence can be reaped in the prediction of blood glucose levels for better health management. However, the practical validity of machine learning (ML) techniques for predicting health parameters using data from low- and middle-income countries, such as Bangladesh, is very low. Specifically, Bangladesh lacks research using ML techniques to predict blood glucose levels based on basic noninvasive clinical measurements and dietary and sociodemographic information.

OBJECTIVE: To formulate strategies for public health planning and the control of diabetes, this study aimed to develop a personalized ML model that predicts the blood glucose level of urban corporate workers in Bangladesh.

METHODS: Based on the basic noninvasive health checkup test results, dietary information, and sociodemographic characteristics of 271 employees of the Bangladeshi Grameen Bank complex, 5 well-known ML models, namely, linear regression, boosted decision tree regression, neural network, decision forest regression, and Bayesian linear regression, were used to predict blood glucose levels. Continuous blood glucose data were used in this study to train the model, which then used the trained data to predict new blood glucose values.

RESULTS: Boosted decision tree regression demonstrated the greatest predictive performance of all evaluated models (root mean squared error=2.30). This means that, on average, our model’s predicted blood glucose level deviated from the actual blood glucose level by around 2.30 mg/dL. The mean blood glucose value of the population studied was 128.02 mg/dL (SD 56.92), indicating a borderline result for the majority of the samples (normal value: 140 mg/dL). This suggests that the individuals should be monitoring their blood glucose levels regularly.

CONCLUSIONS: This ML-enabled web application for blood glucose prediction helps individuals to self-monitor their health condition. The application was developed with communities in remote areas of low- and middle-income countries, such as Bangladesh, in mind. These areas typically lack health facilities and have an insufficient number of qualified doctors and nurses. The web-based application is a simple, practical, and effective solution that can be adopted by the community. Use of the web application can save money on medical expenses, time, and health management expenses. The created system also aids in achieving the Sustainable Development Goals, particularly in ensuring that everyone in the community enjoys good health and well-being and lowering total morbidity and mortality.

PMID:37999944 | DOI:10.2196/49113

Clin Chem Lab Med. 2023 Nov 24. doi: 10.1515/cclm-2023-0312. Online ahead of print.

ABSTRACT

OBJECTIVES: Blood microsampling, particularly dried blood spots (DBSs), is an attractive minimally-invasive approach that is well suited for home sampling and predictive medicine associated with longitudinal follow-up of the elderly. However, in vitro diagnostic quantification of biomarkers from DBS poses a major challenge. Clinical mass spectrometry can reliably quantify blood proteins in various research projects. Our goal here was to use mass spectrometry of DBS in a real-world clinical setting and compared it to the standard immunoassay method. We also sought to correlate DBS mass spectrometry measurements with clinical indices.

METHODS: A clinical trial of diagnostic equivalence was conducted to compare conventional venous samples quantified by immunoassay and DBSs quantified by mass spectrometry in an elderly population. We assayed three protein biomarkers of nutritional and inflammatory status: prealbumin (transthyretin), C-reactive protein, and transferrin.

RESULTS: The analysis of DBSs showed satisfactory variability and low detection limits. Statistical analysis confirmed that the two methods give comparable results at clinical levels of accuracy. In conclusion, we demonstrated, in a real-life setting, that DBSs can be used to measure prealbumin, CRP and transferrin, which are commonly used markers of nutritional status and inflammation in the elderly. However, there was no correlation with patient frailty for these proteins.

CONCLUSIONS: Early detection and regular monitoring of nutritional and inflammatory problems using DBS appear to be clinically feasible. This could help resolve major public health challenges in the elderly for whom frailty leads to serious risks of health complications.

PMID:37999931 | DOI:10.1515/cclm-2023-0312

Clin Chem Lab Med. 2023 Nov 24. doi: 10.1515/cclm-2023-0965. Online ahead of print.

ABSTRACT

OBJECTIVES: Monitoring quality control for a laboratory or network with multiple instruments measuring the same analyte is challenging. We present a retrospective assessment of a method to detect medically significant out-of-control error conditions across a group of instruments measuring the same analyte. The purpose of the model was to ensure that results from any of several instruments measuring the same analytes in a laboratory or a network of laboratories provide comparable results and reduce patient risk. Limited literature has described how to manage QC in these very common situations.

METHODS: Single Levey-Jennings control charts were designed using peer group target mean and control limits for five common clinical chemistry analytes in a network of eight analyzers in two different geographical sites. The QC rules used were 1_3s/2_2s/R_4s, with the mean being a peer group mean derived from a large population of the same instrument and the same QC batch mean and a group CV. The peer group data used to set the target means and limits were from a quality assurance program supplied by the instrument supplier. Both statistical and clinical assessments of significance were used to evaluate QC failure. Instrument bias was continually monitored.

RESULTS: It was demonstrated that the biases of each instrument were not statistically or clinically different compared to the peer group’s average over six months from February 2023 until July 2023. Over this period, the error rate determined by the QC model was consistent with statistical expectations for the 1_3s/2_2s/R_4s rule. There were no external quality assurance failures, and no detected error exceeded the TEa (medical impact). Thus, the combined statistical/clinical assessment reduced unnecessary recalibrations and the need to amend results.

CONCLUSIONS: This paper describes the successful implementation of a quality control model for monitoring a network of instruments, measuring the same analytes and using externally provided quality control targets. The model continually assesses individual instrument bias and imprecision while ensuring all instruments in the network meet clinical goals for quality. The focus of this approach is on detecting medically significant out-of-control error conditions.

PMID:37999926 | DOI:10.1515/cclm-2023-0965

J Med Syst. 2023 Nov 24;47(1):125. doi: 10.1007/s10916-023-02021-3.

ABSTRACT

OBJECTIVES: To evaluate the effectiveness of four large language models (LLMs) (Claude, Bard, ChatGPT4, and New Bing) that have large user bases and significant social attention, in the context of medical consultation and patient education in urolithiasis.

MATERIALS AND METHODS: In this study, we developed a questionnaire consisting of 21 questions and 2 clinical scenarios related to urolithiasis. Subsequently, clinical consultations were simulated for each of the four models to assess their responses to the questions. Urolithiasis experts then evaluated the model responses in terms of accuracy, comprehensiveness, ease of understanding, human care, and clinical case analysis ability based on a predesigned 5-point Likert scale. Visualization and statistical analyses were then employed to compare the four models and evaluate their performance.

RESULTS: All models yielded satisfying performance, except for Bard, who failed to provide a valid response to Question 13. Claude consistently scored the highest in all dimensions compared with the other three models. ChatGPT4 ranked second in accuracy, with a relatively stable output across multiple tests, but shortcomings were observed in empathy and human caring. Bard exhibited the lowest accuracy and overall performance. Claude and ChatGPT4 both had a high capacity to analyze clinical cases of urolithiasis. Overall, Claude emerged as the best performer in urolithiasis consultations and education.

CONCLUSION: Claude demonstrated superior performance compared with the other three in urolithiasis consultation and education. This study highlights the remarkable potential of LLMs in medical health consultations and patient education, although professional review, further evaluation, and modifications are still required.

PMID:37999899 | DOI:10.1007/s10916-023-02021-3

Metab Brain Dis. 2023 Nov 24. doi: 10.1007/s11011-023-01310-7. Online ahead of print.

ABSTRACT

To study the effects of different types of exercise on the plasma metabolomics of chronic unpredictable mild stress (CUMS)-induced depressed rats based on ¹H-NMR metabolomics techniques, and to explore the potential mechanisms of exercise for the treatment of depression. Rats were randomly divided into blank control group (C), CUMS control group (D), pre-exercise with CUMS group (P), CUMS with aerobic exercise group, CUMS with resistance exercise group (R), and CUMS with aerobic + resistance exercise group (E). The corresponding protocol intervention was applied to each group of rats. Body weight, sucrose preference and open field tests were performed weekly during the experiment to evaluate the extent of depression in rats. Plasma samples from each group of rats were collected at the end of the experiment, and then the plasma was analyzed by ¹H-NMR metabolomics combined with multivariate statistical analysis methods to identify differential metabolites and perform metabolic pathway analysis. (1) Compared with the group D, the body weight, sucrose preference rate, and the number of crossings and standings in the different types of exercise groups were significantly improved (p < 0.05 or p < 0.01). (2) Compared to group C, a total of 15 differential metabolites associated with depression were screened in the plasma of rats in group D, involving 6 metabolic pathways. Group P can regulate the levels of 6 metabolites: valine, lactate, inositol, glucose, phosphocreatine, acetoacetic acid. Group A can regulate the levels of 6 metabolites: N-acetylglycoprotein, leucine, lactate, low density lipoprotein, glucose and acetoacetic acid. Group R can regulate the levels of 6 metabolites: choline, lactate, inositol, glucose, phosphocreatine and acetoacetic acid. Group E can regulate the levels of 5 metabolites: choline, citric acid, glucose, acetone and acetoacetic acid. The different types of exercise groups can improve the depressive symptoms in CUMS rats, and there are common metabolites and metabolic pathways for their mechanism of effects. This study provides a powerful analytical tool to study the mechanism of the antidepressant effect of exercise, and provides an important method and basis for the early diagnosis, prevention and treatment of depression.

PMID:37999885 | DOI:10.1007/s11011-023-01310-7

CNS Drugs. 2023 Nov 24. doi: 10.1007/s40263-023-01050-3. Online ahead of print.

ABSTRACT

BACKGROUND: Real-world studies on fremanezumab, an anti-calcitonin gene-related peptide monoclonal antibody for migraine prevention, are few and with limited follow-up.

OBJECTIVE: We aimed to evaluate the long-term (up to 52 weeks) effectiveness and tolerability of fremanezumab in high-frequency episodic migraine and chronic migraine.

METHODS: This s an independent, prospective, multicenter cohort study enrolling outpatients in 17 Italian Headache Centers with high-frequency episodic migraine or chronic migraine and multiple preventive treatment failures. Patients were treated with fremanezumab 225 mg monthly. The primary outcomes included changes from baseline (1 month before treatment) in monthly headache days, response rates (reduction in monthly headache days from baseline), and persistence in medication overuse at months 3, 6, and 12 (all outcome timeframes refer to the stated month). Secondary outcomes included changes from baseline in acute medication intake and disability questionnaires scores at the same timepoints. A last observation carried forward analysis was also performed.

RESULTS: A total of 90 patients who received at least one dose of fremanezumab and with a potential 12-month follow-up were included. Among them, 15 (18.0%) patients discontinued treatment for the entire population, a reduction in monthly headache days compared with baseline was reported at month 3, with a significant median [interquartile range] reduction in monthly headache days (- 9.0 [11.5], p < 0.001). A statistically different reduction was also reported at month 6 compared with baseline (- 10.0 [12.0]; p < 0.001) and at 12 months of treatment (- 10.0 [14.0]; p < 0.001). The percentage of patients with medication overuse was significantly reduced compared with baseline from 68.7% (57/83) to 29.6% (24/81), 25.3% (19/75), and 14.7% (10/68) at 3, 6, and 12 months of treatment, respectively (p < 0.001). Acute medication use (days and total number) and disability scores were also significantly reduced (p < 0.001). A ≥ 50% response rate was achieved for 51.9, 67.9, and 76.5% of all patients at 3, 6, and 12 months, respectively. Last observation carried forward analyses confirmed these findings. Fremanezumab was well tolerated, with just one patient discontinuing treatment because of adverse events.

CONCLUSIONS: This study provides evidence for the real-world effectiveness of fremanezumab in treating both high-frequency episodic migraine and chronic migraine, with meaningful and sustained improvements in multiple migraine-related variables. No new safety issue was identified.

PMID:37999868 | DOI:10.1007/s40263-023-01050-3

J Cancer Surviv. 2023 Nov 24. doi: 10.1007/s11764-023-01482-2. Online ahead of print.

ABSTRACT

PURPOSE: This study assessed health-related quality of life (HRQoL) of long-term breast cancer (BC) survivors diagnosed at early stages and compare with cancer-free, age-matched women.

METHODS: The study population included BC survivors diagnosed with ductal carcinoma in situ (DCIS) or breast cancer stages I-II, who had undergone lumpectomy/mastectomy, with time since diagnosis ranging from 9 to 16 years. Survey was conducted at two tertiary hospitals in 2020. Data for cancer-free female controls was randomly drawn from a population-based survey and age-, education-matched with 1 case: 3 controls ratio. Self-reported HRQoL was assessed using EQ-5D with five dimentions. EQ-5D utility index score was calculated. Difference in EQ-5D score was evaluated using the Tobit regression model with adjustment for other covariates.

RESULTS: Of 273 survivors. 88% and 12% underwent mastectomy and lumpectomy, respectively. The mean (standard deviation, SD) age at survey was 57.3 (8.5) years old. BC survivors reported significantly more problems performing daily activities (11% vs. 5%, p < 0.001), pain/discomfort (46% vs. 23%, p < 0.001), and anxious/depressed feelings (44% vs. 8%, p < 0.001) relative to the controls. Difference in EQ-5D score between BC survivors and the general population was higher in older age groups. The overall EQ-5D score of BC survivors was statistically lower than that of the control subjects (adjusted [Formula: see text]=0.117, p < 0.001).

CONCLUSION: Long-term BC survivors who survived beyond ten years post-diagnosis experience more pain, anxiety, and distress, leading to an overall poorer HRQoL.

IMPLICATIONS FOR CANCER SURVIVORS: This study suggest the importance of follow-up care, particularly focusing on pain, anxiety, and distress management to enhance the HRQoL of long-term BC survivors.

PMID:37999857 | DOI:10.1007/s11764-023-01482-2