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BackgroundCancer patients are at increased risk of severe COVID-19. As COVID-19 presentation and outcomes are heterogeneous in cancer patients, decision-making tools for hospital admission, severity prediction and increased monitoring for early intervention are critical.ObjectiveTo identify features of COVID-19 in cancer patients predicting severe disease and build a decision-support online tool; COVID-19 Risk in Oncology Evaluation Tool (CORONET)MethodData was obtained for consecutive patients with active cancer with laboratory confirmed COVID-19 presenting in 12 hospitals throughout the United Kingdom (UK). Univariable logistic regression was performed on pre-specified features to assess their association with admission (≥24 hours inpatient), oxygen requirement and death. Multivariable logistic regression and random forest models (RFM) were compared with patients randomly split into training and validation sets. Cost function determined cut-offs were defined for admission/death using RFM. Performance was assessed by sensitivity, specificity and Brier scores (BS). The CORONET model was then assessed in the entire cohort to build the online CORONET tool.ResultsTraining and validation sets comprised 234 and 66 patients respectively with median age 69 (range 19-93), 54% males, 46% females, 71% vs 29% had solid and haematological cancers. The RFM, selected for further development, demonstrated superior performance over logistic regression with AUROC predicting admission (0.85 vs. 0.78) and death (0.76 vs. 0.72). C-reactive protein was the most important feature predicting COVID-19 severity. CORONET cut-offs for admission and mortality of 1.05 and 1.8 were established. In the training set, admission prediction sensitivity and specificity were 94.5% and 44.3% with BS 0.118; mortality sensitivity and specificity were 78.5% and 57.2% with BS 0.364. In the validation set, admission sensitivity and specificity were 90.7% and 42.9% with BS 0.148; mortality sensitivity and specificity were 92.3% and 45.8% with BS 0.442. In the entire cohort, the CORONET decision support tool recommended admission of 99% of patients requiring oxygen and of 99% of patients who died.Conclusions and RelevanceCORONET, a decision support tool validated in hospitals throughout the UK showed promise in aiding decisions regarding admission and predicting COVID-19 severity in patients with cancer presenting to hospital. Future work will validate and refine the tool in further datasets.

Highlights • EVD is associated with life-threatening electrolyte imbalance and organ dysfunction. • Clinical staging/early warning scores can be useful EVD prognostic indicators. • Enhanced protocolized care is a blueprint for future treatment in low-resource settings., Background Limited data exist describing supportive care management, laboratory abnormalities and outcomes in patients with Ebola virus disease (EVD) in West Africa. We report data which constitute the first description of the provision of enhanced EVD case management protocols in a West African setting. Methods Demographic, clinical and laboratory data were collected by retrospective review of clinical and laboratory records of patients with confirmed EVD admitted between 5 November 2014 and 30 June 2015. Results A total of 44 EVD patients were admitted (median age 37 years (range 17–63), 32/44 healthcare workers), and excluding those evacuated, the case fatality rate was 49% (95% CI 33%–65%). No pregnant women were admitted. At admission 9/44 had stage 1 disease (fever and constitutional symptoms only), 12/44 had stage 2 disease (presence of diarrhoea and/or vomiting) and 23/44 had stage 3 disease (presence of diarrhoea and/or vomiting with organ failure), with case fatality rates of 11% (95% CI 1%–58%), 27% (95% CI 6%–61%), and 70% (95% CI 47%–87%) respectively (p = 0.009). Haemorrhage occurred in 17/41 (41%) patients. The majority (21/40) of patients had hypokalaemia with hyperkalaemia occurring in 12/40 patients. Acute kidney injury (AKI) occurred in 20/40 patients, with 14/20 (70%, 95% CI 46%–88%) dying, compared to 5/20 (25%, 95% CI 9%–49%) dying who did not have AKI (p = 0.01). Ebola virus (EBOV) PCR cycle threshold value at baseline was mean 20.3 (SD 4.3) in fatal cases and 24.8 (SD 5.5) in survivors (p = 0.007). Mean national early warning score (NEWS) at admission was 5.5 (SD 4.4) in fatal cases and 3.0 (SD 1.9) in survivors (p = 0.02). Central venous catheters were placed in 37/41 patients and intravenous fluid administered to 40/41 patients (median duration of 5 days). Faecal management systems were inserted in 21/41 patients, urinary catheters placed in 27/41 and blood component therapy administered to 20/41 patients. Conclusions EVD is commonly associated life-threatening electrolyte imbalance and organ dysfunction. We believe that the enhanced levels of protocolized care, scale and range of medical interventions we report, offer a blueprint for the future management of EVD in resource-limited settings.

This study explored the physical activities of fifth and sixth graders that projected correlations to science performance and how these physical activities may be utilized for classroom purposes in the context of science-related play activities. Descriptive survey correlational design directed the data collection and analysis of the physical activities of purposively selected 133 fifth and sixth graders. Primarily, the study used a researcher-developed and validated instrument (Physical Activity Questionnaire [PAQ]), and standard instruments: Philippine National Physical Activity Guide (PNPAG) and General Physical Activity Questionnaire (GPAQ). The latter classified the physical activities into five domains which directed the interpretation of the participants‟ responses. The Pearson-r Moment of Correlation described the level of correlation of the frequency of engagement to physical activities (limited to local and localized activities) and the science grade of the respondents. Results show that each of the physical activity domains showed specific correlations to science performance of the respondents. For further research, enrichment of the relationship of the physical activities and the science performance may focus on possible moderating variables like economic status, and time allotment for physical activities.

Objective: To determine the knowledge regarding needle stick injury (NSI) among nursing staff and technicians at Isra university Hospital. Study setting: Isra university hospital, Hyderabad Sindh Pakistan Study design: Cross-sectional survey Study duration: 10 months from February 2015 to December 2015 Materials and Method: All the health care providers including nursing staff, dispensers and laboratory technicians of Isra University Hospital, Hyderabad either of gender were included. A structured questionnaire in English language was designed to assess the knowledge regarding needle stick injury. All the data was entered in the proforma. Results: Total 60 health care providers were studied and most common age groups were 31-40 years and 41-50 years. According to health care providers, nurses were most common 46.70%, followed by dispensers 25.0%, laboratory technicians were 18.30% and doctors were only 10.0%. 37.0% had history of needle-stick injuries. Most of the cases 90.0% were aware regarding needle-stick injuries, assisted in disposal of needles was among 67.0%, 58.0% knew about first aid after NSI, 48.0% knew about universal precautions, 63.0% Get investigated after NSI, 48.0% Use gloves and 78.0% had sufficient number of safety tools. Conclusion: It was concluded that the almost all individuals knew regarding needle-stick injuries, but ignorance was very common and use of preventive protocols were inadequate. Key words: Needle-stick injuries, knowledge, healthcare providers

Using the notion of professional uncertainty a population-based proxy need measure for hospital services was developed. Its relationship with socioeconomic variables and Standardized Mortality Ratios (SMR) was investigated in an attempt to develop an adjustment factor for socioeconomic risk factors beyond age-sex adjustment to be used for a population-based healthcare funding formula for Alberta. The data used are 1990, 1991, 1992 vital statistics and hospital separation abstracts, 1991 census data and Refined Diagnosis Related Group (RDRG) case weights. Geographic units studied were the 26 federal electoral districts in Alberta using postal codes as a linkage geo-code between census and hospital utilization and death data. SMRs, age-sex standardized per capita hospital utilization and proxy need rates were derived and correlated with socioeconomic variables derived from the census files. It appears that the poor, the less educated and aboriginals need more hospital services than the affluent, employed and educated, confirming previous findings. The unemployed tend to need more but use fewer services while immigrants and non-white ethnics tend to need and use fewer services. The unemployed, less educated and non-white ethnics are associated with positive correlation with premature mortality (SMR based on deaths under age 75 years), while the employed, highly educated tend to live longer. In general SMRs have positive but very low correlations with utilization and need rates suggesting that SMRs should not be used for resource allocation. Stepwise multiple regression analyses showed that the percentages of unemployed, immigrants, non-whites, aboriginals and those with education less than grade 9 explain about 90% of the variation in age-sex standardized hospital utilization rates. Percentages of unemployed, non-white ethnics, residents with education less than grade 9 and aboriginals explained 71% of variations in age-sex standardized per capita proxy hospital service need measures. Based on the results of regression analyses, a SEAM (Socio-Economic Adjustment Multiplier) scale was developed for utilization (SEAM-U) and proxy needs (SEAM-N). In essence a SEAM is a set of relative value (RV) multipliers applicable to a provincial common per age-sex adjusted capita allocation value to account for the impact of socioeconomic risk factors on hospital service needs or utilization. Finally, the resulting regression equations derived from the 26 Federal electoral district data were applied to Alberta's health regions, regional SEAMs were derived, and the impact of such adjustment was assessed.