Relationship between popularity and the likely efficacy: an observational study based on a random selection on top-ranked physical activity apps.
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ABSTRACT:
SUBMITTER: Bondaronek P
PROVIDER: S-EPMC6886953 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Importance:Hospital networks formed around top-ranked cancer hospitals represent an opportunity to optimize complex cancer care in the community. Objective:To compare the short- and long-term survival after complex cancer treatment at top-ranked cancer hospitals and the affiliates of top-ranked hospitals. Design, Setting, and Participants:This cohort study was conducted using data from the unabridged version of the National Cancer Database. Included patients were individuals 18 years or older who underwent surgical treatment for esophageal, gastric, lung, pancreatic, colorectal, or bladder cancer diagnosed between January 1, 2012, and December 31, 2016. Patient outcomes after complex surgical procedures for cancer at top-ranked cancer hospitals (as ranked in top 50 by US News and World Report) were compared with outcomes at affiliates of top-ranked cancer hospitals (affiliation listed in American Hospitals Association survey and confirmed by search of internet presence). Data were analyzed from July through December 2019. Exposures:Undergoing complex cancer treatment at a top-ranked cancer hospital or an affiliated hospital. Main Outcomes and Measures:The association of affiliate status with short-term survival (ie, 90-day mortality) was compared using logistic regression, and the association of affiliate status with long-term survival was compared using time-to-event models, adjusting for patient demographic, payer, clinical, and treatment factors. Results:Among 119?834 patients who underwent surgical treatment for cancer, 79?981 patients (66.7%) were treated at top-ranked cancer hospitals (median [interquartile range] age, 66 [58-74] years; 40?910 [54.9%] men) and 39?853 patients (33.3%) were treated at affiliate hospitals (median [interquartile range] age, 69 [60-77] years; 19?004 [50.0%] men). In a pooled analysis of all cancer types, adjusted perioperative mortality within 90 days of surgical treatment was higher at affiliate hospitals compared with top-ranked hospitals (odds ratio, 1.67 [95% CI, 1.49-1.89]; P?<?.001). Adjusted long-term survival following cancer treatment at affiliate hospitals was only 77% that of top-ranked hospitals (time ratio, 0.77 [95% CI, 0.72-0.83]; P?<?.001). The survival advantage was not fully explained by differences in annual surgical volume, with both long- and short-term survival remaining superior at top-ranked hospitals even after models were adjusted for volume. Conclusions and Relevance:These findings suggest that short- and long-term survival after complex cancer treatment were superior at top-ranked hospitals compared with affiliates of top-ranked hospitals. Further study of cancer care within top-ranked cancer networks could reveal collaborative opportunities to improve survival across a broad contingent of the US population.
| S-EPMC7251445 | biostudies-literature
Project description:ObjectiveTo examine outcomes of Medicare enrollees who underwent primary total knee arthroplasty (TKA) in top-ranked orthopedic hospitals identified through the U.S. News & World Report hospital rankings and 2 comparison groups of hospitals.Patients and methodsWe used Medicare Part A data to identify patients who underwent primary TKA between January 1, 2006, and December 31, 2006, in 3 groups of hospitals: (1) top-ranked according to U.S. News & World Report rankings; (2) not top-ranked, but eligible for ranking; and (3) not eligible for ranking by U.S. News & World Report. We compared the demographics and comorbidity of patients treated in the 3 hospital groups. We examined rates of postoperative adverse outcomes--a composite consisting of hemorrhage, pulmonary embolism, deep vein thrombosis, wound infection, myocardial infarction, or mortality within 30 days of surgery. We also compared 30-day all-cause readmission rates and hospital length of stay (LOS) across groups.ResultsOur cohort consisted of 48 top-ranked hospitals (performing 10,477 primary TKAs), 288 eligible non-top-ranked hospitals (28,938 TKAs), and 481 hospitals not eligible for ranking (25,297 TKAs). Unadjusted rates of the composite outcome were modestly higher for top-ranked hospitals (4.3%, 455 patients) as compared with non-top-ranked hospitals (4.1%, 1191 patients) and hospitals ineligible for ranking (3.3%, 843 patients) (P<.001), but these differences were no longer significant after accounting for differences in patient complexity. Likewise, there were no significant differences in readmission rates or LOS across groups.ConclusionRates of postoperative complications and readmission and hospital LOS were similar for Medicare patients who underwent primary TKA in top-ranked and non-top-ranked hospitals.
| S-EPMC3538414 | biostudies-literature
Project description:With considerable accumulation of RNA-Seq transcriptome data, we have extended our understanding about protein-coding gene transcript compositions. However, alternatively compounded patterns of human protein-coding gene transcripts would complicate gene expression data processing and interpretation. It is essential to exhaustively interrogate complex mRNA isoforms of protein-coding genes with an unified data resource. In order to investigate representative mRNA transcript isoforms to be utilized as transcriptome analysis references, we utilized GTEx data to establish a top-ranked transcript isoform expression data resource for human protein-coding genes. Distinctive tissue specific expression profiles and modulations could be observed for individual top-ranked transcripts of protein-coding genes. Protein-coding transcripts or genes do occupy much higher expression fraction in transcriptome data. In addition, top-ranked transcripts are the dominantly expressed ones in various normal tissues. Intriguingly, some of the top-ranked transcripts are noncoding splicing isoforms, which imply diverse gene regulation mechanisms. Comprehensive investigation on the tissue expression patterns of top-ranked transcript isoforms is crucial. Thus, we established a web tool to examine top-ranked transcript isoforms in various human normal tissue types, which provides concise transcript information and easy-to-use graphical user interfaces. Investigation of top-ranked transcript isoforms would contribute understanding on the functional significance of distinctive alternatively spliced transcript isoforms.
| S-EPMC7530651 | biostudies-literature
Project description:ImportanceLeading cancer hospitals have increasingly shared their brands with other hospitals through growing networks of affiliations. However, the brand of top-ranked cancer hospitals may evoke distinct reputations for safety and quality that do not extend to all hospitals within these networks.ObjectiveTo assess perioperative mortality of Medicare beneficiaries after complex cancer surgery across hospitals participating in networks with top-ranked cancer hospitals.Design, setting, and participantsA cross-sectional study was performed of the Centers for Medicare & Medicaid Services 100% Medicare Provider and Analysis Review file from January 1, 2013, to December 31, 2016, for top-ranked cancer hospitals (as assessed by U.S. News and World Report) and affiliated hospitals that share their brand. Participants were 29 228 Medicare beneficiaries older than 65 years who underwent complex cancer surgery (lobectomy, esophagectomy, gastrectomy, colectomy, and pancreaticoduodenectomy [Whipple procedure]) between January 1, 2013, and October 1, 2016.ExposuresUndergoing complex cancer surgery at a top-ranked cancer hospital vs an affiliated hospital.Main outcomes and measuresRisk-adjusted 90-day mortality estimated using hierarchical logistic regression and comparison of the relative safety of hospitals within each cancer network estimated using standardized mortality ratios.ResultsA total of 17 300 patients (59.2%; 8612 women and 8688 men; mean [SD] age, 74.7 [6.2] years) underwent complex cancer surgery at 59 top-ranked hospitals and 11 928 patients (40.8%; 6287 women and 5641 men; mean [SD] age, 76.2 [6.9] years) underwent complex cancer surgery at 343 affiliated hospitals. Overall, surgery performed at affiliated hospitals was associated with higher 90-day mortality (odds ratio, 1.40; 95% CI, 1.23-1.59; P < .001), with odds ratios that ranged from 1.32 (95% CI, 1.12-1.56; P = .001) for colectomy to 2.04 (95% CI, 1.41-2.95; P < .001) for gastrectomy. When the relative safety of each top-ranked cancer hospital was compared with its collective affiliates, the top-ranked hospital was safer than the affiliates in 41 of 49 studied networks (83.7%; 95% CI, 73.1%-93.3%).Conclusions and relevanceThe likelihood of surviving complex cancer surgery appears to be greater at top-ranked cancer hospitals compared with the affiliated hospitals that share their brand. Further investigation of performance across trusted cancer networks could enhance informed decision making for complex cancer care.
| S-EPMC6481444 | biostudies-literature
Project description:Rank aggregation (RA), the process of combining multiple ranked lists into a single ranking, has played an important role in integrating information from individual genomic studies that address the same biological question. In previous research, attention has been focused on aggregating full lists. However, partial and/or top ranked lists are prevalent because of the great heterogeneity of genomic studies and limited resources for follow-up investigation. To be able to handle such lists, some ad hoc adjustments have been suggested in the past, but how RA methods perform on them (after the adjustments) has never been fully evaluated. In this article, a systematic framework is proposed to define different situations that may occur based on the nature of individually ranked lists. A comprehensive simulation study is conducted to examine the performance characteristics of a collection of existing RA methods that are suitable for genomic applications under various settings simulated to mimic practical situations. A non-small cell lung cancer data example is provided for further comparison. Based on our numerical results, general guidelines about which methods perform the best/worst, and under what conditions, are provided. Also, we discuss key factors that substantially affect the performance of the different methods.
| S-EPMC6357556 | biostudies-literature
Project description:In genomic research, it is becoming increasingly popular to perform meta-analysis, the practice of combining results from multiple studies that target a common essential biological problem. Rank aggregation, a robust meta-analytic approach, consolidates such studies at the rank level. There exists extensive research on this topic, and various methods have been developed in the past. However, these methods have two major limitations when they are applied in the genomic context. First, they are mainly designed to work with full lists, whereas partial and/or top-ranked lists prevail in genomic studies. Second, the component studies are often clustered, and the existing methods fail to utilize such information. To address the above concerns, a Bayesian latent variable approach, called BiG, is proposed to formally deal with partial and top-ranked lists and incorporate the effect of clustering. Various reasonable prior specifications for variance parameters in hierarchical models are carefully studied and compared. Simulation results demonstrate the superior performance of BiG compared with other popular rank aggregation methods under various practical settings. A non-small-cell lung cancer data example is analyzed for illustration.
| S-EPMC6235700 | biostudies-literature
Project description:BackgroundSpine-related research continues to evolve rapidly and in the paradigm of increasing data, evidence-based practice becomes imperative. Citation-based rankings are thus critical in allowing clinicians to quickly ascertain the importance and value of a study. The purpose of this article is to report on the 10 most cited articles in the field of spine surgery over the last 10 years to provide an insight into the direction of research and clinical endeavors.MethodsGoogle Scholar was searched (1st April 2021) using an algorithm that sorts all cited spine surgery publications based on the number of citations per year. The top 10 most cited articles were identified. Information including journal, publication title, published year, subspecialty, and purpose of the study were compiled.ResultsThe top 10 publications ranged from 471 to 66 citations, with yearly citations ranging from 67 to 14. Eight articles directly related to lumbar fusion, 2 related to 3D Printing in spinal surgery, and one article on robotic surgery. There were 4 retrospective studies, 1 randomized controlled trial (RCT), and 2 systematic reviews. 3 of the papers related to decision making in surgery, 4 on outcomes of surgery, and 3 on innovations in surgery. The journal that appeared most frequently in the top 10 list was the Journal of Spine Surgery.DiscussionNovel surgical approaches or management strategies are almost always a manifestation of advancements in clinical and basic science research. Algorithm-based identification of highly cited articles provides an effective and prompt avenue for evidence-based medicine. Our ranking found a predominance of publications related to lumbar spinal fusion. Several articles in the top 10 provide an in-depth discussion on novel surgical techniques and technologies that define the current epoch of innovations in spine surgery.
| S-EPMC8339864 | biostudies-literature
Project description:BACKGROUND:In the last decade, there has been a proliferation of mobile apps claiming to support the needs of people living with depression. However, it is unclear what functionality is actually provided by apps for depression, or for whom they are intended. OBJECTIVE:This paper aimed to explore the key features of top-rated apps for depression, including descriptive characteristics, functionality, and ethical concerns, to better inform the design of apps for depression. METHODS:We reviewed top-rated iPhone OS (iOS) and Android mobile apps for depression retrieved from app marketplaces in spring 2019. We applied a systematic analysis to review the selected apps, for which data were gathered from the 2 marketplaces and through direct use of the apps. We report an in-depth analysis of app functionality, namely, screening, tracking, and provision of interventions. Of the initially identified 482 apps, 29 apps met the criteria for inclusion in this review. Apps were included if they remained accessible at the moment of evaluation, were offered in mental health-relevant categories, received a review score greater than 4.0 out of 5.0 by more than 100 reviewers, and had depression as a primary target. RESULTS:The analysis revealed that a majority of apps specify the evidence base for their intervention (18/29, 62%), whereas a smaller proportion describes receiving clinical input into their design (12/29, 41%). All the selected apps are rated as suitable for children and adolescents on the marketplace, but 83% (24/29) do not provide a privacy policy consistent with their rating. The findings also show that most apps provide multiple functions. The most commonly implemented functions include provision of interventions (24/29, 83%) either as a digitalized therapeutic intervention or as support for mood expression; tracking (19/29, 66%) of moods, thoughts, or behaviors for supporting the intervention; and screening (9/29, 31%) to inform the decision to use the app and its intervention. Some apps include overtly negative content. CONCLUSIONS:Currently available top-ranked apps for depression on the major marketplaces provide diverse functionality to benefit users across a range of age groups; however, guidelines and frameworks are still needed to ensure users' privacy and safety while using them. Suggestions include clearly defining the age of the target population and explicit disclosure of the sharing of users' sensitive data with third parties. In addition, we found an opportunity for apps to better leverage digital affordances for mitigating harm, for personalizing interventions, and for tracking multimodal content. The study further demonstrated the need to consider potential risks while using depression apps, including the use of nonvalidated screening tools, tracking negative moods or thinking patterns, and exposing users to negative emotional expression content.
| S-EPMC7007593 | biostudies-literature
Project description:Feature selection is a practical approach for improving the performance of text classification methods by optimizing the feature subsets input to classifiers. In traditional feature selection methods such as information gain and chi-square, the number of documents that contain a particular term (i.e. the document frequency) is often used. However, the frequency of a given term appearing in each document has not been fully investigated, even though it is a promising feature to produce accurate classifications. In this paper, we propose a new feature selection scheme based on a term event Multinomial naive Bayes probabilistic model. According to the model assumptions, the matching score function, which is based on the prediction probability ratio, can be factorized. Finally, we derive a feature selection measurement for each term after replacing inner parameters by their estimators. On a benchmark English text datasets (20 Newsgroups) and a Chinese text dataset (MPH-20), our numerical experiment results obtained from using two widely used text classifiers (naive Bayes and support vector machine) demonstrate that our method outperformed the representative feature selection methods.
| S-EPMC5381872 | biostudies-literature
Project description:BACKGROUND:Regular moderate to vigorous physical activity is essential for maintaining health and preventing the onset of chronic diseases. Both global rates of smartphone ownership and the market for physical activity and fitness apps have grown rapidly in recent years. The use of physical activity and fitness apps may assist the general population in reaching evidence-based physical activity recommendations. However, it remains unclear whether there are evidence-informed physical activity apps and whether behavior change techniques (BCTs) previously identified as effective for physical activity promotion are used in these apps. OBJECTIVE:This study aimed to identify English and German evidence-informed physical activity apps and BCT employment in those apps. METHODS:We identified apps in a systematic search using 25 predefined search terms in the Google Play Store. Two reviewers independently screened the descriptions of apps and screenshots applying predefined inclusion and exclusion criteria. Apps were included if (1) their description contained information about physical activity promotion; (2) they were in English or German; (3) physical activity recommendations of the World Health Organization or the American College of Sports Medicine were mentioned; and (4) any kind of objective physical activity measurement was included. Two researchers downloaded and tested apps matching the inclusion criteria for 2 weeks and coded their content using the Behavioral Change Technique Taxonomy v1 (BCTTv1). RESULTS:The initial screening in the Google Play Store yielded 6018 apps, 4108 of which were not focused on physical activity and were not in German or English. The descriptions of 1216 apps were further screened for eligibility. Duplicate apps and light versions (n=694) and those with no objective measurement of physical activity, requiring additional equipment, or not outlining any physical activity guideline in their description (n=1184) were excluded. Of the remaining 32 apps, 4 were no longer available at the time of the download. Hence, 28 apps were downloaded and tested; of these apps, 14 did not contain any physical activity guideline as an app feature, despite mentioning it in the description, 5 had technical problems, and 3 did not provide objective physical activity measurement. Thus, 6 were included in the final analyses. Of 93 individual BCTs of the BCTTv1, on average, 9 (SD 5) were identified in these apps. Of 16 hierarchical clusters, on average, 5 (SD 3) were addressed. Only BCTs of the 2 hierarchical clusters "goals and planning" and "feedback and monitoring" were identified in all apps. CONCLUSIONS:Despite the availability of several thousand physical activity and fitness apps for Android platforms, very few addressed evidence-based physical activity guidelines and provided objective physical activity measurement. Furthermore, available descriptions did not accurately reflect the app content and only a few evidence-informed physical activity apps incorporated several BCTs. Future apps should address evidence-based physical activity guidelines and a greater scope of BCTs to further increase their potential impact for physical activity promotion.
| S-EPMC6315275 | biostudies-literature