The medical literature

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Chapter 9 The medical literature

This chapter is presented in three parts:

This chapter may be utilised in several ways. Those trainees commencing their approach to the fellowship exam, who have the time and motivation to use EBM techniques as a cornerstone of their preparation, may find this a useful summary of what is most relevant to have in their ‘tool kit’. Alternatively, those closer to the event may choose to focus their efforts on using the material as a review of information that could be asked in the exam — EBM would lend itself well to being an SAQ or SCE topic. The important papers section has relevance to all parts of the exam for trainees at all stages of their preparation.

Part A: the emergency physician’s guide to basic statistics

Consider the following:

If, like most clinicians, reading this question makes your eyes glaze over and your head ache, this section is for you. We will work our way through the answer step-bystep and by the end of this section, your headache will be gone!

First, consider the possible results of a test (positive or negative) when a disease (or disorder) is present or absent. The possible combinations are shown below.

For ease of calculations, we will assume a population size of 10,000. Prevalence is the number of people in the population with the condition at a given time. So a prevalence of 1% in our population of 10,000 will therefore equal 100 people with the disease. Prevalence should not be confused with incidence, which is the number of presentations per unit of time. For example, the annual incidence of diabetes is the number being diagnosed each year, whereas the prevalence (the number of people who have diabetes) is much higher.

Sensitivity is the capacity to detect something when it is present — just like a sensitive person does. In statistical terms it is best thought of as ‘positivity in the presence of disease’ = TP/(TP + FN). Tests with high sensitivity are preferable if the desire is to ensure that a condition is detected or ‘ruled in’. For our case, a sensitivity of 99% will result in a total of 99 out of the 100 patients with the disease returning a (true) positive test and one returning a (false) negative test.

Specificity is the ability of a test to pick only the disease — just as being specific means not getting off the point. In statistical terms, specificity can be thought of as ‘negativity in the absence of disease’ = TN/(TN + FP). Tests with high specificity are preferable when it is important to ensure that a condition is not present, i.e. ‘ruled out’. For our example, a specificity of 99% will result in 99 (1%) of the 9,900 without the disease still returning a (false) positive test.

The table can now be completed with simple arithmetic.

So far, we have been working backwards from a given population with a known disease prevalence to calculate true and false negatives and positives. However, this is not the world of a clinician with a test result. The result returned will be either positive or negative (at least for the sake of this discussion). The question that the clinician must ask is: ‘What does a positive (or negative) test mean?’

Positive predictive value (PPV) and negative pre dictive value (NPV) are the likelihood that a positive (or negative) test is a true result, i.e. what pro portion of positive results are true positives and what proportion of negative results are true negatives.

This is of direct importance to you as the clinician, as it tells you whether or not you can rely on the result you have. Depending on whether the test was intended to ‘rule in’ or ‘rule out’ a particular condi tion, the focus will be more on the PPV or the NPV, respectively.

The final basic statistical value we can also now cal culate is accuracy. Accuracy is the proportion of time the test is correct (TP or TN) for the given population.

Accuracy = (TP + TN)/(TP + TN + FP + FN)

This now enables us to answer the original question. A test with a 99% sensitivity and specificity when applied to a population with a disease prevalence of 1% will have a positive predictive value of only 50%.

From this you should now be able to appreciate that prevalence of disease has a significant impact on the clinical interpretation of a test in addition to simply evaluating the sensitivity and specificity. A practical example of this is assigning pre-test prob abilities to ventilation/perfusion scanning for suspected pulmonary embolism. Assigning a pre-test probability defines the prevalence of disease and hence alters the interpretation of the test result, even though the same test has been performed!

Below is the original question with a prevalence of 10%.

Note, the PPV has now increased dramatically. If your confidence in basic statistics has now grown (and your headache has gone), try different combinations and permutations of parameters to confirm the effect on PPV and NPV. To start with, review a paper or even work through the detail for an investigation you perform on a regular basis. You may never view basic statistics with fear again!

Part B: an overview of EBM

The context

This excerpt from an editorial by Davidoff et al. in the BMJ in 1995 still holds true today. EBM comprises the latest information on the most effective or least harmful management for patients (Davidoff et al., 1995). The key processes in EBM are:

Critical appraisal is ‘the process of systematically examining research evidence to assess its validity, results and relevance before using it to inform a decision’ (Mark, 2008). It allows the reader to assess in a systematic way how strong or weak a paper is in answering a clinically relevant question or whether the paper can be relied on as the basis for making clinical decisions for patients.

Deficits in knowledge and understanding of the critical appraisal process restrict the implementation of the best available evidence into clinical practice. Recog nising the need to understand evidence regard ing treatment or diagnostic options for conten tious issues is the first step in the journey. This requires an acknowledgment of equipoise (one is not sure which is the better treatment or test). The clinician may then wish to explore the quality of evidence underpinning a proven treatment or test, even if they are aware of these.

Carefully formulating a precise, answerable question that is clinically relevant (i.e. that will provide improved care or a better diagnostic test) is the starting point (why). Without knowing the why, there is no point in starting the appraisal journey. The next step is to decide where to look for the evidence. Literature searches need to be efficient, comprehensive, unrestricted and unbiased, encompassing explicit search strategies of published, citable literature databases and sources of unpublished research. How to identify good-quality studies, critically appraise those selected and apply their findings to individual patient care completes the appraisal journey.

Most readers will not limit their literature search in terms of date of publication (when) unless they are confident that a treatment or test was developed only recently, or an unlimited search yields numerous citations, which become unmanageable. As there is often a time lag between study citations being added to searchable databases, it is worthwhile considering conducting a more recent targeted search in relevant journals if the topic area is rapidly evolving. Wang and Bakhai (2006) and Pocock (1983) provide excellent further reading in the area of clinical trials, as do Greenhalgh’s ‘Education and debate’ series from the BMJ (Greenhalgh, 1997a) and Gordon Guyatt’s 2000 focus series from the JAMA (Guyatt, 2000).

Before looking for individual studies, we recom mend a concerted search for metaanalyses, which offer a useful background perspective and, if one is lucky, may even answer the research question, using the summated ‘quality overall evidence’ available so far (Mark, 2008). Meta-analyses are formally designed and properly conducted critical appraisals of intervention trials that attempt to ‘aggregate’ outcome findings from individual studies if they show a consistent effect. The presence of compelling outcome effects, consistent in direction and size across individual non-clinically heterogeneous studies of acceptable methodological quality, will likely be enough to tell you whether a proposed treatment or diagnostic test will be suited to your patient.

Critics claim that such aggregated findings cannot be applied to an individual patient; on average, the treatment effect will be qualitatively similar (if it benefits meta-analysis patients, treatment would probably be effective in your patient) but quantitatively more variable (the magnitude of benefit will vary between patients). The conclusion reached by a meta-analysis will be applicable to your patient and specific clinical setting if these characteristics are comparable to those of the study patients or study settings included in the meta-analysis.

Critically appraising a meta-analysis will still save you time and effort if many intervention trials or studies of diagnostic performance of a certain test relevant to your objective have been carried out. You need to ascertain whether the methodological rigour and quality of the meta-analysis is sufficient for conclusions and recommendations contained in the meta-analysis to reliably fulfil your objectives. If a well-conducted and reported meta-analysis is available, re-examining individual studies in detail is less worthwhile, other than for personal interest. However, a meta-analysis will not include influential studies that become available after the date of publication of the metaanalysis. Carrying out a date-of-publication limited search for newly emerging studies is thus recommended, to see whether the conclusions reached in the meta-analysis remain consistent with the newer studies. For in-depth information on systematic reviews in health care, see the standard text by Matthias Egger et al. (2001).

There may be no relevant meta-analysis to inform your objectives. If there are too few studies, or the studies are relatively small, excessively clinically heterogeneous or dissimilar, or they show inconsistent and widely varying outcomes, an aggregated outcome in a meta-analysis may not be possible. In these situations, decisions regarding patient management or investigation are based on a critical appraisal of individual studies you believe to be relevant to your practice setting, with the clinical risk–benefit analysis tailored to suit the individual needs of your patient, as well as taking into account treatment feasibility, practicability and availability.

Critical appraisal and clinical practice

Standards of clinical care now demand identification and timely delivery of the most effective treatment available in order to achieve optimal outcomes. There are high expectations among colleagues, patients and health administrators that treatments are clinically effective, cost-effective and timely with minimal adverse effects. In emergency medicine this may also involve the further consideration of time-critical situations. Treatment selection by anecdote, eminence or prior personal experience is no longer acceptable. Emergency physicians must make active, informed decisions regarding treatment selection and not simply default to in-patient teams.

In emergency medicine, critical appraisal of the evidence is most pertinent to time-critical conditions that require non-established or contentious urgent treatments that may be highly beneficial but also lead to significant harm. For example, this situation arises in thrombolytic treatment for acute ischaemic stroke, where treatment administered within three hours of symptom onset gives better neurofunctional outcome, but remains little used for fear of causing intracranial bleeding. ECASS III, a recently published RCT comparing IV alteplase with a placebo in ischaemic stroke, found alteplase to remain beneficial at three to four and a half hours after symptom onset (Hacke et al., 2008). The most recent Cochrane meta-analysis of thrombolysis trials in stroke, published in 2003, did not include ECASS III (Wardlaw et al., 2003). Evidence is in a constant state of evolution, so critical appraisal is a continuing process that aligns itself with continuing medical education and professional development. Nowadays, studies informing on therapeutic (in) effectiveness are easily and rapidly accessible through user-friendly information technology media such as the 24-hour medical cybrary. With the exception of acute resuscitation, there is never an excuse not to evaluate effectiveness prior to patient treatment.

High-standard clinical care requires the clinician to correctly select and safely deliver the best available treatment or diagnostic test for each patient in a timely fashion. A poor outcome for a patient receiving the most effective available treatment or a consequential diagnosis missed despite use of the most reliable test is ethically and medico-legally more defensible than the same adverse events in a patient after suboptimal treatment or not receiving an appropriate diagnostic test. The clinician who knows that a poor patient outcome has not resulted in some way from a knowledge gap will sleep the better for it.

Within the realm of clinical research, an unbiased comprehensive literature search is able to identify whether a research question has been answered in previous studies, and therefore whether another study is necessary or even ethical in the presence of compelling evidence. The potential impact on improving patient care and clinical relevance of a proposed study is also assessable by critical examination of the available literature. Furthermore, peer review of medical research manuscripts requires critical appraisal of a study’s internal validity as it relates to methodological rigour and its capability to be generalised to various clinical settings.

Barriers and challenges remain in keeping up to date with the latest evidence. The time pressures of increasing demand for hands-on patient care discourage evidence appraisal. This is exacerbated by perceptions that clinical care is distant and divorced from medical research, engendering the negative connotation that critical appraisal by the ‘thinker’ clinician is a diversionary activity of little relevance to direct patient care rendered by the ‘doers’. Negative perceptions exist that medical research has become an industry with little relevance to clinical practice.

Exponential growth in the medical literature and the increasing ease of access to biomedical journals has produced a ‘noise to signal ratio’ that can easily overwhelm the time-pressured clinician. Successfully identifying, or conversely not missing, crucial studies can be a challenge. The following sections provide a framework to help with this important task.

Levels of evidence

Intervention and non-intervention studies can be stratified into several ‘levels of evidence’, according to their internal validity and dependability in informing treatment effects. A well-designed and conducted meta-analysis or randomised controlled blinded treatment trial is widely recognised as being able to offer the most reliable and least biased estimate of treatment benefit or harm (Wang et al., 2006), followed in descending order of quality of evidence by observational non-intervention studies such as case control studies and finally case series and case reports. This is variously graded (e.g. levels I–IV or grade A–C recommendations) depending on the body utilising this. Several issues should be apparent at this stage:

ACEM recognises the importance of EBM and research as being crucial for the future of the specialty. It is expected that fellowship exam candidates will be aware of major practice informing papers. The purpose of regulation 4.10 is to ensure that all trainees have exposure to research during their training. This is important so that individuals with a predilection for research can self-select and be supported in their future development.

For the working trainee who is approaching the exam, acquiring and applying EBM skills to each topic on the fellowship curriculum can be daunting. Some would say that this is unrealistic, when so many other priorities exist and time is short. Textbooks and exam-focused resources that have incorporated relatively recent clinical evidence provide an attractively efficient way to capture, in digestible portions, the latest controversy or ‘hot topic’ in emergency medicine. A great advantage to this approach is that someone else has already critically appraised the key papers for you, saving you from having to do this yourself. However, books are revised only periodically (usually every few years), so what was topical or controversial when a book was written may now be passé or resolved and no longer an attractive topic in the fellow ship exam.

In practice, the greatest proportion of a consultant emergency physician’s work time is spent ‘on the floor’, caring for patients directly or providing clinical supervision for registrars and residents. With multiple non-clinical tasks required for a functional Emergency Department, time for critical appraisal of EBM topics may be difficult to access. In terms of emergency medicine advanced training, the bread and butter of clinical emergency medicine remains the focus of the fellowship examination. The regulation 4.10 requirement and an occasional question during the fellowship examination on critical appraisal of the evidence are used to assess the trainee’s capacity for skilled self-directed learning and evidence analysis. In the process of achieving the latter aim, some trainees will aspire to becoming research leaders in the future, boosting the research credibility of our specialty.

A tool kit of EBM techniques

Critical appraisal of a single intervention study

It is assumed that you have already conducted an unbiased, reliable and comprehensive literature review. Having identified the article from major biomedical databases such as MEDLINE and EMBASE and others, you are now ready to appraise it. You wish to determine whether it has internal validity and is applicable to the patients you are looking after in the clinical setting in which you practise.

Critical appraisal requires the following questions to be satisfactorily answered.

Are the study results likely to be valid?

A valid intervention trial addresses a clearly focused question with sufficient methodological rigour to enable the results to be trusted. We clearly need to avoid any bias, which occurs when the outcome is materially affected by factors other than the tested intervention. Key issues to assess pertain to trial design and conduct.

Was the trial design valid?

Adequate sample size. Did the study design specify a large enough sample size that will reliably answer the research question? The criteria for sample size calculations are:

Was the analysis of the trial findings valid?

What are the results?

Measures of treatment effect

Treatment effects of binary outcomes can be pre sented as an absolute difference (such as a risk difference), a relative difference (odds ratio or a risk ratio) or a relative risk (risk experimental group/risk standard group). Treatment effects of con tin uous measurements are usually analysed as absolute differences: for example, (mean blood pres sure experimental group) – (mean blood pressure standard group).

In a parallel group treatment trial an experimental treatment is being compared with standard treatment and patients are followed up for an outcome of interest (such as a specific benefit or harmful event such as death). Other metrics are used that are assisted by an outcomes matrix:

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