Can we learn from hidden mistakes? Self-fulfilling prophecy and responsible neuroprognostic innovation.

A self-fulfilling prophecy (SFP) in neuroprognostication occurs when a patient in coma is predicted to have a poor outcome, and life-sustaining treatment is withdrawn on the basis of that prediction, thus directly bringing about a poor outcome (viz. death) for that patient. In contrast to the predominant emphasis in the bioethics literature, we look beyond the moral issues raised by the possibility that an erroneous prediction might lead to the death of a patient who otherwise would have lived. Instead, we focus on the problematic epistemic consequences of neuroprognostic SFPs in settings where research and practice intersect. When this sort of SFP occurs, the problem is that physicians and researchers are never in a position to notice whether their original prognosis was correct or incorrect, since the patient dies anyway. Thus, SFPs keep us from discerning false positives from true positives, inhibiting proper assessment of novel prognostic tests. This epistemic problem of SFPs thus impedes learning, but ethical obligations of patient care make it difficult to avoid SFPs. We then show how the impediment to catching false positive indicators of poor outcome distorts research on novel techniques for neuroprognostication, allowing biases to persist in prognostic tests. We finally highlight a particular risk that a precautionary bias towards early withdrawal of life-sustaining treatment may be amplified. We conclude with guidelines about how researchers can mitigate the epistemic problems of SFPs, to achieve more responsible innovation of neuroprognostication for patients in coma.

High Mountain Asian glacier response to climate revealed by multi-temporal satellite observations since the 1960s.

Knowledge about the long-term response of High Mountain Asian glaciers to climatic variations is paramount because of their important role in sustaining Asian river flow. Here, a satellite-based time series of glacier mass balance for seven climatically different regions across High Mountain Asia since the 1960s shows that glacier mass loss rates have persistently increased at most sites. Regional glacier mass budgets ranged from -0.40 ± 0.07 m w.e.a-1 in Central and Northern Tien Shan to -0.06 ± 0.07 m w.e.a-1 in Eastern Pamir, with considerable temporal and spatial variability. Highest rates of mass loss occurred in Central Himalaya and Northern Tien Shan after 2015 and even in regions where glaciers were previously in balance with climate, such as Eastern Pamir, mass losses prevailed in recent years. An increase in summer temperature explains the long-term trend in mass loss and now appears to drive mass loss even in regions formerly sensitive to both temperature and precipitation.

Glacial lakes exacerbate Himalayan glacier mass loss.

Heterogeneous glacier mass loss has occurred across High Mountain Asia on a multi-decadal timescale. Contrasting climatic settings influence glacier behaviour at the regional scale, but high intra-regional variability in mass loss rates points to factors capable of amplifying glacier recession in addition to climatic change along the Himalaya. Here we examine the influence of surface debris cover and glacial lakes on glacier mass loss across the Himalaya since the 1970s. We find no substantial difference in the mass loss of debris-covered and clean-ice glaciers over our study period, but substantially more negative (-0.13 to -0.29 m w.e.a-1) mass balances for lake-terminating glaciers, in comparison to land-terminating glaciers, with the largest differences occurring after 2000. Despite representing a minor portion of the total glacier population (~10%), the recession of lake-terminating glaciers accounted for up to 32% of mass loss in different sub-regions. The continued expansion of established glacial lakes, and the preconditioning of land-terminating glaciers for new lake development increases the likelihood of enhanced ice mass loss from the region in coming decades; a scenario not currently considered in regional ice mass loss projections.