Abstract Introduction Quality improvement in prehospital emergency medical services (EMS) can only be achieved by high-quality research and critical appraisal of current practices. This study examines current opportunities and barriers in EMS research in the Netherlands. Methods This mixed-methods consensus study consisted of three phases. The first phase consisted of semi-structured interviews with relevant stakeholders. Thematic analysis of qualitative data derived from these interviews was used to identify main themes, which were subsequently discussed in several online focus groups in the second phase. Output from these discussions was used to shape statements for an online Delphi consensus study among relevant stakeholders in EMS research. Consensus was met if 80% of respondents agreed or disagreed on a particular statement. Results Forty-nine stakeholders participated in the study; qualitative thematic analysis of the interviews and focus group discussions identified four main themes: (1) data registration and data sharing, (2) laws and regulations, (3) financial aspects and funding, and (4) organization and culture. Qualitative data from the first two phases of the study were used to construct 33 statements for an online Delphi study. Consensus was reached on 21 (64%) statements. Eleven (52%) of these statements pertained to the storage and use of EMS patient data. Conclusion Barriers for prehospital EMS research in the Netherlands include issues regarding the use of patient data, privacy and legislation, funding and research culture in EMS organizations. Opportunities to increase scientific productivity in EMS research include the development of a national strategy for EMS data and the incorporation of EMS topics in research agendas of national medical professional associations.
In a 13-month period, ligation of the persistent ductus was carried out in 23 prematurely born babies with severe respiratory distress syndrome who were all respirator-dependent. Mean gestational age was 30.6 weeks (26-36 weeks), mean birth weight 1490 g (850-3090 g) with 3 patients under 1000 g. Signs of cardiac failure by large left to right shunt via ductus were seen at the end of the first week of life, radiologic signs as pulmonary edema were seen 1 to 2 days earlier. Mean age at operation was 13.5 days (4-27 days), mean duration of artificial ventilation 22 days (8-59 days). Indomethacin was used orally 12 of these patients without effect to close the ductus. One patient died of cerebral hemorrhage on his 17th day of life, 10 days postoperatively, one 3 1/2 months later at home with porencephaly and hydrocephalus. Four patients show radiologic signs of bronchopulmonary dysplasia. In the following 6 months up to December 1979, another 15 patients with IRDS underwent ductus ligation. Gestational age and birth weights were about the same as in the first group. Out of this second group which has not been followed up for a longer period. 3 babies died. Early mortality in both groups is 10.5% (4 out of 38 patients).
Background The coagulation system is crucial in the pathogenesis of infective endocarditis and undergoes significant changes during course of the disease. However, little is known about the implications of those changes in the perioperative period. Aim of the present study was to delineate the specific coagulation patterns and their clinical consequence in patients undergoing cardiac surgery due to infective endocarditis. Methods In this single-centre, exploratory, prospective observational study, we investigated the incidence and degree of coagulopathy in patients with (n = 31) and without infective endocarditis (n = 39) undergoing cardiac valve surgery. The primary outcome was the differences between these two groups in rotational thromboelastometry (ROTEM) results before, during and after surgery. The secondary outcomes were the differences between the groups in heparin sensitivity, bleeding complications, and transfusion requirements. Results Most ROTEM parameters in EXTEM, INTEM and FIBTEM assays were significantly altered in patients with infective endocarditis. Clotting time in the EXTEM assay was significantly prolonged in the endocarditis group at all time-points, while all clot firmness parameters (A5, A10 and MCF) were significantly increased. The heparin sensitivity index was significantly lower in the endocarditis group (median index 0.99 vs 1.17s. IU -1 .kg -1 , p = .008), indicating increased heparin resistance. Patients with infective endocarditis had more bleeding complications as assessed by the universal definition of perioperative bleeding score (OR 3.0, p = .018), and more patients with endocarditis underwent early re-exploration (p = .018). Conclusions The findings of this exploratory investigation show significantly altered coagulation profiles in patients with infective endocarditis, with concomitant hyper- and hypocoagulability. Furthermore, the incidence of bleeding complications and transfusion requirements were increased in patients with endocarditis. These results show the potential of ROTEM to detect coagulation abnormalities in patients with infective endocarditis. Existing point-of-care coagulation testing guided algorithms for optimizing perioperative coagulation management possibly need to be adjusted for these high-risk patients undergoing cardiac surgery.
KEY POINT: Equivalence or noninferiority testing is required when the aim of a study is to show that a treatment works as good as, or not worse than, another treatment.In this issue of Anesthesia & Analgesia, Tsan et al1 report results of a randomized, controlled trial in which authors compared the laryngeal view during conventional laryngoscopy in the bed-up-head-elevated (BUHE) position to the view obtained during videolaryngoscopy in supine position. These authors appropriately used a noninferiority design aiming to show that the laryngeal view is not significantly worse in the BUHE position. As useful therapies or interventions are currently available for many conditions, research increasingly focuses on whether alternative treatments could be equally useful as (equivalent to), or not worse than (noninferior to), the standard treatment. Such studies are particularly useful when the alternative treatment has advantages, such as lower costs or fewer side effects, and could replace the current standard treatment, when the alternative treatment effect is equivalent or noninferior. Researchers commonly use superiority testing to assess whether one treatment is better than the other, and are then tempted to conclude that the treatments are "similar," "comparable," or "equivalent" when the between-group difference is not statistically significant. However, this is a classic misinterpretation. A nonsignificant result of a superiority test only demonstrates that there is insufficient evidence to claim a difference, but it does not exclude relevant differences.2 Other statistical methods are hence required when the study aim is not to show superiority, but equivalence or noninferiority.2,3 Two different treatments would likely never have identical effects, and even if so, this would be fundamentally impossible to prove. Therefore, an equivalence trial aims to show that the effects differ by no more than a clinically acceptable amount.2,3 This amount is termed the equivalence margin, and it must be specified a priori to avoid post hoc decision making. Similarly, a noninferiority trial assesses whether the alternative treatment is no worse than the standard treatment by more than a prespecified noninferiority margin. While equivalence or noninferiority can be tested with hypothesis tests, the intuitive and statistically equivalent confidence interval (CI)–based approach is often preferred. This concept is illustrated in the Figure here, which shows hypothetical CIs of the mean difference of a continuous outcome between 2 treatments, where a negative difference indicates a worse performance of the treatment of interest.Figure.: The upper part of this figure shows hypothetical CIs, which are identical across all 3 panels. The interpretation depends on whether a superiority, equivalence, or noninferiority testing framework is applied (see text for details). The bold text under the x-axis corresponds to the rejection region, meaning that the null-hypothesis is rejected when the CI entirely lies in that region. Note that a "nonsignificant" result of a superiority test (CIs B, C, and D) does not necessarily correspond to an equivalent or noninferior treatment effect. The lower part of this figure is Figure 2 from Tsan et al,1 showing the mean difference and 2-sided 98% CI of the laryngeal view (expressed as POGO). The authors set the noninferiority margin at −15%. The entire CI lies in the noninferiority region, allowing the authors to claim noninferiority. Note this is analogous to the CI K in the upper part of this figure. CI indicates confidence interval; POGO, percentage of glottic opening.In superiority testing, a 2-sided [100 × (1 − α)]% CI that does not contain the null-difference (A) corresponds to a "statistically significant" difference in a 2-sided hypothesis test on significance level α.4 In contrast, a CI that contains the null value (B, C, and D) is compatible with lack of a difference,4 and is thus "nonsignificant." In equivalence or noninferiority testing, the CI is compared to the equivalence or noninferiority margin (δ), respectively.2,3 A 2-sided [100 × (1 − 2α)]% CI that lies entirely in the equivalence region (G, between −δ and +δ) or noninferiority region (K and L, to the right of −δ) indicates equivalence or noninferiority on significance level α, respectively. Otherwise, equivalence or noninferiority cannot be claimed. Note the difference in the above confidence level between 2-sided superiority testing versus equivalence and noninferiority testing, because equivalence and noninferiority testing actually test 1-sided hypotheses. However, in practice, 2-sided 95% CIs are commonly used for all these tests, as a more conservative 0.025 α level is often recommended for equivalence or noninferiority testing. Tsan et al1 use a 0.01 α level, corresponding to a [100 × (1 − 0.02)]% = 98% CI, as shown in Figure 2 of their manuscript, and included in our Figure here.
OBJECTIVES: To evaluate the base excess response during acute in vivo carbon dioxide changes. DESIGN: Secondary analysis of individual participant data from experimental studies. SETTING: Three experimental studies investigating the effect of acute in vivo respiratory derangements on acid-base variables. SUBJECTS: Eighty-nine (canine and human) carbon dioxide exposures. INTERVENTIONS: Arterial carbon dioxide titration through environmental chambers or mechanical ventilation. MEASUREMENTS AND MAIN RESULTS: For each subject, base excess was calculated using bicarbonate and pH using a fixed buffer power of 16.2. Analyses were performed using linear regression with arterial dioxide (predictor), base excess (outcome), and studies (interaction term). All studies show different baselines and slopes for base excess across carbon dioxide titrations methods. Individual subjects show substantial, and potentially clinically relevant, variations in base excess response across the hypercapnic range. Using a mathematical simulation of 10,000 buffer power coefficients we determined that a coefficient of 12.1 (95% CI, 9.1–15.1) instead of 16.2 facilitates a more conceptually appropriate in vivo base excess equation for general clinical application. CONCLUSIONS: In vivo changes in carbon dioxide leads to changes in base excess that may be clinically relevant for individual patients. A buffer power coefficient of 16.2 may not be appropriate in vivo and needs external validation in a range of clinical settings.
