Catastrophic storms share several cardinal features, including heavy precipitation, damaging winds, and rapid progression. But no two storms are the same. Meteorologists rely on differences in severity (tropical depressions versus category 5 hurricanes), character (tornados versus monsoons), and etiology (nor’easters versus typhoons). Such granular characterization has been necessary to protect lives and property, and has been achieved through generations of iterative observation and technological innovation. A global network of meteorologists now combines dozens of parameters, collected continuously and synthesized by complex prediction algorithms, to keep ahead of storms... with variable success. In clinical practice, we often struggle for a sense of the character, severity, and etiology of a patient’s

“hyperinflammatory storm.” Because the distinctions between inflammatory syndromes greatly affect proper treatment, we cannot afford to simply “batten down the hatches” on every patient. A nuanced response requires a nuanced understanding. Given the myriad interacting host and environmental factors that result in systemic inflammation, our task could not be greater. Unfortunately, our biomarkers and prediction algorithms remain very primitive, and our model systems are deeply flawed (1).