Height-dependent and height-independent bSCr estimation methods were comparable. This may have significant implications for performing pediatric AKI research using large databases, and in clinical care to define AKI when height is unknown.

Less than half the PICU population had serum creatinine measured before hospital discharge. More severe acute kidney injury was associated with higher likelihood of serum creatinine monitoring and lower probability of acute kidney injury recovery. Future research should address knowledge translation on post-PICU acute kidney injury follow-up before hospital discharge.

Background:Large studies evaluating pediatric acute kidney injury (AKI) epidemiology and outcomes are lacking, partially due to underuse of large administrative health care data.Objective:To assess the diagnostic accuracy of administrative health care data-defined AKI in children admitted to the pediatric intensive care unit (PICU).Design:Retrospective cohort study utilizing chart and administrative data.Setting:Children admitted to the PICU at 2 centers in Montreal, QC.Patients:Patients between 0 and 18 years old with a provincial health insurance number, without end-stage renal disease and admitted to the PICU between January 1, 2003, and March 31, 2005, were included.Measurements:The AKI was defined from chart data using the Kidney Disease: Improving Global Outcomes (KDIGO) definition (Chart-AKI). The AKI defined using administrative health data (Admin-AKI) was based on International Classification of Disease, Ninth Revision (ICD-9) AKI codes.Methods:Data available from retrospective chart review, including baseline and PICU patient characteristics, and serum creatinine (SCr) and urine output (UO) values during PICU admission, were merged with provincial administrative health care data containing diagnostic and procedure codes used for ascertaining Admin-AKI. Sensitivity, specificity, positive, and negative predictive value of Admin-AKI compared with Chart-AKI (reference standard) were calculated. Univariable associations between Admin-AKI and hospital mortality were evaluated.Results:A total of 2051 patients (55% male, mean age at admission 6.1 ± 5.8 years, 355 cardiac surgery, 1696 noncardiac surgery) were included. The AKI defined by SCr or UO criteria occurred in 52% of cardiac surgery patients and 24% of noncardiac surgery patients. Overall, Admin-AKI detected Chart-AKI with low sensitivity, but high specificity in cardiac and noncardiac surgery patients. Sensitivity increased by 1.5 to 2 fold with each increase in AKI severity stage. Admin-AKI was associated with hospital mortality (13% in Admin-AKI vs 2% in non-AKI, P < .001).Limitations:These data were generated in a PICU population; future research should study non-PICU populations.Conclusions:Use of administrative health care data to define AKI in children leads to AKI incidence underestimation. However, for detecting more severe AKI, sensitivity is higher, while maintaining high specificity.

(1) Background: Preventive measures taken in response to the coronavirus disease 2019 (COVID-19) pandemic have adversely affected an entire range of cancer-related medical activities. The reallocation of medical resources, staff, and ambulatory services, as well as critical shortages in pharmaceutical and medical supplies have compelled healthcare professionals to prioritize patients with cancer to treatment and screening services based on a set of classification criteria in cancer-related guidelines. Cancer patients themselves have been affected on multiple levels, and addressing their concerns poses another challenge to the oncology community. (2) Methods: We conducted a Canada-wide search of cancer-related clinical practice guidelines on the management and prioritization of individuals into treatment and screening services. We also outlined the resources provided by Canadian cancer charities and patient advocacy groups to provide cancer patients, or potential cancer patients, with useful information and valuable support resources. (3) Results: The identified provincial guidelines emphasized cancer care (i.e., treatment) more than cancer control (i.e., screening). For cancer-related resources, a clear significance was placed on knowledge & awareness and supportive resources, mainly relating to mental health. (4) Conclusion: We provided a guidance document outlining cancer-related guidelines and resources that are available to healthcare providers and patients across Canada during the COVID-19 pandemic.

Background: The COVID-19 pandemic has disrupted cancer care, raising concerns regarding the impact of wait time, or 'lag time', on clinical outcomes. We aimed to contextualize pandemic-related lag times by mapping pre-pandemic evidence from systematic reviews and/or meta-analyses on the association between lag time to cancer diagnosis and treatment with mortality- and morbidity-related outcomes. Methods: We systematically searched MEDLINE, EMBASE, Web of Science, and Cochrane Library of Systematic Reviews for reviews published prior to the pandemic (1 January 2010-31 December 2019). We extracted data on methodological characteristics, lag time interval start and endpoints, qualitative findings from systematic reviews, and pooled risk estimates of mortality- (i.e., overall survival) and morbidity- (i.e., local regional control) related outcomes from meta-analyses. We categorized lag times according to milestones across the cancer care continuum and summarized outcomes by cancer site and lag time interval. Results: We identified 9,032 records through database searches, of which 29 were eligible. We classified 33 unique types of lag time intervals across 10 cancer sites, of which breast, colorectal, head and neck, and ovarian cancers were investigated most. Two systematic reviews investigating lag time to diagnosis reported different findings regarding survival outcomes among pediatric patients with Ewing's sarcomas or central nervous system tumours. Comparable risk estimates of mortality were found for lag time intervals from surgery to adjuvant chemotherapy for breast, colorectal, and ovarian cancers. Risk estimates of pathologic complete response indicated an optimal time window of 7-8 weeks for neoadjuvant chemotherapy completion prior to surgery for rectal cancers. In comparing methods across meta-analyses on the same cancer sites, lag times, and outcomes, we identified critical variations in lag time research design. Conclusions: Our review highlighted measured associations between lag time and cancer-related outcomes and identified the need for a standardized methodological approach in areas such as lag time definitions and accounting for the waiting-time paradox. Prioritization of lag time research is integral for revised cancer care guidelines under pandemic contingency and assessing the pandemic's long-term effect on patients with cancer. Funding: The present work was supported by the Canadian Institutes of Health Research (CIHR-COVID-19 Rapid Research Funding opportunity, VR5-172666 grant to Eduardo L. Franco). Parker Tope, Eliya Farah, and Rami Ali each received an MSc. stipend from the Gerald Bronfman Department of Oncology, McGill University.

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Background: The COVID-19 pandemic has disrupted cancer care, raising concerns regarding the impact of wait time, or lag time, on clinical outcomes. We aimed to contextualize pandemic-related lag times by mapping pre-pandemic evidence from systematic reviews and/or meta-analyses on the association between lag time to cancer diagnosis and treatment with mortality- and morbidity-related outcomes. Methods: We systematically searched MEDLINE, EMBASE, Web of Science, and Cochrane Library of Systematic Reviews for reviews published prior to the pandemic (1 January 2010-31 December 2019). We extracted data on methodological characteristics, lag time interval start and endpoints, qualitative findings from systematic reviews, and pooled risk estimates of mortality- (i.e., overall survival) and morbidity- (i.e., local regional control) related outcomes from meta-analyses. We categorized lag times according to milestones across the cancer care continuum and summarized outcomes by cancer site and lag time interval. Results: We identified 9,032 records through database searches, of which 29 were eligible. We classified 33 unique types of lag time intervals across 10 cancer sites, of which breast, colorectal, head and neck, and ovarian cancers were investigated most. Two systematic reviews investigating lag time to diagnosis reported contradictory findings regarding survival outcomes among pediatric patients with Ewing's sarcomas or central nervous system tumours. Comparable risk estimates of mortality were found for lag time intervals from surgery to adjuvant chemotherapy for breast, colorectal, and ovarian cancers. Risk estimates of pathologic complete response indicated an optimal time window of 7-8 weeks for neoadjuvant chemotherapy completion prior to surgery for rectal cancers. In comparing methods across meta-analyses on the same cancer sites, lag times, and outcomes, we identified critical variations in lag time research design. Conclusions: Our review highlighted measured associations between lag time and cancer-related outcomes and identified the need for a standardized methodological approach in areas such as lag time definitions and accounting for the waiting-time paradox. Prioritization of lag time research is integral for revised cancer care guidelines under pandemic contingency and assessing the pandemic's long-term effect on patients with cancer.

Background: Anaemia is one of the most significant health problems among children in the world. Detecting anaemia before the symptoms begin to arise will help in limiting the magnitude of this problem. Anaemia is generally recognized as the greatest nutritional problem among children and adolescents. Aims of the Study: This study aims to measure the prevalence, severity, and risk factors of anaemia in primary school children of Alabnaa primary schools, Tabuk city, Saudi Arabia, in the academic year of 2018-2019. Methods: The present study is a cross-sectional one, carried out at Alabnaa primary schools at Tabuk city, Saudi Arabia with total coverage of all the students, who were enrolled in the academic year of 2018-2019. The data was collected via a pre-tested questionnaire, designed to meeting study objectives. The total number of the sampled students was 4158, they have undergone, personal interviews and filling out the questionnaire. General examination including observation of the general condition, and pallor, measuring of pulse, weight, and height, chest, heart, and abdominal examination was done to detect any gross abnormality. Then every student was subjected to measuring the blood HB% by Sahle's method. Students having haemoglobin level less than 70% [cut off point] considered anaemic. Results: The overall prevalence of anaemia among the studied students was 15.6%. Among the anaemic children, 340 (7.6%) had mild anaemia, 308 (7.4%) had moderate anaemia, and 3 (0.07%) had severe anaemia. There was a significant relationship between haemoglobin level and some sociodemographic characteristics and dietary practices of the studied children. Conclusion: This study has revealed that the prevalence of anaemia in children is high and several steps are still needed to increase public awareness about the complications of anaemia, good nutritional habits, iron sources, and prevention of nutritional anaemia.