공황장애

Background: Panic attacks are common, and while they are not life-threatening events, they can lead to the development of panic disorder and agoraphobia. Appropriate help at the time that a panic attack occurs may decrease the fear associated with the attack and reduce the risk of developing an anxiety disorder. However, few people have the knowledge and skills required to assist. Simple first aid guidelines may help members of the public to offer help to people who experience panic attacks.

Methods: The Delphi method was used to reach consensus in a panel of experts. Experts included 50 professionals and 6 people who had experience of panic attacks and were active in mental health advocacy. Statements about how to assist someone who is having a panic attack were sourced through a systematic search of both professional and lay literature. These statements were rated for importance as first aid guidelines by the expert and consumer panels and guidelines were written using the items most consistently endorsed.

Results: Of 144 statements presented to the panels, 27 were accepted. These statements were used to develop the guidelines appended to this paper.

Conclusion: There are a number of actions which are considered to be useful for members of the public to do if they encounter someone who is having a panic attack. These guidelines will be useful in revision of curricula of mental health first aid programs. They can also be used by members of the public who want immediate information about how to assist someone who is experiencing panic attacks.

Table 1 shows the continuity of participation across the three rounds.

Figure 2 shows the rates of inclusion, exclusion, and re-rating of the items in each round of the questionnaire. From a total of 144 items, 27 were eventually included in the guidelines. (See Table 2 for a categorised list of included items.)

Writing the Guidelines: It was important to the research team to avoid making the guidelines read like a list of 'dos' and 'don'ts'. The accepted items were incorporated into a plain language document. To illustrate, consider the following statements:

1. The first aider should reassure the person that a panic attack, while very frightening, is not life threatening.

2. The first aider should reassure the person that a panic attack, while very frightening, is not dangerous.

3. The first aider should not belittle the person's experience.

4. The first aider should reassure the person that they are safe.

5. The first aider should reassure the person that the symptoms will pass.

These statements were incorporated to make the following paragraph:

Do not belittle the person's experience. Acknowledge that the terror feels very real, but reassure them that a panic attack, while very frightening, is not life threatening or dangerous.

When the guidelines were in draft form, they were sent to all the panel members for feedback. Only feedback related to readability and structure was sought and incorporated. The guidelines are appended to this article and can be freely distributed (see additional file 1).

Panic disorder (PD), a complex anxiety disorder characterized by recurrent panic attacks, represents a poorly understood psychiatric condition which is associated with significant morbidity and an increased risk of suicide attempts and completed suicide. Recently however, neuroimaging and panic provocation challenge studies have provided insights into the pathoetiology of panic phenomena and have begun to elucidate potential neural mechanisms that may underlie panic attacks. In this regard, accumulating evidence suggests that acidosis may be a contributing factor in induction of panic. Challenge studies in patients with PD reveal that panic attacks may be reliably provoked by agents that lead to acid–base dysbalance such as CO2 inhalation and sodium lactate infusion. Chemosensory mechanisms that translate pH into panic-relevant fear, autonomic, and respiratory responses are therefore of high relevance to the understanding of panic pathophysiology. Herein, we provide a current update on clinical and preclinical studies supporting how acid–base imbalance and diverse chemosensory mechanisms may be associated with PD and discuss future implications of these findings.

Background: Anxiety disorders increase risk of future cardiovascular disease (CVD) and mortality, even after controlling for confounds including smoking, lifestyle, and socioeconomic status, and irrespective of a history of medical disorders. While impaired vagal function, indicated by reductions in heart rate variability (HRV), may be one mechanism linking anxiety disorders to CVD, prior studies have reported inconsistent findings highlighting the need for meta-analysis.

Method: Studies comparing resting-state HRV recordings in patients with an anxiety disorder as a primary diagnosis and healthy controls were considered for meta-analysis.

Results: Meta-analyses were based on 36 articles, including 2086 patients with an anxiety disorder and 2294 controls. Overall, anxiety disorders were characterized by lower HRV [high frequency (HF): Hedges’ g = −0.29. 95% CI: −0.41 to −0.17, p < 0.001; time domain: Hedges’ g = −0.45, 95% CI: −0.57 to −0.33, p < 0.001] than controls. Panic disorder (n = 447), post-traumatic stress disorder (n = 192), generalized anxiety disorder (n = 68), and social anxiety disorder (n = 90), but not obsessive–compulsive disorder (n = 40), displayed reductions in HF HRV relative to controls (all ps < 0.001).

Conclusion: Anxiety disorders are associated with reduced HRV, findings associated with a small-to-moderate effect size. Findings have important implications for future physical health and well-being of patients, highlighting a need for comprehensive cardiovascular risk reduction.

Included studies: The search of electronic databases for HRV research in anxiety revealed 4149 studies as at October 2013; these were reduced to 194 after examining study abstracts and then to 36 after reviewing the study methods (Figure 1).

Impact of anxiety disorders on HRV: High frequency HRV was reduced in participants with any anxiety disorder, regardless of specific diagnosis, relative to healthy controls [Hedges’ g = −0.29 (−0.41 to −0.17); SE = 0.06; p < 0.001], a finding associated with a small effect size. Egger’s regression test (p = 0.43) indicated no evidence of publication bias. The Q statistic was significant (Q = 51.39, p = 0.002) indicating study heterogeneity (I2 statistic = 35.8%). To examine findings in further detail, we examined effect sizes in specific anxiety disorders (see Table 2, which displays the summary effect sizes for each disorder; and Supplementary Material, which displays the relevant forest plots for each analysis.). HF HRV was significantly reduced in patients with GAD and SAD, findings associated with a moderate effect size, as well as in those with PD and PTSD, findings associated with a small effect size. Findings for OCD, specific phobia, and those studies in which anxiety disorders were grouped were all non-significant.

Moderator analysis revealed no significant differences across anxiety disorder diagnoses (Q = 6.83; p = 0.34). There was no evidence of heterogeneity between studies using different diagnostic criteria including DSM-III, DSM-IV, or ICD-10 (Q = 0.85, p = 0.65), nor was there heterogeneity for use of medication (Q = 0.1, p = 0.75), co-morbid psychiatric diagnoses (Q = 0.29, p = 0.59), or co-morbid medical disorders (Q = 0.004, p = 0.95). No evidence of heterogeneity between studies using short-term versus long-term recordings was obtained either (Q = 2.92, p = 0.09).

Low frequency HRV did not differ between participants with any anxiety disorder and controls [Hedges’ g = −0.08 (−0.31–0.15); SE = 0.09; p = 0.49]. Egger’s regression test (p = 0.001) indicated evidence of publication bias and the Q statistic was significant (Q = 85.02, p < 0.001) (I2 statistic = 75.3%). However, LF HRV did not differ for any anxiety disorder relative to healthy controls (Table 2). Moderator analyses revealed that LF HRV did not differ across anxiety disorders (Q = 3.73, p = 0.59); nor was there any evidence of heterogeneity from other factors.

Time domain HRV was reduced in participants with any anxiety disorder relative to controls [Hedges’ g = −0.7 (−1.45– 0.05); SE = 0.38; p = 0.07], a finding associated with a moderate effect size. While this finding was at trend levels, the overall Q statistic was significant (Q = 1027.39, p < 0.001) and the I2 statistic was 98.2% indicating high variance between studies, highlighting a need to further inspect these data. Egger’s regression test (p < 0.001) also indicated evidence of publication bias. After the exclusion of a clear outlier (see Supplementary Material), HRV was significantly reduced in those with anxiety disorders relative to healthy controls [Hedges’ g = −0.45 (−0.57 to −0.33); SE = 0.06; p < 0.001], and there was no longer evidence of heterogeneity between studies (Q = 18.46, p = 0.43, I2 statistic = 2.5%). Egger’s regression test still revealed evidence of publication bias (p = 0.01). TD HRV was significantly reduced in patients with PTSD and GAD, findings associated with a moderate effect size, as well as in PD, SAD, and Specific Phobias, findings associated with a small effect size (see Table 2). Follow-up moderator analyses revealed no difference in summary effect sizes between disorders (Q = 2.8, p = 0.73). No evidence of heterogeneity from other factors was observed.

Cognitive-behaviour therapy (CBT) for panic disorder may consist of different combinations of several therapeutic components such as relaxation, breathing retraining, cognitive restructuring, interoceptive exposure and/or in vivo exposure. It is therefore important both theoretically and clinically to examine whether specific components of CBT or their combinations are superior to others in the treatment of panic disorder. Component network meta-analysis (NMA) is an extension of standard NMA that can be used to disentangle the treatment effects of different components included in composite interventions. We searched MEDLINE, EMBASE, PsycINFO and Cochrane Central, with supplementary searches of reference lists and clinical trial registries, for all randomized controlled trials comparing different CBT-based psychological therapies for panic disorder with each other or with control interventions. We applied component NMA to disentangle the treatment effects of different components included in these interventions. After reviewing 2526 references, we included 72 studies with 4064 participants. Interoceptive exposure and face-to-face setting were associated with better treatment efficacy and acceptability. Muscle relaxation and virtual-reality exposure were associated with significantly lower efficacy. Components such as breathing retraining and in vivo exposure appeared to improve treatment acceptability while having small effects on efficacy. The comparison of the most v. the least efficacious combination, both of which may be provided as ‘evidence-based CBT,’ yielded an odds ratio for the remission of 7.69 (95% credible interval: 1.75 to 33.33). Effective CBT packages for panic disorder would include face-to-face and interoceptive exposure components, while excluding muscle relaxation and virtual-reality exposure.

Results of the search: Our search identified 2526 references. After removal of duplicates and screening based on title and abstract, 616 references (353 studies) were retrieved for a full inspection. Finally, 72 studies, representing 4064 participants, were included in quantitative analyses (online Supplement 3).

Description of studies: Online Supplement 4 summarizes the references and characteristics of the included and excluded studies. Table 3 shows the number of study arms that included each component. Apart from third wave components, which were administered only in two studies (each contributing to only one outcome), all other components were well represented in the network. The percentage of agreement among raters for the identification of components ranged from 99.0 to 99.7%.

The risk of bias of many included studies was judged as unclear or high in various important domains. Online Supplement 5 provides the RoB assessment for each domain and for each study. The percentage of agreement among raters for the assessment of RoB ranged from 75 to 96%.

Assessments of transitivity, inconsistency and additivity assumption: We compiled a table of important trial and patient characteristics (therapy duration, percentages of agoraphobic, depressed and drug-treated patients) across treatment comparisons and components. Its visual inspection showed that those effect modifiers were likely to be similarly distributed across the networks of treatments and components, although there was missing information from several studies (online Supplement 2). Overall there was little concern about the plausibility of the transitivity assumption.

After exploring data for inconsistencies, first at the treatment level and then at the component level, we found no strong evidence of inconsistency for any of the explored outcomes but the power of this analysis is expected to be low (online Supplement 6).

We did not find any strong evidence against the additivity assumption (online Supplement 6). Sensitivity analyses examining several clinically relevant interaction terms in the model (ftf with ine, ftf with cr, pe with ine, cr with ive, br with ine, br with ive) did not alter the results: none of these interactions was statistically significant (online Supplement 7).

Primary outcome: remission of panic disorder: Data regarding remission were available from 60 studies, with a total of 134 study arms (3556 patients). Figure 1 shows the network at the treatment level and at the component level.

Including the variance of the treatment effect in the meta-regression model reduced the median heterogeneity standard deviation from τ = 0.85 (0.56–1.22) to τ = 0.40 (0.05–0.73) and the regression coefficient was estimated to be −1.96 (−2.72 to −1.30) providing strong evidence for the presence of small study effects. Heterogeneity was found to be close to the expected values (Turner et al. ). The results from the network meta-regression are presented in Table 3.

The inclusion of third-wave components, interoceptive exposure, face-to-face setting and cognitive restructuring in a composite intervention apparently led to higher odds of remission but uncertainty was large, as seen from the very wide CIs for the corresponding iOR (Table 3). Conversely, placebo effect, breathing retraining, psychoeducation, psychological support, in-vivo exposure and virtual reality exposure were found to decrease the odds of remission, but again with large uncertainty in the estimates. However, including muscle relaxation in a complex treatment was shown to significantly reduce the efficacy in terms of short-term remission. Results were favourable for third-wave components, but with very large uncertainty. As expected, the waiting component (which is mainly administered without other components as a supposedly inert control condition) showed the smallest mean iOR.

Based on the findings of Table 3 (and excluding third wave components, which was only informed by a single study, and for which the estimate was very imprecise) we can identify the CBT associated with the largest remission rates as consisting of (ftf + pl + pe + ps + cr + ine) and the least effective CBT as (pl + pe + ps + br + mr + ive + vre); the components of pl, pe and ps are included here as would be expected in typical CBT programs but in the calculation of relative efficacy their effects are cancelled out and the best treatment would provide an average relative increase in the odds of remission by almost 700% (OR 7.69 CrI 1.75 to 33.33).

Response to the interventions: A total of 55 studies (124 study arms including 3275 patients) provided evidence on the response. There was evidence of small study effects in the comparisons of active interventions v. waiting list. Heterogeneity was found to be within the range of expected values (Turner et al. ). Table 3 gives the values of the iOR values for response estimated from the component network meta-regression. Taken together, results about response were in general agreement with those for remission. Results were more precise for muscle relaxation and virtual reality exposure, which appeared to reduce the odds of response.

Dropout rate from the study: Data regarding dropouts was available from 68 studies, with a total of 153 study arms (3705 patients). Table 3 gives the estimates of the iOR parameters for dropouts, where values smaller than 1 are associated with higher treatment acceptability. Heterogeneity was again found to be within the range of expected values (Turner et al. ).

The low estimate for iORftf suggests that dropouts were generally less frequent in face-to-face therapies than in self-help therapies. Components such as breathing retraining and in vivo exposure seemed to marginally improve treatment acceptability; the inclusion of psychoeducation, interoceptive exposure, cognitive restructuring and muscle relaxation showed negligible influence on dropouts. Finally, psychological support and virtual reality exposure were associated with lower acceptability, although the corresponding estimate came with a lot of uncertainty. The placebo effect was associated with the highest and the waiting component with the second highest odds of dropout. Because all active interventions are administered together with the placebo effect, the estimate for this component can be seen as a sort of an average acceptability of the active treatments. Therefore, our results suggest that the risk of dropout was on average higher in active treatments as a whole than in waiting list (people placed on the waiting list were more likely to return for the assessment at end of a trial than people in active treatments). Results were again favourable but very imprecise for third-wave components.