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Intranasal treatment of cluster headache

We read with interest the pilot results of Petersen et al. on the use of intranasal ketamine for cluster headache.1 Indeed, given the limited options for cluster headache,2 adding to the armamentarium of treatment options is vitally important. However, we agree that a larger controlled design is needed. While the initial results are promising, it is possible that they are no better than other commonly tried treatments, as has been shown previously when comparing intranasal ketamine to IV metoclopramide for headache.3 Even if intranasal ketamine treatment is superior to alternative treatments for cluster headache, it may not be due to the ketamine per se, but rather secondary to stimulation of the sphenopalatine ganglion (SPG). SPG has an important role in the pathophysiology of cluster headache, and for this reason, SPG stimulation has been used to treat cluster headache with minimally invasive implantable devices.4 The authors acknowledge the utility of SPG modulation, but suggest that it is unrealistic because the device they reference is no longer available. However, other SPG devices exist.5 Furthermore, we have had good success treating headaches using SPG block without any device— namely, by coating cotton swabs with bupivacaine and swabbing inside the patients’ nostrils. Alternatively, one can use an IV catheter attached to a syringe in order to cake the SPG with fluid. Regardless, a future trial ideally not only compares intranasal ketamine to IV medications, but also intranasal ketamine to SPG stimulation/blockade. On a separate note, we wonder why the authors chose to use mean change in pain. The numerical rating scale used by the authors to assess pain is an ordinal scale; therefore, many would deem the use of parametric statistics as inappropriate, unless the changeinpain data are normal in distribution.6 Otherwise, one would expect medians with interquartile ranges for nonnormally distributed continuous data. The spaghetti plots do not necessarily lead one to be able to infer the distribution. It is possible (and probable) that the ultimate results would remain unchanged even with nonparametric statistics. But they would be interesting to see— or otherwise, a metric describing the distribution of the data (whether via Kolmogorov– Smirnov or ShapiroWilk tests or otherwise)— to reassure providers as to the effect (or perhaps lack thereof) of treatment.