Timothy J. McCulloch

Posttraumatic stress disorder in aware patients from the B-aware trial.

BACKGROUND: The long-term consequences of an awareness episode vary. Some patients do not have any long-term disability, whereas others develop psychological problems that may be severe and persistent. In this study, we compared the incidence of posttraumatic stress disorder (PTSD) in patients with and without confirmed awareness who were randomized in the B-Aware Trial. METHODS: We used a matched cohort design, aiming to follow up the 13 patients with confirmed awareness. Each surviving awareness patient was matched with 4 controls for age, sex, surgery type, date of surgery, and hospital. A face-to-face interview was conducted with each awareness patient and matched controls using the Clinician Administered Posttraumatic Stress Disorder Scale. RESULTS: Data collection for this study occurred between June 2006 and March 2007, with a median follow-up time of 5.3 yr (range, 4.3–5.7 yr). Six of the 13 confirmed awareness patients had died. Five of the 7 confirmed awareness patients (71%) and 3 of the 25 controls (12%) fulfilled the criteria for PTSD at the time of the interview (adjusted odds ratio = 13.3 [95% confidence interval: 1.4–650]; P = 0.02). The median onset time of symptoms was 14 days (range, 7–243 days) after surgery, and the median duration of symptoms was 4.7 yr (range, 4.4–5.6 yr). CONCLUSIONS: PTSD was common and persistent in the confirmed awareness patients of the B-Aware Trial. Strategies to prevent awareness in patients under general anesthesia are justified.

Graded Hypercapnia and Cerebral Autoregulation during Sevoflurane or Propofol Anesthesia

BackgroundHypercapnia abolishes cerebral autoregulation, but little is known about the interaction between hypercapnia and autoregulation during general anesthesia. With normocapnia, sevoflurane (up to 1.5 minimum alveolar concentration) and propofol do not impair cerebral autoregulation. This study aimed to document the level of hypercapnia required to impair cerebral autoregulation during propofol or sevoflurane anesthesia. MethodsEight healthy subjects received a remifentanil infusion and were anesthetized with propofol (140 &mgr;g · kg−1 · min−1) and sevoflurane (1.0–1.1% end tidal) in a randomized crossover study. Ventilation was adjusted to achieve incremental increases in arterial carbon dioxide partial pressure (Paco2) until autoregulation was impaired. Cerebral autoregulation was tested by increasing the mean arterial pressure (MAP) from 80 to 100 mmHg with phenylephrine while measuring middle cerebral artery flow velocity by transcranial Doppler. The autoregulation index, which has a value ranging from 0 to 1, representing absent to perfect autoregulation, was calculated, and an autoregulation index of 0.4 or less represented significantly impaired autoregulation. ResultsThe threshold Paco2 to significantly impair cerebral autoregulation ranged from 50 to 66 mmHg. The threshold averaged 56 ± 4 mmHg (mean ± SD) during sevoflurane anesthesia and 61 ± 4 mmHg during propofol anesthesia (P = 0.03). Carbon dioxide reactivity measured at a MAP of 100 mmHg was 30% greater than that at a MAP of 80 mmHg. ConclusionsEven mild hypercapnia can significantly impair cerebral autoregulation during general anesthesia. There is a significant difference between propofol anesthesia and sevoflurane anesthesia with respect to the effect of hypercapnia on cerebral autoregulation. This difference occurs at clinically relevant levels of Paco2. When inducing hypercapnia, carbon dioxide reactivity is significantly affected by the MAP.

The effect of hypocapnia on the autoregulation of cerebral blood flow during administration of isoflurane.

Isoflurane impairs autoregulation of cerebral blood flow in a dose-related manner. Previous investigations in several other conditions have demonstrated that impaired autoregulation can be restored by hyperventilation. We hypothesized that hypocapnia may restore cerebral autoregulation impaired by isoflurane anesthesia. We administered isoflurane in 100% oxygen to 12 healthy patients aged 21–59 yr scheduled for elective nonneurological surgery. Isoflurane end-tidal concentration was individualized at 0.1% to 0.2% less than that required to induce short periods of isoelectric electroencephalogram. This resulted in an end-tidal isoflurane concentration of 1.6% ± 0.2% (mean ± sd) corresponding to an age-adjusted minimum alveolar anesthetic concentration multiple of 1.4. Mean arterial blood pressure was reduced to <80 mm Hg, by infusion of remifentanil if required. Cerebral autoregulation was assessed by infusing phenylephrine to increase mean arterial blood pressure to 100 mm Hg while monitoring middle cerebral artery blood flow velocity with transcranial Doppler ultrasonography. The change in flow velocity was used to calculate the autoregulation index (ARI). The ARI ranges between 0 and 1 and an ARI ≤0.4 indicates significantly impaired autoregulation. Autoregulation was tested twice in randomized order: once during normocapnia (Paco2 38–43 mm Hg) and once during hypocapnia (Paco2 27–34 mm Hg). The median (interquartile range) ARI was 0.29 (0.23–0.64) during normocapnia and 0.77 (0.70–0.78) during hypocapnia (P < 0.005). Of the 12 subjects, autoregulation was significantly impaired in 8 subjects during normocapnia and none during hypocapnia (P = 0.001). Hypocapnia restored cerebral autoregulation in normal subjects during isoflurane-induced impairment of autoregulation.

A randomized crossover comparison of the effects of propofol and sevoflurane on cerebral hemodynamics during carotid endarterectomy.

Background:Intravenous and inhalational anesthetic agents have differing effects on cerebral hemodynamics: Sevoflurane causes some vasodilation, whereas propofol does not. The authors hypothesized that these differences affect internal carotid artery pressure (ICAP) and the apparent zero flow pressure (critical closing pressure) during carotid endarterectomy. Vasodilation is expected to increase blood flow, reduce ICAP, and reduce apparent zero flow pressure. Methods:In a randomized crossover study, the gradient between systemic arterial pressure and ICAP during carotid clamping was measured while changing between sevoflurane and propofol in 32 patients. Middle cerebral artery blood velocity, recorded by transcranial Doppler, and ICAP waveforms were analyzed to determine the apparent zero flow pressure. Results:ICAP increased when changing from sevoflurane to propofol, causing the mean gradient between arterial pressure and ICAP to decrease by 10 mmHg (95% confidence interval, 6–14 mmHg; P < 0.0001). Changing from propofol to sevoflurane had the opposite effect: The pressure gradient increased by 5 mmHg (95% confidence interval, 2–7 mmHg; P = 0.002). Ipsilateral middle cerebral artery blood velocity decreased when changing from sevoflurane to propofol. Cerebral steal was detected in one patient after changing from propofol to sevoflurane. The apparent zero flow pressure (mean ± SD) was 22 ± 10 mmHg with sevoflurane and 30 ± 14 mmHg with propofol (P < 0.01). There was incomplete drug crossover due to the limited duration of carotid clamping. Conclusions:Compared with sevoflurane, ipsilateral ICAP and apparent zero flow pressure are both higher with propofol. Vasodilatation associated with sevoflurane can cause cerebral steal.

The Effects of hypocapnia and the cerebral autoregulatory response on cerebrovascular resistance and apparent zero flow pressure during isoflurane anesthesia

BACKGROUND: Simultaneous recordings of arterial blood pressure (ABP) and middle cerebral artery blood velocity can be used to calculate the apparent zero flow pressure (aZFP). The inverse of the slope of the pressure-velocity relationship is known as resistance area product (RAP) and is an index of cerebrovascular resistance. There is little information available regarding the effects of vasoactive drugs, arterial carbon dioxide (Paco2), and impaired cerebral autoregulation on aZFP and RAP during general anesthesia. During isoflurane anesthesia, we investigated the effects of hypocapnia and the effects of a phenylephrine infusion, on aZFP and RAP. METHODS: Radial ABP and transcranial Doppler middle cerebral artery blood velocity signals were recorded in 11 adults undergoing isoflurane anesthesia. A phenylephrine infusion was used to increase ABP and ventilation was adjusted to control Paco2. Cerebral hemodynamic variables were compared at two levels of mean ABP (approximately 80 and 100 mm Hg) and at two levels of Paco2: normocapnia (Paco2 38–43 mm Hg) and hypocapnia (Paco2 27–34 mm Hg). Two aZFP analysis methods were compared: one based on linear regression and one based on Fourier analysis of the waveforms. RESULTS: At the lower ABP, aZFP was 23 ± 11 mm Hg and 30 ± 13 mm Hg (mean ± sd) with normocapnia and hypocapnia, respectively (P < 0.001) and RAP was 0.76 ± 0.97 mm Hg · s · cm−1 and 1.16 ± 0.16 mm Hg · s · cm−1 with normocapnia and hypocapnia, respectively (P < 0.001). Similar effects of hypocapnia were seen at the higher ABP. With normocapnia, isoflurane impaired cerebral autoregulation and aZFP did not change with the increase in ABP. With hypocapnia, cerebral autoregulation was not significantly impaired and increasing ABP was associated with increased aZFP (from 30 ± 13 to 35 ± 13 mm Hg, P < 0.01) and increased RAP (from 1.16 ± 0.16 to 1.52 ± 0.20 mm Hg · s · cm−1, P < 0.001). Calculation of the relative contributions of aZFP and RAP to the cerebral hemodynamic responses indicated that changes in RAP appeared to have a greater influence than changes in aZFP. The mean difference between the two methods of determining aZFP (Fourier–regression) was 0.5 ± 3.6 mm Hg (mean ± 2sd). CONCLUSIONS: During isoflurane anesthesia, two interventions that increase cerebral arteriolar tone, hypocapnia and the autoregulatory response to increasing ABP, were associated with increased RAP and increased aZFP. The effect of changes in RAP appeared to be quantitatively greater than the effects of changes in aZFP. These results imply that arteriolar tone influences cerebral blood flow by controlling both resistance and effective downstream pressure.

Widening the search for suspect data – is the flood of retractions about to become a tsunami?

This pessimistic assertion is from a 1988 textbook by T. W. K€orner in which he discussed the statistical methods suggested by J. B. S. Haldane [2] for recognising possibly fraudulent data. He continued his remarks thus: “The kind of tests proposed by Haldane depended on the fact that “higher order faking” required a great deal of computational work. The invention and accessibility of the computer means that the computational work involved has ceased to be a problem for the dishonest scientist” [1]. However, three decades on, we are seeing a number of high-profile cases in which dishonest scientists, apparently unaware of K€orner’s ‘advice’, have been caught out faking results, exposed by the aberrant statistical distributions of their fraudulent data. As previously noted in an editorial [3] accompanying the exposure of one author’s prolific body of fraudulent papers [4], methods being used now to detect fraud are similar to Philip and Haldane’s 1939 analysis of the subsequently discredited genetic experiments of Franz Moewus [5]. As a result of the recent cases, editors and other interested parties are now becoming far more aware of the potential for dishonest authors to submit fraudulent data. This follows a similar increase in awareness of the problem of plagiarism, and many editors are now taking a closer look at aspects like data distributions as well as textual similarity. It could be argued that journals, editors and other bodies charged with the oversight of research have been slow to learn the lessons of history, and to apply newer statistical methods to detect and analyse spurious or suspicious data, but this deficiency is now being addressed. Anaesthesia as a specialty, and particularly the journal Anaesthesia, can rightly claim with vicarious pride that one of its own, John Carlisle, is at the forefront of this effort. Carlisle’s first statistical expos e, involving data from the randomised, controlled trials (RCTs) of Yoshitaka Fujii, made the research world stand up and take notice [4]. After further refinement of the method [6], it was similarly applied to the RCTs of one of Fujii’s regular collaborators, Yuhji Saitoh [7]. Carlisle has now completed a further project of remarkable scale with arguably even more important implications – an analysis of 5087 RCTs, spanning eight journals and 16 years – published in this issue of Anaesthesia [8]. The method of Carlisle’s analysis has been published [6] and explained in detail elsewhere [3]. Briefly, in a properly conducted and accurately reported RCT, differences in baseline characteristics between groups are, by definition, due to chance. For this reason, reporting p values for demographic and other baseline data is usually discouraged. The p value is the probability of random sampling resulting in a difference as large or larger than the observed difference so, because we already know that differences in baseline characteristics occurred by chance, it is uninformative to calculate a p value. Carlisle, however, has developed and refined a novel use for the statistical analysis of baseline data to identify instances where sampling in clinical trials may not have been random, suggesting the trial was either not properly conducted or was inaccurately reported. Essentially, Carlisle’s method identifies papers in which the baseline characteristics (e.g. age, weight) exhibit either too narrow or too wide a distribution than expected by chance, resulting in an excess of p values close to either one or zero. This editorial accompanies an article by Carlisle, Anaesthesia 2017; 72: 944–52.

Pharmacokinetics of sevoflurane uptake into the brain

Two recent studies have examined the pharmacokinetics of sevoflurane in adults. Lu et al.(Pharmacokinetics of sevoflurane uptake into the brain and body, Anaesthesia 2003; 58: 951–6) observed that jugular bulb sevoflurane concentration initially rose unexpectedly rapidly and then approached arterial concentrations unexpectedly slowly, suggesting that a blood–brain diffusion barrier exists. They also observed a large alveolar‐arterial sevoflurane gradient, suggesting that an alveolar–arterial diffusion barrier exists. Nakamura et al. (Predicted sevoflurane partial pressure in the brain with an uptake and distribution model: Comparison with the measured value in internal jugular vein blood. Journal of Clinical Monitoring and Computing 1999; 15: 299–305) found no diffusion barriers. We used a computer model to analyse both data sets and show that the observations of Lu et al. can be explained by contamination of jugular samples with extracerebral blood. It is possible that the alveolar‐arterial gradients observed by Lu et al. are due to discrepancies in conversions between blood concentrations and gas partial pressures. Our study suggests that there is no blood–brain diffusion barrier for sevoflurane and that the data of Lu et al. must be interpreted with caution.

Cerebral hemodynamics immediately following carotid occlusion.

During carotid endarterectomy, we routinely monitor internal carotid artery pressure (PICA) and middle cerebral artery flow velocity (VMCA). PICA has been previously shown to accurately reflect pressure at the origin of the middle cerebral artery, even during times of rapidly changing pressure such as occurs with sudden occlusion of the common carotid artery. We retrospectively analyzed pressure recordings around the time of carotid cross clamping in 29 consecutive carotid endarterectomy operations. Suitable transcranial Doppler recordings of VMCA were available from eight of the operations. Comparing the cardiac cycle prior to cross clamping with the first complete cardiac cycle after cross clamping, the mean PICA fell from 93 mm Hg to 62 mm Hg and the mean VMCA fell from 41 cm·sec−1 to 25 cm·sec−1. Over the subsequent 10 seconds, there was a further decrease in PICA to 51 mm Hg (P < .0001), while VMCA changed in the opposite direction, increasing to 32 cm·sec−1 (P < .01). The patients with the greatest decrease in PICA immediately on cross clamping also had the greatest additional decrease over the following 10 seconds (r = 0.74). The increase in VMCA during the first 10 seconds after carotid occlusion is well recognized and is presumed to be due to autoregulatory vasodilatation. The simultaneous decrease that we observed in PICA indicates an increase in the pressure gradient along the collateral vessels, which is to be expected during a period of increasing flow along those vessels.

Seeking and reporting apparent research misconduct: errors and integrity - a reply

References 1. Carlisle JB. Data fabrication and other reasons for non-random sampling in 5087 randomised, controlled trials in anaesthetic and general medical journals. Anaesthesia 2017; 72: 944–52. 2. Carlisle JB, Dexter F, Pandit JJ, Shafer SL, Yentis SM. Calculating the probability of random sampling for continuous variables in submitted or published randomised controlled trials. Anaesthesia 2015; 70: 848–58. 3. Devlin H. Statistical vigilantes: the war on scientific fraud – Science Weekly podcast. https://www.theguardian.com/ science/audio/2017/sep/14/statisticalvigilantes-the-war-on-scientific-scienceweekly-podcast (accessed 04/10/2017). 4. Senn SJ. Covariate imbalance and random allocation in clinical trials. Statistics in Medicine 1989; 8: 467–75.

Peri-operative lidocaine infusion for open radical prostatectomy.

We would like to invite Weinberg et al. to answer some questions that we have about their paper [1], which reports an improvement in average length of stay, as well as a number of secondary outcomes, when lidocaine was infused for 24 h peri-operatively for open radical prostatectomy. We are concerned that the difference in primary outcome, 1.3 days, appears to be almost entirely due to three outliers in the control group (lengths of stay: 9 days, 14 days and 19 days), and no details are provided to explain why these patients had a much longer hospital stay. Figure 2 in the paper shows a minimal difference in median length of stay and the rates of discharge were similar out to 5 days. In small studies such as this, it cannot be assumed the two groups were matched for confounders. The paper does not report important potential confounders such as duration of surgery and transfusion rates. We are left wondering if the prolonged stay in three of the control group patients may have been due to significant intra-operative or postoperative complications unrelated to the lack of lidocaine. Similarly, the study protocol allowed inclusion of patients taking up to 72 mg of oral morphine per day for up to a month pre-operatively. That amount of opioid could have a very important influence on a study such as this, but no information is provided regarding pre-operative use of opioids or other analgesics. It appears to us that the mean length of stay was compared with a t-test. If so, is that appropriate given the highly unequal variance between groups and the clearly non-normal distribution in the control group? Also, the standard deviation in the control group is several times larger than in the 2009 sample upon which the power calculation was based, suggesting the control group was, for some reason, not representative of the institutions’ usual patients. Furthermore, regarding the pain score comparison, was this analysis performed with a parametric test? The Author Guidelines for Anaesthesia indicate parametric testing of visual analog scale (VAS) data is likely to be inappropriate for samples less than 50. The pain assessment tool is described as a ten millimetre VAS. We suggest it would not be possible for a patient to mark such a tiny scale, and therefore we have concerns about the accuracy of these data. It is stated in the Methods that pain was assessed hourly for the first 4 h then 4-hourly for the next 20 h. It is therefore perplexing that Fig. 3 includes pain scores every hour for the first 24 h. The paper does not indicate who administered a VAS hourly throughout the night. Were those additional data actually numerical pain scores, rather than VAS, collected by ward nurses as part of routine PCA observations and subsequently recovered for this study from the nursing observation charts? If so, that could seriously compromise the reliability of the pain score data. The authors’ statement that lidocaine reduced pain at rest over the first 24 h does not appear to be supported by their data. They claim a difference of 1.8 mm.h . We do not understand how pain can be quantified in units of velocity. If the statistic was actually 1.8 units on the vertical scale of Figure 3 (whatever those units