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The same calculation can be done for people who are not exposed to the risk and who nevertheless get the outcome of interest purchase 60mg levitra extra dosage with amex. Their absolute risk is the ratio of those not exposed to the risk factor and who have the outcome of interest to all those not exposed to the risk factor cheap levitra extra dosage 60mg visa. They can help asso- ciate an etiology such as smoking to an outcome such as lung cancer purchase levitra extra dosage in india. Risk cal- culations can estimate the probability of developing an outcome such as the increased risk of endometrial cancer because of exposure to estrogen therapy cheap 40mg levitra extra dosage free shipping. They can demonstrate the effectiveness of an intervention on an outcome such as showing a decreased mortality from measles in children who have been vac- cinated against the disease. For example, they can measure the effect of aspirin as opposed to stronger blood thinners like heparin or low-molecular-weight hep- arin on mortality from heart attacks. These studies can separate groups by the exposure and then measure the risk of the outcome. They can also be set up so that the exposure precedes the out- come, thus showing a cause and effect relationship. The measure of risk calcu- lated from these studies is called the relative risk, which will be deﬁned shortly. Relative risk can also be measured from a cross-sectional study, but the cause and effect cannot be shown from that study design. Less reliable estimates of risk may still be useful and can come from case–control studies, which start with the assumption that there are equal numbers of subjects with and without the outcome of interest. The estimates of risk from these studies approximate the relative risk calculated from cohort studies using a calculation known as an odds ratio, which will also be deﬁned shortly. There are several measures associated with any clinical or epidemiological study of risk. The study design determines which way the data are gathered and this determines the type of risk measures that can be calculated from a given Risk assessment 143 Fig. Absolute risk Absolute risk is the probability of the outcome of interest in those exposed or not exposed to the risk factor. It compares those with the outcome of interest and the risk factor (a) to all subjects in the population exposed to the risk factor (a + b). In probabilistic terms, it is the probability of the outcome if exposed to the risk factor, also written as P outcome | risk = P (O+ |R+). One can also do this for patients with the outcome of interest who are not exposed to the risk fac- tor (c) and compare them to all of those who are not exposed to the risk factor [c/(c + d)]. Absolute risk only gives information about the risk of one group, either those exposed to the risk factor or those not exposed to the risk factor. It can only be calculated from cross-sectional studies, cohort studies, or randomized clinical trials, because in these study designs, you can calculate the incidence of a par- ticular outcome for those exposed or not exposed to the risk factor. One must know the relative proportions of the factors in the total population in order to calculate this number, as demonstrated in the rows of the 2 × 2 table in Fig. The absolute risk is the probability that someone with the risk factor has the outcome of interest. The ratio a/(a + b) is the probability that one will have the outcome if exposed to the risk factor. The same can be done for the row of patients who were not exposed to the risk factor. These absolute risks are the same as the incidence of disease in the cohort being studied. This is the absolute risk of the outcome in subjects exposed to the risk factor divided by the absolute risk of the outcome in subjects not exposed to the risk factor. In other words, it is the ratio of the probability of the outcome if exposed to the probability of the out- come if not exposed. Relative risk can only be calculated from cross-sectional studies, cohort studies or randomized clinical trials. The larger or smaller the relative risk, the stronger the association between the risk factor and the outcome. If it is 1, there is no change in risk from the baseline risk level and it is said that the risk factor has no effect on the outcome. Values below this could have been obtained because of systematic ﬂaws in the study. This is especially true for observational studies like cross-sectional and cohort studies where there may be many confounding variables that could be responsible for the results. A high relative risk does not prove that the risk factor is responsible for out- come: it merely quantiﬁes the strength of association of the two. It is always pos- sible that a third unrecognized factor, a surrogate or confounding variable, is the cause of the association because it equally affects both the risk factor and the outcome. Data collected for relative-risk calculations come from cross-sectional stud- ies, cohort studies, non-concurrent cohort studies, and randomized clinical trials. These studies are used because they are the only ones capable of cal- culating incidence. Importantly, cohort studies should demonstrate complete follow-up of all study subjects, as a large drop-out rate may lead to invalid results. The researchers should allow for an adequate length of follow-up in order to ensure that all possible outcome events have occurred. This could be years or even decades for cancer while it is usually weeks or days for certain infec- tious diseases. This follow-up cannot be done in cross-sectional studies, which can only show the strength of association but not that the cause preceded the effect. Odds ratio An odds ratio is the calculation used to estimate the relative risk or the associa- tion of risk and outcome for case–control studies. In case–control studies, sub- jects are selected based upon the presence or absence of the outcome of interest. This study design is used when the outcome is relatively rare in the population and calculating relative risk would require a cohort study with a huge number of subjects in order to ﬁnd enough patients with the outcome. In case–control stud- ies, the number of subjects selected with and without the outcome of interest are independent of the true ratio of these in the population. Therefore the incidence, the rate of occurrence of new cases of each outcome associated with and without 146 Essential Evidence-Based Medicine Odds of having risk factor if outcome is present = a/c Odds of having risk factor if outcome is not present = b/d Case−control study Disease Disease Direction of sampling present (D+) absent (D−) Odds ratio = (a/c)/(b/d) = ad/bc. Risk present (R+) a b a + b Risk absent (R−) c d c + d This is also called the “cross product”. Odds tell someone the number of times an event will happen divided by the number of times it won’t happen. Although they are different ways of expressing the same number, odds and probability are mathematically related. In case–control stud- ies, one measures the individual odds of exposure in subjects with the outcome as the ratio of subjects with and without the risk factor among all subjects with that outcome. The same odds can be calculated for exposure to the risk factor among those without the outcome. The odds ratio compares the odds of having the risk factor present in the sub- jects with and without the outcome under study. This is the odds of having the risk factor if a person has the outcome divided by the odds of having the risk fac- tor if a person does not have the outcome. Using the odds ratio to estimate the relative risk The odds ratio best estimates the relative risk when the disease is very rare. Cohort-study patients are evaluated on the basis of exposure and then outcome is determined. Therefore, one can calculate the absolute risk or the incidence of disease if the patient is or is not exposed to the risk factor and subsequently the relative risk can be calculated. Case–control study patients are evaluated on the basis of outcome and expo- sure is then determined. The true ratio of patients with and without the outcome in the general population cannot be known from the study, but is an arbitrary ratio set by the researcher. One can only look at the ratio of the odds of risk in the diseased and non-diseased groups, hence the odds ratio. Hulley study, we are looking at the disease as if it were present in a preset ratio, usually & S.
His nonfnancial dis- closures include authorship of the position statement on fuid resuscitation Dr generic 40mg levitra extra dosage. Vincent reports consulting income paid to his institution from Astellas order levitra extra dosage 40 mg mastercard, Associates (soluble guanylate cyclase activator in acute respiratory distress AstraZeneca levitra extra dosage 40 mg without prescription, Curacyte 60mg levitra extra dosage with mastercard, Eli Lilly, Eisai, Ferring, GlaxoSmithKline, Merck, and syndrome/acute lung injury adjunct therapy to supportive care and ventila- Pfzer. His institution received honoraria on his behalf from Astellas, Astra- tion strategies), Eisai (eritoran), and Phillips (Respironics); he provided expert Zeneca, Curacyte, Eli Lilly, Eisai, Ferring, Merck, and Pfzer. He is the author Hearing), Eisai (eritoran through leader touch plan in Brussels), Eli Lilly of several manuscripts defning sepsis and stratifcation of the patient with (Lunchtime Symposium, Vienna), Covidien (adult monitoring advisory board sepsis. Severe sepsis and septic shock are major health- Severe sepsis is defned as sepsis plus sepsis-induced organ care problems, affecting millions of people around the world dysfunction or tissue hypoperfusion (Tables 1 and 2) (6). Similar to polytrauma, acute myocardial ment bundles, which are included, a distinction is made infarction, or stroke, the speed and appropriateness of therapy between defnitions and therapeutic targets or thresholds. Sep- administered in the initial hours after severe sepsis develops sis-induced hypotension is defned as a systolic blood pressure are likely to infuence outcome. Recommendations from these deviations below normal for age in the absence of other causes guidelines cannot replace the clinician’s decision-making capa- of hypotension. An example of a therapeutic target or typical bility when he or she is presented with a patient’s unique set of threshold for the reversal of hypotension is seen in the sepsis clinical variables. In fact, the committee believes that the greatest outcome be evident throughout this article. Septic shock is defned as improvement can be made through education and process sepsis-induced hypotension persisting despite adequate fuid change for those caring for severe sepsis patients in the non- resuscitation. The 2008 publication analyzed evidence available and feedback performance improvement initiatives, the guide- through the end of 2007. The most current iteration is based lines will infuence bedside healthcare practitioner behavior on updated literature search incorporated into the evolving that will reduce the burden of sepsis worldwide. This system classifes mation incorporated into the evolving manuscript through quality of evidence as high (grade A), moderate (grade B), low year-end 2011 and early 2012). Committees and the results, indirectness of the evidence, and possible reporting their subgroups continued work via phone and the Internet. Examples of indirectness of the evidence Several subsequent meetings of subgroups and key indi- include population studied, interventions used, outcomes viduals occurred at major international meetings (nominal measured, and how these relate to the question of interest. An example of this is heads, executive committee members, and other key commit- the quality of evidence for early administration of antibiotics. The assignment of strong heads to identify pertinent search terms that were to include, or weak is considered of greater clinical importance than a at a minimum, sepsis, severe sepsis, septic shock, and sepsis syn- difference in letter level of quality of evidence. The commit- drome crossed against the subgroup’s general topic area, as well tee assessed whether the desirable effects of adherence would as appropriate key words of the specifc question posed. All outweigh the undesirable effects, and the strength of a rec- questions used in the previous guidelines publications were ommendation refects the group’s degree of confdence in searched, as were pertinent new questions generated by gen- that assessment. Thus, a strong recommendation in favor of eral topic-related searches or recent trials. A weak recommendation in favor of an intervention Clinical Trials, International Standard Randomized Controlled indicates the judgment that the desirable effects of adherence Trial Registry [http://www. Where appropriate, available evidence was either because some of the evidence is low quality (and thus summarized in the form of evidence tables. Diagnostic Criteria for Sepsis Infection, documented or suspected, and some of the following: General variables Fever (> 38. Diagnostic criteria for sepsis in the pediatric population are signs and symptoms of infammation plus infection with hyper- or hypothermia (rectal temperature > 38. A strong recom- The implications of calling a recommendation strong mendation is worded as “we recommend” and a weak recom- are that most well-informed patients would accept that mendation as “we suggest. Severe Sepsis Severe sepsis defnition = sepsis-induced tissue hypoperfusion or organ dysfunction (any of the following thought to be due to the infection) Sepsis-induced hypotension Lactate above upper limits laboratory normal Urine output < 0. Indirectness of evidence (differing population, intervention, control, outcomes, comparison) 4. High likelihood of reporting bias Main factors that may increase the strength of evidence 1. Large magnitude of effect (direct evidence, relative risk > 2 with no plausible confounders) 2. Very large magnitude of effect with relative risk > 5 and no threats to validity (by two levels) 3. Weak Recommendation What Should be Considered Recommended Process High or moderate evidence The higher the quality of evidence, the more likely a strong recommendation. The larger the difference between the desirable and undesirable consequences and harms and burdens (Is there certainty? The smaller the net beneft and the lower the certainty for that beneft, the more likely a weak recommendation. Certainty in or similar values The more certainty or similarity in values and preferences, the more likely a strong (Is there certainty or similarity? Resource implications The lower the cost of an intervention compared to the alternative and other costs related to (Are resources worth expected benefts? Initial Resuscitation and Infection Issues (Table 5) Confict of Interest Policy A. We recommend the protocolized, quantitative resuscitation of of the committee represented industry; there was no industry patients with sepsis- induced tissue hypoperfusion (defned in input into guidelines development; and no industry represen- this document as hypotension persisting after initial fuid chal- tatives were present at any of the meetings. Full mixed venous oxygen saturation (SvO2) 70% or 65%, disclosure and transparency of all committee members’ poten- respectively. In a randomized, controlled, single-center study, not relevant to the guidelines content process. Nine were judged as having conficts This strategy, termed early goal-directed therapy, was evalu- that could not be resolved solely by reassignment. One of ated in a multicenter trial of 314 patients with severe sepsis in these individuals was asked to step down from the commit- eight Chinese centers (14). The other eight were assigned to the groups in which reduction in 28-day mortality (survival rates, 75. A large number of other observational studies using generally can be relied upon as supporting positive response to similar forms of early quantitative resuscitation in comparable fuid loading. Either intermittent or continuous measurements patient populations have shown signifcant mortality reduction of oxygen saturation were judged to be acceptable. During compared to the institutions’ historical controls (Supplemental the frst 6 hrs of resuscitation, if ScvO2 less than 70% or SvO2 Digital Content 2, http://links. As part of performance improvement programs, attempts to achieve the ScvO2 or SvO2 goal are options. Protocolized, quantitative resuscitation of patients with sepsis- induced tissue hypoperfusion (defned in this document as hypotension persisting after initial fuid challenge or blood lactate concentration ≥ 4 mmol/L). In patients with elevated lactate levels targeting resuscitation to normalize lactate (grade 2C). Routine screening of potentially infected seriously ill patients for severe sepsis to allow earlier implementation of therapy (grade 1C). Cultures as clinically appropriate before antimicrobial therapy if no signifcant delay (> 45 mins) in the start of antimicrobial(s) (grade 1C). At least 2 sets of blood cultures (both aerobic and anaerobic bottles) be obtained before antimicrobial therapy with at least 1 drawn percutaneously and 1 drawn through each vascular access device, unless the device was recently (<48 hrs) inserted (grade 1C). Use of the 1,3 beta-D-glucan assay (grade 2B), mannan and anti-mannan antibody assays (2C), if available and invasive candidiasis is in differential diagnosis of cause of infection. Administration of effective intravenous antimicrobials within the frst hour of recognition of septic shock (grade 1B) and severe sepsis without septic shock (grade 1C) as the goal of therapy. Initial empiric anti-infective therapy of one or more drugs that have activity against all likely pathogens (bacterial and/or fungal or viral) and that penetrate in adequate concentrations into tissues presumed to be the source of sepsis (grade 1B). Antimicrobial regimen should be reassessed daily for potential deescalation (grade 1B). Use of low procalcitonin levels or similar biomarkers to assist the clinician in the discontinuation of empiric antibiotics in patients who initially appeared septic, but have no subsequent evidence of infection (grade 2C). Combination empirical therapy for neutropenic patients with severe sepsis (grade 2B) and for patients with diffcult-to-treat, multidrug- resistant bacterial pathogens such as Acinetobacter and Pseudomonas spp.
Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www proven 60 mg levitra extra dosage. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www 60 mg levitra extra dosage otc. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www cheap 60 mg levitra extra dosage overnight delivery. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www purchase 60mg levitra extra dosage with amex. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. See also At-risk populations; specifc Gynecologists, 84, 97 populations Copyright © National Academy of Sciences. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. See also of chronic hepatitis Foreign-born access to care, 56, 169 educational programs for, 87, 92, 93, B 153, 183 Baltimore, 28, 92, 122-123, 190 health-care providers, 82 Blacks. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. See also Partner services Central nervous system demyelinating education of, 97, 98 disorders, 32 vaccination, 54, 57-58, 62, 93, 117, Chicago, 28, 116, 121 119-120 Childhood Immunization Initiative, 126 Correctional facilities. See also Liver cancer and discrimination liver cirrhosis age at exposure and, 19, 22, 46, 51, 82- Drug treatment programs and facilities. See also Illicit-drug users 83, 113, 117, 118, 156 knowledge of, 80, 83, 89 educational programs on viral hepatitis, 8, 88-89, 95-96, 100, 176 Copyright © National Academy of Sciences. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. See Illicit-drug users Infectious Diseases program, 59 Exposure routes knowledge and awareness, 95 E sexual, 1, 23, 44, 72, 84, 119-120 unsafe vaccine injections, 24 Economic issues. See also Funding; Insurance coverage screening and testing, 27, 161-162, 163 F vaccination, 54, 57-58, 117-119, 124, 137-138 Federal Employees Health Benefts Program, Educational programs. See also Knowledge 5, 13, 130, 148, 172 and awareness of chronic hepatitis Florida Hepatitis Prevention Program, advocacy efforts, 153-154 186-187 for alternative-medicine professionals, Food and Drug Administration, 109 86, 87, 89 Foreign-born populations. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. See also Vaccination for also Liver cancer and liver cirrhosis Hepatitis B; specifc populations and public vaccine programs and insurance, services 128-132 acute infection, 1, 19, 23, 27, 34, 48, racial/ethnic differences, 27, 29 50, 59, 70-71, 99, 117, 118, 119, reactivation, 162 120, 121, 125, 161, 189 registries of immunization, 126-127 adults, 27, 47, 117-125, 132 risk factors, 27 at-risk populations, 1-2, 21-22, 27, 81- screening and testing, 5, 8, 13, 14, 23, 82, 120-125 27, 47, 48-49, 51, 81, 82-83, 86, 90, case defnition, 48, 50, 51, 52 91, 124-125, 152, 156-157, 160-162 causative agent, 19, 21 stigma/discrimination, 23, 91-92 children, 23, 25, 30, 47, 116-117, surveillance, 44, 46, 47, 48, 50, 51, 52, 128-132 59-60, 61, 64, 71 Copyright © National Academy of Sciences. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. See Liver cancer referral for medical management, 148 and liver cirrhosis screening, testing, and counseling, 14, High-risk populations. See At-risk 62, 83, 85, 86, 94, 148, 156-157, populations Hispanics, 2, 10, 27, 30, 93, 116, 121, 159, 158, 162, 163, 179 stigmatization and discrimination, 24, 168-169, 184-185 85 Copyright © National Academy of Sciences. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. See also Foreign-born Insurance coverage populations gaps and barriers, 11, 134-135, 170 Immunization. See also Educational surveillance, 62 programs vaccination, 121-124, 157, 185 age and, 93 viral health services, 6, 16, 149, 184-186 asymptomatic infected individuals, 1, 3, Incidence of hepatitis. See Prevalence and 24, 26, 27, 50, 51, 90 incidence of hepatitis at-risk populations, 3, 4, 8, 9, 13, 34, Infants. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. See Viral hepatitis services applications of data from, 41, 42, 43-46 Sexual exposure to hepatitis, 1, 23, 44, 72, at-risk populations, 2, 4, 6, 7, 32, 61-62, 84, 113, 119-120 67, 68, 71-72 Copyright © National Academy of Sciences. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C http://www. Request reprint permission for this book Copyright © National Academy of Sciences. The members of the Committee responsible for the report were chosen for their special competences and with regard for appropriate balance. N01-0D-4-2139 between the National Academy of Sciences and the National Institutes of Health. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the organizations or agencies that provided support for the project. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease The National Academy of Sciences is a private, nonprofit, self-perpetuating society of distinguished scholars engaged in scientific and engineering research, dedicated to the furtherance of science and technology and to their use for the general welfare. Upon the authority of the charter granted to it by the Congress in 1863, the Academy has a mandate that requires it to advise the federal government on scientific and technical matters. The National Academy of Engineering was established in 1964, under the charter of the National Academy of Sciences, as a parallel organization of outstanding engineers. It is autonomous in its administration and in the selection of its members, sharing with the National Academy of Sciences the responsibility for advising the federal government. The National Academy of Engineering also sponsors engineering programs aimed at meeting national needs, encourages education and research, and recognizes the superior achievements of engineers. The Institute of Medicine was established in 1970 by the National Academy of Sciences to secure the services of eminent members of appropriate professions in the examination of policy matters pertaining to the health of the public. The Institute acts under the responsibility given to the National Academy of Sciences by its congressional charter to be an adviser to the federal government and, upon its own initiative, to identify issues of medical care, research, and education. The National Research Council was organized by the National Academy of Sciences in 1916 to associate the broad community of science and technology with the Academy’s purposes of furthering knowledge and advising the federal government. Functioning in accordance with general policies determined by the Academy, the Council has become the principal operating agency of both the National Academy of Sciences and the National Academy of Engineering in providing services to the government, the public, and the scientific and engineering communities. The Council is administered jointly by both Academies and the Institute of Medicine. The purpose of this independent review is to provide candid and critical comments that will assist the institution in making its published report as sound as possible and to ensure that the report meets institutional standards of objectivity, evidence, and responsiveness to the study charge. The review comments and draft manuscript remain confidential to protect the integrity of the deliberative process. We thank the following individuals for their review of this report: x Leslie Biesecker, National Institutes of Health x Martin J. Blaser, New York University Langone Medical Center x Wylie Burke, University of Washington x Christopher G. Chute, University of Minnesota and Mayo Clinic x Sean Eddy, Howard Hughes Medical Institute Janelia Farm Research x Elaine Jaffe, National Cancer Institute x Brian J. Schwartz, University of Washington Although the reviewers listed above have provided many constructive comments and suggestions, they were not asked to endorse the conclusions or recommendations, nor did they see the final draft of the report before its release. The review of the report was overseen by Dennis Ausiello, Harvard Medical School, Massachusetts General Hospital and Partners Healthcare and Queta Bond, Burroughs Welcome Fund. Appointed by the National Research Council, they were responsible for making certain that an independent examination of this report was carried out in accordance with institutional procedures and that all review comments were carefully considered. Responsibility for the final content of the report rests entirely with the authoring committee and the institution. We are grateful to those who attended and participated in the workshop “Toward a New st nd Taxonomy of Disease,” held March 1 and 2 , 2011 (Appendix D) and those who discussed data sharing with the Committee during the course of this study. Kelly, Head of Informatics and Strategic Alignment, Aetna x Debra Lappin, President, Council for American Medical Innovation x Jason Lieb, Professor, Department of Biology, University of North Carolina at Chapel Hill x Klaus Lindpaintner, Vice President of R&D, Strategic Diagnostics Inc. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease Summary The Committee’s charge was to explore the feasibility and need for “a New Taxonomy of human disease based on molecular biology” and to develop a potential framework for creating one. Clearly, the motivation for this study is the explosion of molecular data on humans, particularly those associated with individual patients, and the sense that there are large, as-yet- untapped opportunities to use these data to improve health outcomes. The Committee agreed with this perspective and, indeed, came to see the challenge of developing a New Taxonomy of Disease as just one element, albeit an important one, in a truly historic set of health-related challenges and opportunities associated with the rise of data-intensive biology and rapidly expanding knowledge of the mechanisms of fundamental biological processes.
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