substantially if one event occurs.
b. Beware when a small sample size results in outcomes that are marginally different between the two cohorts and yet result in a p-value that is significant (e.g., 10 coin flips give 4 heads and 6 tails; it is unlikely that tails are the more likely result, and instead 100 flips might demonstrate that the results are closer to 50:50).
6. Confidence interval (CI):
a. Generally provided as 95% CI—there is a 95% chance that a repeat of a study will demonstrate differences or similarities within the range given. For example, medication A reduces systolic blood pressure by 12 points and medication B reduces systolic blood pressure by 20 points. The average reduction is 8 points, with a 95% CI of 3–12. So, 95% of trials that are duplicates of this study should yield a reduction in systolic blood pressure of 3 to 12 points.
b. Larger trials result in smaller CIs.
7. Diagnostic parameters (▶Fig. 5.2):
a. Sensitivity—how good is the test at picking up a condition (true positives)?
b. Specificity—how good is the test at excluding those without a condition (true negatives)?
c. Positive predictive value—if a test reveals that a condition exists, how likely is it that the condition exists (probability)?
d. Negative predictive value—if a test reveals that the condition does not exist, how likely is it that the condition does not exist (probability)?
B. Tests used routinely in orthopaedic trauma manuscripts
1. Chi-square (ξ2) test—tests the likelihood that two separate samples are different:
a. Comparison of categorical variables (e.g., yes/no; infection present or absent).
b. Fisher’s exact test similarly compares categorical variables and is typically used when sample sizes are small; chi-square test is used when sample sizes are large.
Fig. 5.2 Example of a sensitivity and specificity table evaluating a new test (culture swab) for diagnosis of a disease (tibia infection).
2. One-sample (paired) t test or Wilcoxon rank sum test—tests the likelihood that two different measurements in the same sample are different. Comparison of continuous variables.
3. Two-sample (unpaired) t test or Mann–Whitney U test—tests the likelihood that two separate samples from the same population are different.
4. Analysis of variance (ANOVA)—tests the likelihood that three or more sets of observations made on a single sample are different.
5. Pearson’s or Spearman’s test—if a straight-line association exists between two continuous variables, what is the strength of that association?
6. Linear regression—describes a numerical relationship between two variables.
7. Multiple regression—describes a numerical relationship between one dependent variable and multiple (at least two) other covariates.
V. Critical Analysis of a Journal Article
A. Review the abstract first.
1. Does it catch your attention?
2. Does the research question make sense? Does it matter?
3. Are the authors’ conclusions derived from the data presented?
4. Is it clearly presented?
B. Review methods next.
1. Careful review of inclusion/exclusion criteria and interventions (and control groups).
2. Can the study be duplicated based upon the method presented (i.e., if the methods are followed by another group, can the study be performed by them?)?
3. Was ethical approval obtained?
4. Are there any sources of bias?
a. Check conflicts of interest.
b. Selection bias—occurs when the sample analyzed is not representative of the intended population. Problematic with retrospective trials as treatments provided may have been selected based upon surgeon preference, for example, unblinding of interventions in randomized trials.
c. Interventions are applied by standardization of application (i.e., all patients with condition X received either treatment A or B in a randomized fashion).
d. Outcomes are presented by standardized measurements (i.e., all patients who received a given treatment provided patient-centered outcomes scores, and objective clinical outcomes as measured clinically and radiographically were also consistently reported).
5. Is there sufficient follow-up to determine efficacy in a therapeutic trial?
C. Review the results.
1. Are the results presented in abstract consistent with results presented in body of manuscript?
2. Often, more results are presented in manuscript body than in the abstract.
3. Carefully pay attention to figures and tables (some journals require that all results be presented in table and figure form in addition to prose).
D. Introduction and discussion
1. These sections are potentially more beneficial for the novice reader.
2. Often set the context for the research question and can provide context for use of the results in the scheme of current practice.
3. These sections often represent authors’ opinions and are potentially least helpful to the intermediate/expert reader.
E. References
1. Pay attention to references from reputable journals.
a. A foreign journal is not disreputable.
b. Some open-access journals are very respectable.
2. If many references are from textbooks, be wary.
a. Textbooks/review articles may quote literature incorrectly.
b. A reference to a textbook or review article which misquotes the literature is misleading (perhaps unintentionally).
c. Always go back to source literature (primary research articles), when possible.
Suggested Readings
Greenhalgh T. How to Read a Paper. 5th ed. Wiley Blackwell and BMJ Books, West Sussex, United Kingdom; 2014
JBJS Inc. Levels of Evidence, https://journals.lww.com/jbjsjournal/Pages/Journals-Level-of-Evidence.aspx. Accessed January 17, 2018
Kirkwood BR, Sterne JAC. Essential medical statistics, 2nd ed. Blackwell Science Ltd, Oxford, United Kingdom; 2003
6 Acute Infection Following Musculoskeletal Surgery
Frank R. Avilucea and William T. Obremskey
Introduction
Postoperative infection following internal fixation involves the soft tissues (skin, subcutaneous tissues, muscle fascia, and muscle), hardware, and potentially the bone. The infection is typically bacterial (▶Video 6.1).
I. Preoperative
A.