Nevin Manimala

Vascular. 2024 Jun 17:17085381241262575. doi: 10.1177/17085381241262575. Online ahead of print.

ABSTRACT

OBJECTIVE: This study used unsupervised machine learning (UML) cluster analysis to explore clinical phenotypes of endovascular aortic repair (EVAR) for abdominal aortic aneurysm (AAA) patients based on radiomics.

METHOD: We retrospectively reviewed 1785 patients with infra-renal AAA who underwent elective EVAR procedures between January 2010 and December 2020. Pyradiomics was used to extract the radiomics features. Statistical analysis was applied to determine the radiomics features that related to severe adverse events (SAEs) after EVAR. The selected features were used for UML cluster analysis in training set and validation in test set. Comparison of basic characteristics and radiomics features of different clusters. The Kaplan-Meier analysis was conducted to generate the cumulative incidence of freedom from SAEs rate.

RESULT: A total of 1180 patients were enrolled. During the follow-up, 353 patients experienced EVAR-related SAEs. In total, 1223 radiomics features were extracted from each patient, of which 23 radiomics features were finally preserved to identify different clinical phenotypes. 944 patients were allocated to the training set. Three clusters were identified in training set, in which patients had identical clinical characteristics and morphological features, while varied considerably of selected radiomics features. This encouraging performance was further approved in the test set. In addition, each cluster was well differentiated from other clusters and Kaplan-Meier analysis showed significant differences of freedom from SAEs rate between different clusters both in the training (p = .0216) and test sets (p = .0253).

CONCLUSION: Based on radiomics, UML cluster analysis can identify clinical phenotypes in EVAR patients with distinct long-term outcomes.

PMID:38885967 | DOI:10.1177/17085381241262575

Stat Med. 2024 Jun 17. doi: 10.1002/sim.10151. Online ahead of print.

ABSTRACT

Recent advances in engineering technologies have enabled the collection of a large number of longitudinal features. This wealth of information presents unique opportunities for researchers to investigate the complex nature of diseases and uncover underlying disease mechanisms. However, analyzing such kind of data can be difficult due to its high dimensionality, heterogeneity and computational challenges. In this article, we propose a Bayesian nonparametric mixture model for clustering high-dimensional mixed-type (eg, continuous, discrete and categorical) longitudinal features. We employ a sparse factor model on the joint distribution of random effects and the key idea is to induce clustering at the latent factor level instead of the original data to escape the curse of dimensionality. The number of clusters is estimated through a Dirichlet process prior. An efficient Gibbs sampler is developed to estimate the posterior distribution of the model parameters. Analysis of real and simulated data is presented and discussed. Our study demonstrates that the proposed model serves as a useful analytical tool for clustering high-dimensional longitudinal data.

PMID:38885953 | DOI:10.1002/sim.10151

Int J Pediatr Otorhinolaryngol. 2024 Jun 5;182:112001. doi: 10.1016/j.ijporl.2024.112001. Online ahead of print.

ABSTRACT

INTRODUCTION: The neural response telemetry (NRT) is a standard procedure in cochlear implantation mostly used to determine the functionality of implanted device and to check auditory nerve responds to the stimulus. Correlation between NRT measurements and subjective threshold (T) and maximum comfort (C) levels has been reported but results are inconsistent, and it is still not clear which of the NRT measurements could be the most useful in predicting fitting levels.

PURPOSE: In our study we aimed to investigate which NRT measurement corresponds better to fitting levels. Impedance (IMP), Evoked Action Potential (ECAP) threshold and amplitude growth function (AGF) slope values were included in the study. Also, we tried to identify cochlear area at which the connection between NRT measurements and fitting levels would be the most pronounced.

MATERIALS AND METHODS: Thirty-one children implanted with Cochlear device were included in this retrospective study. IMP, ECAP thresholds and AGF were obtained intra-operatively and 12 months after surgery at electrodes 5, 11 and 19 as representative for each part of cochlea. Subjective T and C levels were obtained 12 months after the surgery during cochlear fitting.

RESULTS: ECAP thresholds obtained 12 months after surgery showed statistically significant correlation to both T and C levels at all 3 selected electrodes. IMP correlated with C levels while AGF showed tendency to correlate with T levels. However, these correlations were not statistically significant for all electrodes.

CONCLUSION: ECAP threshold measurements correlated to T and C values better than AGF slope and IMP. Measurements obtained twelve months after surgery seems to be more predictive of T and C values compared to intra-operative measurements. The best correlation between ECAP threshold and T and C values was found at electrode 11 suggesting NRT measurements at mid-portion cochlear region to be the most useful in predicting fitting levels.

PMID:38885546 | DOI:10.1016/j.ijporl.2024.112001

Swiss Med Wkly. 2024 Jun 17;154:3425. doi: 10.57187/s.3425.

ABSTRACT

BACKGROUND: In the context of an ageing population and increasing health needs, primary care reform is needed and several new models have emerged, including the introduction of case managers in general practitioner practices.

AIM: To describe the frequency of case managers in general practices in eleven Western countries between 2012 and 2019 and to investigate the characteristics of general practitioners and their practices associated with case manager frequency.

METHODS: A secondary analysis of the Commonwealth Fund International Health Policy Surveys of Primary Care Physicians, which were international cross-sectional studies conducted in 2012, 2015 and 2019. Random samples of general practitioners were selected in 11 Western countries (2012: n = 9776; 2015: n = 12,049; 2019: n = 13,200). The use of case managers in general practitioner practices was determined with the question “Does your practice use personnel, such as nurses or case managers, to monitor and manage care for patients with chronic conditions that need regular follow-up care?”, with possible answers “Yes, within the practice”, “Yes, outside the practice”, “Yes, both within and outside the practice” or “No”. Other variables characterising general practitioners and their practices were considered. Mixed-effects logistic regression was performed.

RESULTS: The frequency of case managers within general practitioner practices varied greatly by country, with an overall trend towards an increase from 2012 to 2019. In the multivariate analysis, more case managers were found in practices located in small towns (odds ratio [OR] 1.4; 95% confidence interval [CI] 1.2-1.7) and in rural areas (OR 1.9; 95% CI 1.5-2.4) compared to cities. The frequency of case managers was higher in larger practices, as shown in comparisons of practices in the second, third and fourth quartile of full-time equivalent employee counts compared to those in the first quartile (Q2: OR 1.7, 95% CI 1.4-1.9; Q3: OR 2.1, 95% CI 1.6-2.9; Q4: OR 3.8, 95% CI 3.0-4.9). There was no significant difference in frequency with respect to the age and sex of the general practitioners.

CONCLUSION: The use of case managers in general practitioner practices is a promising approach, but its practice varies greatly. This practice has been developing in Western countries and is tending to increase. The implementation of case managers seems to be associated with certain characteristics linked to general practitioner practices (practice location, practice size), whereas it does not seem to depend on the personal characteristics of general practitioners, such as age or sex.

PMID:38885527 | DOI:10.57187/s.3425

Medwave. 2024 Jun 17;24(5):e2781. doi: 10.5867/medwave.2024.05.2781.

ABSTRACT

INTRODUCTION: Updating recommendations for guidelines requires a comprehensive and efficient literature search. Although new information platforms are available for developing groups, their relative contributions to this purpose remain uncertain.

METHODS: As part of a review/update of eight selected evidence-based recommendationsfor type 2 diabetes, we evaluated the following five literature search approaches (targeting systematic reviews, using predetermined criteria): PubMed for MEDLINE, Epistemonikos database basic search, Epistemonikos database using a structured search strategy, Living overview of evidence (L.OVE) platform, and TRIP database. Three reviewers independently classified the retrieved references as definitely eligible, probably eligible, or not eligible. Those falling in the same “definitely” categories for all reviewers were labelled as “true” positives/negatives. The rest went to re-assessment and if found eligible/not eligible by consensus became “false” negatives/positives, respectively. We described the yield for each approach and computed “diagnostic accuracy” measures and agreement statistics.

RESULTS: Altogether, the five approaches identified 318 to 505 references for the eight recommendations, from which reviewers considered 4.2 to 9.4% eligible after the two rounds. While Pubmed outperformed the other approaches (diagnostic odds ratio 12.5 versus 2.6 to 5.3), no single search approach returned eligible references for all recommendations. Individually, searches found up to 40% of all eligible references (n = 71), and no combination of any three approaches could find over 80% of them. Kappa statistics for retrieval between searches were very poor (9 out of 10 paired comparisons did not surpass the chance-expected agreement).

CONCLUSION: Among the information platforms assessed, PubMed appeared to be more efficient in updating this set of recommendations. However, the very poor agreement among search approaches in the reference yield demands that developing groups add information from several (probably more than three) sources for this purpose. Further research is needed to replicate our findings and enhance our understanding of how to efficiently update recommendations.

PMID:38885522 | DOI:10.5867/medwave.2024.05.2781

Ann Intern Med. 2024 Jun 18. doi: 10.7326/M23-2038. Online ahead of print.

ABSTRACT

BACKGROUND: Metformin is a first-line pharmacotherapy for type 2 diabetes, but there is limited evidence about its safety in early pregnancy.

OBJECTIVE: To evaluate the teratogenicity of metformin use in the first trimester of pregnancy.

DESIGN: In an observational cohort of pregnant women with pregestational type 2 diabetes receiving metformin monotherapy before the last menstrual period (LMP), a target trial with 2 treatment strategies was emulated: insulin monotherapy (discontinue metformin treatment and initiate insulin within 90 days of LMP) or insulin plus metformin (continue metformin and initiate insulin within 90 days of LMP).

SETTING: U.S. Medicaid health care administration database (2000 to 2018).

PARTICIPANTS: 12 489 pregnant women who met the eligibility criteria.

MEASUREMENTS: The risk and risk ratio of nonlive births, live births with congenital malformations, and congenital malformations among live births were estimated using standardization to adjust for covariates.

RESULTS: A total of 850 women were in the insulin monotherapy group and 1557 in the insulin plus metformin group. The estimated risk for nonlive birth was 32.7% under insulin monotherapy (reference) and 34.3% under insulin plus metformin (risk ratio, 1.02 [95% CI, 1.01 to 1.04]). The estimated risk for live birth with congenital malformations was 8.0% (CI, 5.7% to 10.2%) under insulin monotherapy and 5.7% (CI, 4.5% to 7.3%) under insulin plus metformin (risk ratio, 0.72 [CI, 0.51 to 1.09]).

LIMITATION: Possible residual confounding by glycemic control and body mass index.

CONCLUSION: Compared with switching to insulin monotherapy, continuing metformin and adding insulin in early pregnancy resulted in little to no increased risk for nonlive birth among women receiving metformin before pregnancy. Under conventional statistical criteria, anything between a 49% decrease and a 9% increase in risk for congenital malformations was highly compatible with our data.

PRIMARY FUNDING SOURCE: National Institutes of Health.

PMID:38885505 | DOI:10.7326/M23-2038

JMIR Form Res. 2024 Jun 17;8:e56687. doi: 10.2196/56687.

ABSTRACT

BACKGROUND: Internet medical treatment, also known as telemedicine, represents a paradigm shift in health care delivery. This contactless model allows patients to seek medical advice remotely, often before they physically visit a doctor’s clinic. Herein, physicians are in a relatively passive position, as patients browse and choose their health care providers. Although a wealth of experience is undoubtedly a draw for many patients, it remains unclear which specific facets of a doctor’s credentials and accomplishments patients prioritize during their selection process.

OBJECTIVE: Our primary aim is to delve deeper into the correlation between physicians’ static characteristics-such as their qualifications, experiences, and profiles on the internet-and the number of patient visits they receive. We seek to achieve this by analyzing comprehensive internet hospital data from public hospitals. Furthermore, we aim to offer insights into how doctors can present themselves more effectively on web-based platforms, thereby attracting more patients and improving overall patient satisfaction.

METHODS: We retrospectively gathered web-based diagnosis and treatment data from the First Affiliated Hospital of Guangxi Medical University in 2023. These data underwent rigorous analysis, encompassing basic descriptive statistics, correlation analyses between key factors in doctors’ internet-based introductions, and the number of patient consultation visits. Additionally, we conducted subgroup analyses to ascertain the independence of these vital factors. To further distill the essence from these data, we used nonnegative matrix factorization to identify crucial demographic characteristics that significantly impact patient choice.

RESULTS: The statistical results suggested that there were significant differences in the distribution of consultation volume (P<.001), and the correlation analysis results suggested that there was a strong correlation between the two groups of data (ρ=0.93; P<.001). There was a correlation between the richness of a profile and popularity (P<.001). Patients were more interested in physicians with advanced titles, doctoral degrees, social activities, and scientific achievements (P<.001) as well as other institutional visit experiences (P=.003). More prosperous social activities, scientific achievements, experiences of other institutional visits, and awards were more common among people with advanced professional titles. Doctoral degrees remained attractive to patients when data were limited to senior physicians (P<.001). Patients trusted the medical staff with advanced titles, social activities, scientific achievements, and doctoral degrees (P<.001).

CONCLUSIONS: Patient preferences for choosing a health care provider differed significantly between free and paid consultations. Notably, patients tended to trust doctors with advanced professional titles more and were more likely to seek out those with doctoral qualifications over other professional ranks. Additionally, physicians who actively participated in social events and scientific endeavors often had an advantage in attracting new patients. Given these insights, doctors who invest in enhancing their personal and professional experiences within these domains are likely to see increased popularity and patient satisfaction.

PMID:38885498 | DOI:10.2196/56687

Lupus. 2024 Jun 17:9612033241260334. doi: 10.1177/09612033241260334. Online ahead of print.

ABSTRACT

OBJECTIVE: In this pilot study, we used untargeted metabolomics to identify biochemical mechanisms or biomarkers potentially underlying SLE-related fatigue.

METHODS: Metabolon conducted untargeted metabolomic plasma profiling using ultrahigh performance liquid chromatography/tandem mass spectrometry on plasma samples of 23 Black females with systemic lupus erythematosus (SLE) and 21 no SLE controls. Fatigue phenotypes of general fatigue, physical fatigue, mental fatigue, reduced activity, and reduced motivation were measured with the reliable and valid Multidimensional Fatigue Inventory (MFI).

RESULTS: A total of 290 metabolites were significantly different between the SLE and no SLE groups, encompassing metabolites related to glycolysis, TCA cycle activity, heme catabolism, branched chain amino acids, fatty acid metabolism, and steroids. Within the SLE group, controlling for age and co-morbidities, TCA cycle metabolites of alpha-ketoglutarate (AKG) and succinate were statistically significantly associated (p < .05) with physical and general fatigue.

CONCLUSION: While pervasive perturbations in the entire TCA cycle have been implicated as a potential mechanism for fatigue, our results suggest individual metabolites of AKG and succinate may be potential biomarkers or targets of intervention for fatigue symptom management in SLE. Additionally, perturbations in heme metabolism in the SLE group provide additional insights into mechanisms that promote systemic inflammation.

PMID:38885489 | DOI:10.1177/09612033241260334

Anesth Analg. 2024 Jul 1;139(1):211-219. doi: 10.1213/ANE.0000000000006967. Epub 2024 Jun 17.

ABSTRACT

BACKGROUND: Postoperative acute kidney injury (PO-AKI) is a frequent complication after surgery. Various tools have been proposed to identify patients at high risk for AKI, including preoperative serum creatinine or estimated glomerular filtration rate (eGFR), urinary cell cycle arrest, and tubular damage biomarkers; however, none of these can appropriately assess AKI risk before surgery. Renal functional reserve (RFR) screened by the Doppler-derived intraparenchymal renal resistive index variation (IRRIV) test has been proposed to identify patients at risk for AKI before a kidney insult. IRRIV test has been developed in healthy individuals and previously investigated in cardiac surgery patients. This study aims to evaluate the value of the IRRIV test in identifying PO-AKI among patients undergoing robotic abdominal surgery in the Trendelenburg position for pelvic oncological disease.

METHODS: We performed a prospective, double-blinded, observational study. Preoperative baseline renal function and RFR were assessed in 53 patients with baseline eGFR >60 mL/min/1.73 m2, undergoing robotic surgery in the Trendelenburg position for pelvic oncological disease. The capability of Doppler-derived RFR in predicting PO-AKI was investigated with the area under the receiver operating characteristic curve (ROC-AUC).

RESULTS: Approximately 15.1% of patients developed AKI within the first 3 postoperative days. Thirty-one (58.5%) patients had a physiologic delta-RRI (ie, ≥0.05), while 22 (41.5%) patients did not. The ROC-AUC for PO-AKI was 0.85 (95% confidence interval [CI], 0.74-0.97; P = .007) for serum creatinine, 0.84 (95% CI, 0.71-0.96; P = .006) for eGFR, and 0.84 (95% CI, 0.78-0.91; P = .017) for delta-RRI. When combined with eGFR, the ROC-AUC for delta-RRI was 0.95 (95% CI, 0.9-1).

CONCLUSIONS: Our findings show that the preoperative assessment of Doppler-derived RFR combined with baseline renal function improves the capability of identifying patients at high risk for PO-AKI with eGFR >60 mL/min/1.73 m2 after robotic abdominal surgery in Trendelenburg position for pelvic oncological disease.

PMID:38885478 | DOI:10.1213/ANE.0000000000006967

JCO Oncol Pract. 2024 Jun 17:OP2400016. doi: 10.1200/OP.24.00016. Online ahead of print.

ABSTRACT

PURPOSE: This study used willingness-to-pay (WTP) exercises to explore the relationships between race, financial toxicity, and treatment decision making among people with cancer.

METHODS: A convenience sample of people with multiple myeloma who attended an academic medical center in 2022 was surveyed. Financial toxicity was assessed by the Comprehensive Score for financial Toxicity, with scores <26 indicating financial toxicity. WTP was assessed with (1) a discrete choice experiment (DCE), (2) fixed-choice tasks, and (3) a bidding game.

RESULTS: In total, 156 people were approached, and 130 completed the survey. The majority of the sample was White (n = 99), whereas 24% (n = 31) was African American or Black. Forty-six percent (n = 60) of the sample were experiencing financial toxicity. In the DCE, the relative importance of cost was twice as high for those with financial toxicity (30% compared with 14%; P < .001). In the fixed-choice tasks, they were twice as likely to accept a treatment with shorter progression-free survival but lower costs (adjusted odds ratio [aOR], 2.47; P = .049). In the bidding game, the median monthly WTP of those with financial toxicity was half that of those without ($100 in US dollars [USD] compared with $200 USD; P < .001). Only in the bidding game was race statistically associated with WTP; after controlling for financial toxicity, African American or Black participants were three times as likely (aOR, 3.06; P = .007) to report a lower WTP.

CONCLUSION: Across all three exercises, participants with financial toxicity reported lower WTP than those without. As financial toxicity disproportionally affects some segments of patients, it is possible that financial toxicity contributes to cancer disparities.

PMID:38885465 | DOI:10.1200/OP.24.00016