Derivation and Validation of Risk Prediction Model for 30-Day Readmissions Following Transcatheter Mitral Valve Repair
01 Mar 2023-Current Problems in Cardiology (Current Problems in Cardiology)-Vol. 48, Iss: 3, pp 101033-101033
TL;DR: In this paper , the authors developed and validated a 30-day readmission risk calculator for transcatheter mitral valve repair (TMVr), which can guide in optimal discharge planning and reduce resource utilization.
About: This article is published in Current Problems in Cardiology.The article was published on 2023-03-01. It has received 1 citations till now. The article focuses on the topics: Medicine & Calculator.
TL;DR: In this article , the performance of machine learning algorithms vs. logistic regression in predicting readmissions after mitral valve transcatheter edge-to-edge repair (MV-TEER) is investigated.
University of California, Berkeley1, Stellenbosch University2, University of Jyväskylä3, University of Cambridge4, Google5, University of Toronto6, University of Birmingham7, Temple University8, Amazon.com9, University of British Columbia10, University of Georgia11, University of Oxford12, Los Alamos National Laboratory13, University of California, Irvine14
TL;DR: In this paper, the authors review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data, and their evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.
Abstract: Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis. NumPy is the primary array programming library for Python; here its fundamental concepts are reviewed and its evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.
Columbia University Medical Center1, Vanderbilt University2, Ohio State University3, Cedars-Sinai Medical Center4, University of Virginia5, Intermountain Medical Center6, Baylor University Medical Center7, Carolinas Medical Center8, Piedmont Hospital9, University of Colorado Hospital10, University of Missouri–Kansas City11, MedStar Health12, Scott & White Hospital13
TL;DR: Among patients with heart failure and moderate‐to‐severe or severe secondary mitral regurgitation who remained symptomatic despite the use of maximal doses of guideline‐directed medical therapy, transcatheter mitral‐valve repair resulted in a lower rate of hospitalization forHeart failure and lower all‐cause mortality within 24 months of follow‐up than medical therapy alone.
Abstract: Background Among patients with heart failure who have mitral regurgitation due to left ventricular dysfunction, the prognosis is poor Transcatheter mitral-valve repair may improve their clinical outcomes Methods At 78 sites in the United States and Canada, we enrolled patients with heart failure and moderate-to-severe or severe secondary mitral regurgitation who remained symptomatic despite the use of maximal doses of guideline-directed medical therapy Patients were randomly assigned to transcatheter mitral-valve repair plus medical therapy (device group) or medical therapy alone (control group) The primary effectiveness end point was all hospitalizations for heart failure within 24 months of follow-up The primary safety end point was freedom from device-related complications at 12 months; the rate for this end point was compared with a prespecified objective performance goal of 880% Results Of the 614 patients who were enrolled in the trial, 302 were assigned to the device group and 312 t
TL;DR: Most current readmission risk prediction models that were designed for either comparative or clinical purposes perform poorly and although in certain settings such models may prove useful, efforts to improve their performance are needed as use becomes more widespread.
Abstract: Context Predicting hospital readmission risk is of great interest to identify which patients would benefit most from care transition interventions, as well as to risk-adjust readmission rates for the purposes of hospital comparison. Objective To summarize validated readmission risk prediction models, describe their performance, and assess suitability for clinical or administrative use. Data Sources and Study Selection The databases of MEDLINE, CINAHL, and the Cochrane Library were searched from inception through March 2011, the EMBASE database was searched through August 2011, and hand searches were performed of the retrieved reference lists. Dual review was conducted to identify studies published in the English language of prediction models tested with medical patients in both derivation and validation cohorts. Data Extraction Data were extracted on the population, setting, sample size, follow-up interval, readmission rate, model discrimination and calibration, type of data used, and timing of data collection. Data Synthesis Of 7843 citations reviewed, 30 studies of 26 unique models met the inclusion criteria. The most common outcome used was 30-day readmission; only 1 model specifically addressed preventable readmissions. Fourteen models that relied on retrospective administrative data could be potentially used to risk-adjust readmission rates for hospital comparison; of these, 9 were tested in large US populations and had poor discriminative ability (c statistic range: 0.55-0.65). Seven models could potentially be used to identify high-risk patients for intervention early during a hospitalization (c statistic range: 0.56-0.72), and 5 could be used at hospital discharge (c statistic range: 0.68-0.83). Six studies compared different models in the same population and 2 of these found that functional and social variables improved model discrimination. Although most models incorporated variables for medical comorbidity and use of prior medical services, few examined variables associated with overall health and function, illness severity, or social determinants of health. Conclusions Most current readmission risk prediction models that were designed for either comparative or clinical purposes perform poorly. Although in certain settings such models may prove useful, efforts to improve their performance are needed as use becomes more widespread.
TL;DR: Although percutaneous repair was less effective at reducing mitral regurgitation than conventional surgery, the procedure was associated with superior safety and similar improvements in clinical outcomes.
Abstract: Background Mitral-valve repair can be accomplished with an investigational procedure that involves the percutaneous implantation of a clip that grasps and approximates the edges of the mitral leaflets at the origin of the regurgitant jet. Methods We randomly assigned 279 patients with moderately severe or severe (grade 3+ or 4+) mitral regurgitation in a 2:1 ratio to undergo either percutaneous repair or conventional surgery for repair or replacement of the mitral valve. The primary composite end point for efficacy was freedom from death, from surgery for mitral-valve dysfunction, and from grade 3+ or 4+ mitral regurgitation at 12 months. The primary safety end point was a composite of major adverse events within 30 days. Results At 12 months, the rates of the primary end point for efficacy were 55% in the percutaneous-repair group and 73% in the surgery group (P=0.007). The respective rates of the components of the primary end point were as follows: death, 6% in each group; surgery for mitral-valve dysfu...
TL;DR: Among patients with severe secondary mitral regurgitation, the rate of death or unplanned hospitalization for heart failure at 1 year did not differ significantly between patients who underwent percutaneous mitral‐valve repair in addition to receiving medical therapy and those who received medical therapy alone.
Abstract: Background In patients who have chronic heart failure with reduced left ventricular ejection fraction, severe secondary mitral-valve regurgitation is associated with a poor prognosis. Whether percutaneous mitral-valve repair improves clinical outcomes in this patient population is unknown. Methods We randomly assigned patients who had severe secondary mitral regurgitation (defined as an effective regurgitant orifice area of >20 mm2 or a regurgitant volume of >30 ml per beat), a left ventricular ejection fraction between 15 and 40%, and symptomatic heart failure, in a 1:1 ratio, to undergo percutaneous mitral-valve repair in addition to receiving medical therapy (intervention group; 152 patients) or to receive medical therapy alone (control group; 152 patients). The primary efficacy outcome was a composite of death from any cause or unplanned hospitalization for heart failure at 12 months. Results At 12 months, the rate of the primary outcome was 54.6% (83 of 152 patients) in the intervention grou...