statxact version 11 (Cytel Inc)
90
Structured Review
Cytel Inc
statxact version 11
Statxact Version 11, supplied by Cytel Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/statxact-11/statxact/pmc10657854-133-10-13
Average 90 stars, based on 1 article reviews
Statxact Version 11, supplied by Cytel Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/statxact-11/statxact/pmc10657854-133-10-13
Average 90 stars, based on 1 article reviews
statxact version 11 - by Bioz Stars,
2026-10
90/100 stars
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other:Article Title: Monte Carlo Simulations Comparing Fisher Exact Test and Unequal Variances t Test for Analysis of Differences Between Groups in Brief Hospital Lengths of Stay Article Snippet: December 2017 • Volume 125 • Number 6 www.anesthesia-analgesia.org 2141 DOI: 10.1213/ANE.0000000000002428 Hospital length of stay (LOS) is a common and suitable secondary, economic end point for Perioperative Surgical Home and Enhanced Recovery type interventions.1 LOS can be benchmarked using publically available national data.2 Each 1-day increase in hospital median LOS is associated with odds of readmission nationwide of 1.05 (P = .012) and odds of transfer to short-term care facility of 1.47 (P = .0008).3 LOS can be influenced by perioperative anesthesia care.4 The vast majority of anesthesiologists nationwide think that their clinical decisions influence LOS: 90% think “anesthesiologist intraoperative management should reduce overall LOS”; 81% think that “anesthesiologist coordination of all preoperative care should reduce overall LOS”; and 81% think “anesthesiologist coordination of all postoperative care should reduce overall LOS.”5 Surprisingly, there are limited data on appropriate inferential analyses for comparing brief hospital LOS between groups.. Intensive care unit LOS is often short (eg, overnight for many surgical patients).. From Moran and Solomon6 and Verburg et al’s7 analyses of intensive care unit LOS, treating LOS data as coming from a log-normal distribution can be appropriate. Article Title: Financial Incentives for Adherence to Hepatitis C Virus Clinical Care and Treatment: A Randomized Trial of Two Strategies Article Snippet: All statistical analyses were conducted in SAS version 9.4 (SAS Institute, Cary, NC) or Article Title: Dodecafluoropentane Emulsion in Acute Ischemic Stroke: A Phase Ib/II Randomized and Controlled Dose-Escalation Trial. Article Snippet: Purpose: This randomized, placebo-controlled, double-blind, dose-escalation acute ischemic stroke trial was designed to demonstrate maximum tolerated dose, characterize adverse events (AEs), and explore clinical outcomes when intravenous dodecafluoropentane emulsion (DDFPe) was used as neuroprotection.. Methods: Acute ischemic stroke patients (n 1⁄4 24) with National Institutes of Health Stroke Scale (NIHSS) score of 2–20 were randomized to either 3 doses of intravenous DDFPe or placebo, 1 every 90 minutes, starting within 12 hours of symptom onset.. Doses were given without affecting standard stroke care. Article Title: Database Quality and Access Issues Relevant to Research Using Anesthesia Information Management System Data Article Snippet: XXX 2018 • Volume XXX • Number XXX www.anesthesia-analgesia.org 1 DOI: 10.1213/ANE.0000000000003324 Anesthesia information management system (AIMS) data are entered as routine clinical documentation or acquired automatically from patient monitors and anesthesia machines.1,2 Secondary use of such data involves activities such as quality assurance, governmental reporting, clinical decision support, and research.3,4 Studies using AIMS data have provided valuable, pragmatic insights that could not have been realized practically within the constraints of traditional randomized clinical trials.5,6 In addition, retrospective data from large numbers of patients can easily be collected and analyzed.7 Such processes avoid the corresponding expense and logistical difficulties of enrolling patients in a prospective, observational study.8 Because AIMSs are ubiquitous in academic anesthesia departments,9 nearly all departments can be performing perioperative informatics research.. However, to our knowledge, few departments worldwide published >5 informatics papers involving AIMS data from 2006 through 2017 (eg, 4 departments in an annotated bibliography of such studies).10 In this special article, we reviewed the computer code used to extract the data and text for all 47 studies published between January 2006 and August 2017 using AIMS data from Thomas Jefferson University Hospital (TJUH).11–57 Our approach was deliberately not a systematic or narrative review but rather a quantitative, self-reflective study of our experiences at a single institution that was highly productive in the area of AIMS informatics.. Data from this institution were used in the largest number (26/90; P = .0007 versus the next largest group, 9/90) of papers describing the use of AIMS published in this time frame (ie, 26/90 in the bibliography; P = .0007).10 The objective of the current article was to identify factors that made TJUH successful in publishing anesthesia informatics studies so that others might learn from our experiences. Article Title: US critical access hospitals' listings of pain medicine physicians and other clinicians performing interventional pain procedures. Article Snippet: Study objective: There is little knowledge of rural hospitals' roles in the care of chronic pain patients nationwide in the United States of America.. We hypothesized that very few (≅5%) critical access hospitals provide patients with interventional pain procedures performed by pain medicine physicians.. Design: Random sample of the 1346 critical access hospitals in USA. |