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The risk of developing AMS is high on Mt Kilimanjaro. Although taking an extra day to acclimatize with the use of acetazolamide did provide some protection against AMS, ideally trekkers need a more gradual route profile for climbing this mountain.

The I-allele rather than the D-allele of the human angiotensin converting enzyme (ACE) gene has been associated with high-altitude mountaineering success. We investigated whether the I-allele was associated with summit success, and also with AMS development, in altitude-naïve trekkers. Subjects ascended from 1,860 m to the summit over 4 days (n = 34, 'direct-profile') or 5 days (n = 82, 'slower-profile'). Proportionally more II direct-profile subjects were successful than ID or DD, although the difference was not significant (100% of II subjects, 52% ID and 43% DD, P = 0.09). There was no difference in success amongst subjects on the slower-profile (50% II, 45% ID and 58% DD, P = 0.54). There was a non-significant trend for increasing AMS scores in ID/DD subjects. Amongst tourist trekkers on Mt. Kilimanjaro the I-allele is not associated with summit success. No evidence is found to support an association between ACE genotype and AMS development.

More than 30 000 climbers attempt to reach the summit of Mount Kilimanjaro every year; it is likely that a significant proportion have diabetes [1]. Summit success rates in climbers with diabetes appear to be similar to those without diabetes [2,3], with the exception of a study carried out on Mount Kilimanjaro in 2001, in which all 15 climbers with Type 1 diabetes failed to reach the summit [4]. One explanation suggested for this discrepancy is the short time of 5 days allowed for climbers to reach the summit of Kilimanjaro at 5895 m.Whilst investigating altitude physiology and acute mountain sickness (AMS) on tourist trekkers attempting Kilimanjaro, we compared a group of 11 climbers with Type 1 diabetes [six males, five females, age 20 ± 7.6 years (mean ± SD ), body mass index (BMI) 22.0 ± 2.3 kg/m 2 ] with 275 subjects without diabetes (180 males, 95 females, age 33 ± 12.1 years, BMI 23.0 ± 2.8 kg/m 2 ). All subjects gave written informed consent and ethical approval was obtained from the Tanzanian Commission for Science and Technology (COSTECH reference 2005-261-NA-2005. Eight of the eleven diabetic climbers (73%) took regular acetazolamide as AMS prophylaxis, compared with 66 (24%) of subjects without diabetes. The climbers with diabetes attempted the mountain over 7 days, with two acclimatization nights at 3700 m during ascent. Seven of the eleven climbers (64%) reached the summit, a success rate comparable with that of the rest of the hiking population (61%); three reached 5600 m, and one reached 4700 m. Reasons for turning back were AMS symptoms of dizziness, fatigue and nausea.AMS scores (Lake Louise questionnaire) were not different between those with or without diabetes (median = 6, range 1-15 versus median = 6, range 1-21 respectively on the summit day, P = 0.389). The physiological response to high altitude in the diabetic group was not different to that in nondiabetic climbers (SaO 2 , respiratory rate, heart rate and lung function). Although we did not have access to capillary blood glucose measurements, members of the group monitored their own measurements regularly whilst on the mountain.Mount Kilimanjaro is an extremely popular tourist mountain, and the risk of AMS is high for everyone. Climbers with Type 1 diabetes should not have a higher rate of AMS and should not have a reduced chance of success if they are well prepared and acclimatize, and we suggest the two extra acclimatization nights and the high rate of acetazolamide use were critical factors in this group's success. References1 Brubaker PL. Adventure travel and type 1 diabetes: the complicating effects of high altitude. Diabetes Care 2005; 28 : 2563 -2572. 2 Pavan P, Sarto P, Merlo L, Casara D, Ponchia A, Biasin R et al . Extreme altitude mountaineering and type 1 diabetes: the Cho Oyu alpinisti in Alta Quota expedition. Diabetes Care 2003; 26 : 3196-3197. 3 Admetlla J, Leal C, Ricart A. Management of diabetes at high altitude. Br J Sports Med 2001; 35 : 282-283.

PURPOSE Patients with cancer are at increased risk of severe COVID-19 disease, but have heterogeneous presentations and outcomes. Decision-making tools for hospital admission, severity prediction, and increased monitoring for early intervention are critical. We sought to identify features of COVID-19 disease in patients with cancer predicting severe disease and build a decision support online tool, COVID-19 Risk in Oncology Evaluation Tool (CORONET). METHODS Patients with active cancer (stage I-IV) and laboratory-confirmed COVID-19 disease presenting to hospitals worldwide were included. Discharge (within 24 hours), admission (≥ 24 hours inpatient), oxygen (O2) requirement, and death were combined in a 0-3 point severity scale. Association of features with outcomes were investigated using Lasso regression and Random Forest combined with Shapley Additive Explanations. The CORONET model was then examined in the entire cohort to build an online CORONET decision support tool. Admission and severe disease thresholds were established through pragmatically defined cost functions. Finally, the CORONET model was validated on an external cohort. RESULTS The model development data set comprised 920 patients, with median age 70 (range 5-99) years, 56% males, 44% females, and 81% solid versus 19% hematologic cancers. In derivation, Random Forest demonstrated superior performance over Lasso with lower mean squared error (0.801 v 0.807) and was selected for development. During validation (n = 282 patients), the performance of CORONET varied depending on the country cohort. CORONET cutoffs for admission and mortality of 1.0 and 2.3 were established. The CORONET decision support tool recommended admission for 95% of patients eventually requiring oxygen and 97% of those who died (94% and 98% in validation, respectively). The specificity for mortality prediction was 92% and 83% in derivation and validation, respectively. Shapley Additive Explanations revealed that National Early Warning Score 2, C-reactive protein, and albumin were the most important features contributing to COVID-19 severity prediction in patients with cancer at time of hospital presentation. CONCLUSION CORONET, a decision support tool validated in health care systems worldwide, can aid admission decisions and predict COVID-19 severity in patients with cancer.