Challenging management dogma where evidence is non-existent, weak or outdated

Medical practice is dogged by dogma. A conclusive evidence base is lacking for many aspects of patient management. Clinicians, therefore, rely upon engrained treatment strategies as the dogma seems to work, or at least is assumed to do so. Evidence is often distorted, overlooked or misapplied in the re-telling. However, it is incorporated as fact in textbooks, policies, guidelines and protocols with resource and medicolegal implications. We provide here four examples of medical dogma that underline the above points: loop diuretic treatment for acute heart failure; the effectiveness of heparin thromboprophylaxis; the rate of sodium correction for hyponatraemia; and the mantra of “each hour counts” for treating meningitis. It is notable that the underpinning evidence is largely unsupportive of these doctrines. We do not necessarily advocate change, but rather encourage critical reflection on current practices and the need for prospective studies

A Cheeger Inequality for the Graph Connection Laplacian

The O(d) Synchronization problem consists of estimating a set of unknown orthogonal transformations O_i from noisy measurements of a subset of the pairwise ratios O_iO_j^{-1}. We formulate and prove a Cheeger-type inequality that relates a measure of how well it is possible to solve the O(d) synchronization problem with the spectra of an operator, the graph Connection Laplacian. We also show how this inequality provides a worst case performance guarantee for a spectral method to solve this problem.Comment: To appear in the SIAM Journal on Matrix Analysis and Applications (SIMAX

The economic implications of HLA matching in cadaveric renal transplantation.

Abstract Background: The potential economic effects of the allocation of cadaveric kidneys on the basis of tissue-matching criteria are controversial. We analyzed the economic costs associated with the transplantation of cadaveric kidneys with various numbers of HLA mismatches and examined the potential economic benefits of a local, as compared with a national, system designed to minimize HLA mismatches between donor and recipient in first cadaveric renal transplantations. Methods: All data were supplied by the U.S. Renal Data System. Data on all payments made by Medicare from 1991 through 1997 for the care of recipients of a first cadaveric renal transplant were analyzed according to the number of HLA-A, B, and DR mismatches between donor and recipient and the duration of cold ischemia before transplantation. Results: Average Medicare payments for renal-transplant recipients in the three years after transplantation increased from $60,436 per patient for fully HLA-matched kidneys (those with no HLA-A, B, or DR mismatches) to$80,807 for kidneys with six HLA mismatches between donor and recipient, a difference of 34 percent (P\u3c0.001). By three years after transplantation, the average Medicare payments were $64,119 for transplantations of kidneys with less than 12 hours of cold-ischemia time and$74,997 for those with more than 36 hours (P\u3c0.001). In simulations, the assignment of cadaveric kidneys to recipients by a method that minimized HLA mismatching within a local geographic area (i.e., within one of the approximately 50 organ-procurement organizations, which cover widely varying geographic areas) produced the largest cost savings ($4,290 per patient over a period of three years) and the largest improvements in the graft-survival rate (2.3 percent) when the potential costs of longer cold-ischemia time were considered. Conclusions: Transplantation of better-matched cadaveric kidneys could have substantial economic advantages. In our simulations, HLA-based allocation of kidneys at the local level produced the largest estimated cost savings, when the duration of cold ischemia was taken into account. No additional savings were estimated to result from a national allocation program, because the additional costs of longer cold-ischemia time were greater than the advantages of optimizing HLA matching

Sustained water storage in Horn of Africa drylands dominated by seasonal rainfall extremes

Rural communities in the Horn of Africa Drylands (HAD) are increasingly vulnerable to multi-season droughts due to the strong dependence of livelihoods on seasonal rainfall. We analysed multiple observational rainfall datasets for recent decadal trends in mean and extreme seasonal rainfall, as well as satellite-derived terrestrial water storage and soil moisture trends arising from two key rainfall seasons across various subregions of HAD. We show that, despite decreases in total March-April-May rainfall, total water storage in the HAD has increased. This trend correlates strongly with seasonal totals and especially with extreme rainfall in the two dominant HAD rainy seasons between 2003 and 2016. We further show that high-intensity October-November-December rainfall associated with positive Indian Ocean Dipole events lead to the largest seasonal increases in water storage that persist over multiple years. These findings suggest that developing groundwater resources in HAD could offset or mitigate the impacts of increasingly common droughts

Prediction of Complications and Prognostication in Perioperative Medicine: A Systematic Review and PROBAST Assessment of Machine Learning Tools

Background: The utilization of artificial intelligence and machine learning as diagnostic and predictive tools in perioperative medicine holds great promise. Indeed, many studies have been performed in recent years to explore the potential. The purpose of this systematic review is to assess the current state of machine learning in perioperative medicine, its utility in prediction of complications and prognostication, and limitations related to bias and validation. Methods: A multidisciplinary team of clinicians and engineers conducted a systematic review using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocol. Multiple databases were searched, including Scopus, Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Cochrane Library, PubMed, Medline, Embase, and Web of Science. The systematic review focused on study design, type of machine learning model used, validation techniques applied, and reported model performance on prediction of complications and prognostication. This review further classified outcomes and machine learning applications using an ad hoc classification system. The Prediction model Risk Of Bias Assessment Tool (PROBAST) was used to assess risk of bias and applicability of the studies. Results: A total of 103 studies were identified. The models reported in the literature were primarily based on single-center validations (75%), with only 13% being externally validated across multiple centers. Most of the mortality models demonstrated a limited ability to discriminate and classify effectively. The PROBAST assessment indicated a high risk of systematic errors in predicted outcomes and artificial intelligence or machine learning applications. Conclusions: The findings indicate that the development of this field is still in its early stages. This systematic review indicates that application of machine learning in perioperative medicine is still at an early stage. While many studies suggest potential utility, several key challenges must be first overcome before their introduction into clinical practice

Altered Hyperlipidemia, Hepatic Steatosis, and Hepatic Peroxisome Proliferator-Activated Receptors in Rats with Intake of Tart Cherry

ABSTRACT Elevated plasma lipids, glucose, insulin, and fatty liver are among components of metabolic syndrome, a phenotypic pattern that typically precedes the development of Type 2 diabetes. Animal studies show that intake of anthocyanins reduces hyperlipidemia, obesity, and atherosclerosis and that anthocyanin-rich extracts may exert these effects in association with altered activity of tissue peroxisome proliferator-activated receptors (PPARs). However, studies are lacking to test this correlation using physiologically relevant, whole food sources of anthocyanins. Tart cherries are a rich source of anthocyanins, and whole cherry fruit intake may also affect hyperlipidemia and/or affect tissue PPARs. This hypothesis was tested in the Dahl Salt-Sensitive rat having insulin resistance and hyperlipidemia. For 90 days, Dahl rats were pair-fed AIN-76a-based diets supplemented with either 1% (wt:wt) freeze-dried whole tart cherry or with 0.85% additional carbohydrate to match macronutrient and calorie provision. After 90 days, the cherry-enriched diet was associated with reduced fasting blood glucose, hyperlipidemia, hyperinsulinemia, and reduced fatty liver. The cherry diet was also associated with significantly enhanced hepatic PPAR-α mRNA, enhanced hepatic PPAR-α target acyl-coenzyme A oxidase mRNA and activity, and increased plasma antioxidant capacity. In conclusion, physiologically relevant tart cherry consumption reduced several phenotypic risk factors that are associated with risk for metabolic syndrome and Type 2 diabetes. Tart cherries may represent a whole food research model of the health effects of anthocyanin-rich foods and may possess nutraceutical value against risk factors for metabolic syndrome and its clinical sequelae.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63187/1/jmf.2007.658.pd

Association Between Hypocholesterolemia and Mortality in Critically Ill Patients With Sepsis: A Systematic Review and Meta-Analysis

OBJECTIVE: To ascertain the association between cholesterol and triglyceride levels on ICU admission and mortality in patients with sepsis. DATA SOURCES: Systematic review and meta-analysis of published studies on PubMed and Embase. STUDY SELECTION: All observational studies reporting ICU admission cholesterol and triglyceride levels in critically ill patients with sepsis were included. Authors were contacted for further data. DATA EXTRACTION: Eighteen observational studies were identified, including 1,283 patients with a crude overall mortality of 33.3%. Data were assessed using Revman (Version 5.1, Cochrane Collaboration, Oxford, United Kingdom) and presented as mean difference (MD) with 95% CIs, p values, and I2 values. DATA SYNTHESIS: Admission levels of total cholesterol (17 studies, 1,204 patients; MD = 0.52 mmol/L [0.27–0.77 mmol/L]; p < 0.001; I2 = 91%), high-density lipoprotein (HDL)-cholesterol (14 studies, 991 patients; MD = 0.08 mmol/L [0.01–0.15 mmol/L]; p = 0.02; I2 = 61%), and low-density lipoprotein (LDL) cholesterol (15 studies, 1,017 patients; MD = 0.18 mmol/L [0.04–0.32 mmol/L]; p = 0.01; I2 = 71%) were significantly lower in eventual nonsurvivors compared with survivors. No association was seen between admission triglyceride levels and mortality (15 studies, 1,070 patients; MD = 0.00 mmol/L [–0.16 to 0.15 mmol/L]; p = –0.95; I2 = 79%). CONCLUSIONS: Mortality was associated with lower levels of total cholesterol, HDL-cholesterol, and LDL-cholesterol, but not triglyceride levels, in patients admitted to ICU with sepsis. The impact of cholesterol replacement on patient outcomes in sepsis, particularly in at-risk groups, merits investigation. KEYWORDS: cholesterol levels; intensive care unit; lipids; sepsis; triglyceride