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The fate of carbon subducted to mantle depths remains uncertain, yet strongly influences the distribution of terrestrial carbon on geologic timescales. Carbon fluxes into subduction zones are exceptionally high where downgoing plates contain thick sedimentary fans. This study uses volcano geochemistry to assess sedimentary carbon recycling in the high-flux Makran subduction zone, where the Arabian plate subducts northward beneath Eurasia. On the basis of strontium isotope geochemistry and 40 Ar– 39 Ar geochronology, I show that a portion of the submarine Indus Fan entered the Makran Trench, melted and ascended as magmas that erupted in southern Afghanistan. The resulting volcano, composed primarily of carbonate minerals, formed at approximately 3.8 million years ago. The 87 Sr/ 86 Sr ratios of the lavas indicate that their magmatic precursors were derived from marine sediments deposited at 28.9 ± 1.4 Ma. This implies that sedimentary carbon was subducted to and returned from mantle depths in less than 27 million years, indicating that magmas can efficiently recycle sedimentary carbon from subducting slabs to the overlying plate. Sedimentary carbon is subducted to, and returned from, mantle depths in less than 27 million years, according strontium isotope analysis and geochronology of lavas from southern Afghanistan.

High‐temperature melting in mantle plumes produces voluminous eruptions that are often temporally coincident with mass extinctions. Paleocene Baffin Island lavas—products of early Iceland mantle plume activity—are exceptionally well characterized geochemically but have poorly constrained stratigraphy, geochronology, and eruptive tempos. To provide better geologic context, we measured seven stratigraphic sections of the volcanic deposits and collected paleomagnetic data from 38 sites in the lavas and underlying Cretaceous sediments (Quqaluit Fm.). The average paleomagnetic pole from this study does not overlap with the expected pole for a stable North American locality at 60 Ma, yet the data have sufficient dispersion to average out secular variation. After ruling out other possibilities, we find that the picrites were probably erupted during a polarity transition, over less than 5 kyr. If so, the average eruption interval was ∼67 years per flow for the thickest sequence of exposed lavas. We also calculate that the flood basalts had a minimum total volume of ∼176 km3 (excluding submerged lavas in Baffin Bay). This implies a minimum eruption rate of ∼0.035 km3 yr−1, which is similar to rates found in West Greenland lavas but less than rates found in larger flood basalts. Despite this, the Baffin and West Greenland lavas temporally correlate with the “End C27n event” (a period of ∼2°C global warming) and may be its underlying cause. Plain Language Summary Lavas erupted about 60 million years ago on Baffin Island, Canada, are well studied by geochemists because they are thought to derive from the Iceland mantle plume. However, the age and eruptive frequencies of the flows are not well known. We report geologic observations from seven packages of lava flows and present paleomagnetic data from 38 sites. We calculate that at least 0.035 km3 of lava was being produced every year during the volcanic episode. Based on the paleomagnetic data, all the flows erupted in less than five thousand years with an average of 67 years between eruptions. This is consistent with results from similar lavas in West Greenland, which likely erupted at the same time. For unknown reasons, the Baffin Island and West Greenland eruptions did not cause a mass extinction but may have caused a global warming event. Key Points New stratigraphic and paleomagnetic data are presented from flood basalts on Baffin Island, Canada The exposed lavas erupted in less than 5,000 years, with an average eruption interval of 67 years Minimum long‐term eruption rates were less than rates found in larger flood basalt provinces

Introduction The modified early warning score (mEWS) has been used to identify decompensating patients in critical care settings, potentially leading to better outcomes and safer, more cost-effective patient care. We examined whether the admission or maximum mEWS of neurosurgical patients was associated with outcomes and total patient costs across neurosurgical procedures. Methods This retrospective cohort study included all patients hospitalized at a quaternary care hospital for neurosurgery procedures during 2019. mEWS were automatically generated during a patient's hospitalization from data available in the electronic medical record. Primary and secondary outcome measures were the first mEWS at admission, maximum mEWS during hospitalization, length of stay (LOS), discharge disposition, mortality, cost of hospitalization, and patient biomarkers (i.e., white blood cell count, erythrocyte sedimentation rate, C-reactive protein, and procalcitonin). Results In 1,408 patients evaluated, a mean first mEWS of 0.5 ± 0.9 (median: 0) and maximum mEWS of 2.6 ± 1.4 (median: 2) were observed. The maximum mEWS was achieved on average one day (median = 0 days) after admission and correlated with other biomarkers (p < 0.0001). Scores correlated with continuous outcomes (i.e., LOS and cost) distinctly based on disease types. Multivariate analysis showed that the maximum mEWS was associated with longer stay (OR = 1.8; 95% CI = 1.6-1.96, p = 0.0001), worse disposition (OR = 0.82, 95% CI = 0.71-0.95, p = 0.0001), higher mortality (OR = 1.7; 95% CI = 1.3-2.1, p = 0.0001), and greater cost (OR = 1.2, 95% CI = 1.1-1.3, p = 0.001). Machine learning algorithms suggested that logistic regression, naïve Bayes, and neural networks were most predictive of outcomes. Conclusion mEWS was associated with outcomes in neurosurgical patients and may be clinically useful. The composite score could be integrated with other clinical factors and was associated with LOS, discharge disposition, mortality, and patient cost. mEWS also could be used early during a patient's admission to stratify risk. Increase in mEWS scores correlated with the outcome to a different degree in distinct patient/disease types. These results show the potential of the mEWS to predict outcomes in neurosurgical patients and suggest that it could be incorporated into clinical decision-making and/or monitoring of neurosurgical patients during admission. However, further studies and refinement of mEWS are needed to better integrate it into patient care.Introduction The modified early warning score (mEWS) has been used to identify decompensating patients in critical care settings, potentially leading to better outcomes and safer, more cost-effective patient care. We examined whether the admission or maximum mEWS of neurosurgical patients was associated with outcomes and total patient costs across neurosurgical procedures. Methods This retrospective cohort study included all patients hospitalized at a quaternary care hospital for neurosurgery procedures during 2019. mEWS were automatically generated during a patient's hospitalization from data available in the electronic medical record. Primary and secondary outcome measures were the first mEWS at admission, maximum mEWS during hospitalization, length of stay (LOS), discharge disposition, mortality, cost of hospitalization, and patient biomarkers (i.e., white blood cell count, erythrocyte sedimentation rate, C-reactive protein, and procalcitonin). Results In 1,408 patients evaluated, a mean first mEWS of 0.5 ± 0.9 (median: 0) and maximum mEWS of 2.6 ± 1.4 (median: 2) were observed. The maximum mEWS was achieved on average one day (median = 0 days) after admission and correlated with other biomarkers (p < 0.0001). Scores correlated with continuous outcomes (i.e., LOS and cost) distinctly based on disease types. Multivariate analysis showed that the maximum mEWS was associated with longer stay (OR = 1.8; 95% CI = 1.6-1.96, p = 0.0001), worse disposition (OR = 0.82, 95% CI = 0.71-0.95, p = 0.0001), higher mortality (OR = 1.7; 95% CI = 1.3-2.1, p = 0.0001), and greater cost (OR = 1.2, 95% CI = 1.1-1.3, p = 0.001). Machine learning algorithms suggested that logistic regression, naïve Bayes, and neural networks were most predictive of outcomes. Conclusion mEWS was associated with outcomes in neurosurgical patients and may be clinically useful. The composite score could be integrated with other clinical factors and was associated with LOS, discharge disposition, mortality, and patient cost. mEWS also could be used early during a patient's admission to stratify risk. Increase in mEWS scores correlated with the outcome to a different degree in distinct patient/disease types. These results show the potential of the mEWS to predict outcomes in neurosurgical patients and suggest that it could be incorporated into clinical decision-making and/or monitoring of neurosurgical patients during admission. However, further studies and refinement of mEWS are needed to better integrate it into patient care.