Harsheen Kaur

A survey on the resources and practices in pediatric critical care of resource-rich and resource-limited countries

BackgroundContemporary critical care research necessitates involvement of multiple centers, preferably from many countries. Adult and pediatric research networks have produced outstanding data; however, their involvement is restricted to a small percentage of the industrialized nations. Implementation of their findings in low- and middle-income countries (LMICs) is fraught with challenges.MethodsWe conducted an online international survey to assess and compare disease burden and resources to participate in multicenter research studies through a listserv of the World Federation of Pediatric Intensive and Critical Care Societies. Respondents were grouped into high-income countries and LMICs on the basis of World Bank classification.ResultsSurvey was completed by 73 centers in 34 countries (34 from high-income countries and 39 from LMICs). Compared with high-income countries, the pediatric intensive care units in LMICs were characterized by a lower number of critical care specialists, more difficult access to hemodialysis, and a lower number of elective postoperative patients, but a similar overall disease burden. Training and resources for research were comparable in the two cohorts.ConclusionsAlthough differences exist in access to both trained providers and equipment, the survey results were more striking in their similarity. It is essential that centers from LMICs be included in multinational studies, to generate results applicable to all children worldwide.

Comparison of staff and family perceptions of causes of noise pollution in the Pediatric Intensive Care Unit and suggested intervention strategies.

Noise and excessive, unwanted sound in the Pediatric Intensive Care Unit (PICU) is common and has a major impact on patients′ sleep and recovery. Previous research has focused mostly on absolute noise levels or included only staff as respondents to acknowledge the causes of noise and to plan for its reduction. Thus far, the suggested interventions have not ameliorated noise, and it continues to serve as a barrier to recovery. In addition to surveying PICU providers through internet-based software, patients′ families were evaluated through in-person interviews utilizing a pretested instrument over 3 months. Families of patients admitted for more than 24 h were considered eligible for evaluation. Participants were asked to rank causes of noise from 1 to 8, with eight being highest, and identified potential interventions as effective or ineffective. In total, 50 families from 251 admissions and 65 staff completed the survey. Medical alarms were rated highest (mean ± standard deviation [SD], 4.9 ± 2.1 [2.8-7.0]), followed by noise from medical equipment (mean ± SD, 4.7 ± 2.1 [2.5-6.8]). This response was consistent among PICU providers and families. Suggested interventions to reduce noise included keeping a patient′s room door closed, considered effective by 93% of respondents (98% of staff; 88% of families), and designated quiet times, considered effective by 82% (80% of staff; 84% of families). Keeping the patient′s door closed was the most effective strategy among survey respondents. Most families and staff considered medical alarms an important contributor to noise level. Because decreasing the volume of alarms such that it cannot be heard is inappropriate, alternative strategies to alert staff of changes in vital signs should be explored.

PROPER: Development of an Early Pediatric Intensive Care Unit Readmission Risk Prediction Tool

Objective: No risk prediction model is currently available to measure patient’s probability for readmission to the pediatric intensive care unit (PICU). This retrospective case–control study was designed to assess the applicability of an adult risk prediction score (Stability and Workload Index for Transfer [SWIFT]) and to create a pediatric version (PRediction Of PICU Early Readmissions [PROPER]). Design: Eighty-six unplanned early (<48 hours) PICU readmissions from January 07, 2007, to June 30, 2014, were compared with 170 random controls. Patient- and disease-specific data and PICU workload factors were compared across the 2 groups. Factors statistically significant on multivariate analysis were included in the creation of the risk prediction model. The SWIFT scores were calculated for cases and controls and compared for validation. Results: Readmitted patients were younger, weighed less, and were more likely to be admitted from the emergency department. There were no differences in gender, race, or admission Pediatric Index of Mortality scores. A higher proportion of patients in the readmission group had a Pediatric Cerebral Performance Category in the moderate to severe disability category. Cases and controls did not differ with respect to staff workload at discharge or discharge day of the week; there was a much higher proportion of patients on supplemental oxygen in the readmission group. Only 2 of 5 categories in the SWIFT model were significantly different, and although the median SWIFT score was significantly higher in the readmissions group, the model discriminated poorly between cases and controls (area under the curve: 0.613). A 7-category PROPER score was created based on a multiple logistic regression model. Sensitivity of this model (score ≥12) for the detection of readmission was 81% with a positive predictive value of 0.50. Conclusion: We have created a preliminary model for predicting patients at risk of early readmissions to the PICU from the hospital floor. The SWIFT score is not applicable for predicting the risk for pediatric population.

Effects of enteral nutrition on clinical outcomes among mechanically ventilated and sedated patients in the pediatric intensive care unit

Objective. To analyze the effects of enteral nutrition on outcomes and complications of critically ill children in the pediatric in-tensive care unit (PICU).Design. Retrospective cohort study. Setting. PICU in a tertiary care academic medical center.Patients. Patients up to age 17 years who were admitted to the PICU between Janu-ary 1, 2011, and December 31, 2013. Interventions. Intubation for more than 48 hours and requiring any sedative medica-tions. Patients with surgical contraindica-tions to feeding were excluded. Measures and Main Results. A total of 165 patients met inclusion criteria. Both manual review of the electronic health re-cord and automated data capture (when-ever technically feasible) were conducted. Data were collected in REDCap software and analyzed using a statistical discovery program. The mean (SD) calorie intake within the first 10 days of PICU admission was 40% (31.9%) of the prescribed calo-ries. Only 67% of the patients had feeding initiated within 48 hours of admission. No significant difference in hospital or PICU length of stay or ventilator-free days was observed in patients who met one-third of their nutritional goals (50.3%) compared with patients who did not (49.7%). Mor-tality was nonsignificantly higher among patients who did not meet nutritional goals (P=.07). No association was found between higher doses of opioids or benzo-diazepines and nutrition tolerance or gas-trointestinal complications. Conclusions. Early adequate enteral nutri-tion had no statistically significant impact on the short-term clinical outcomes of PICU patients.

913: DESIGN AND WORLDWIDE PILOT OF A WEB-BASED, REAL TIME PEDIATRIC CRITICAL CARE DECISION SUPPORT TOOL

Learning Objectives: Incomplete knowledge and adherence to best practices in critical illness often leads to complications and poor outcomes. Creation of an international collaborative using a Quality Improvement approach (Checklist for Early Recognition and Treatment of Acute Illness and Injury in Pediatrics, CERTAINp) can facilitate timely and improved best practice delivery in countries with limited local resources and training in pediatric intensive care. Methods: A web-based platform was created using cognitive and ergonomic principles and integrated into the daily unit workflow to facilitate high quality, high value healthcare behaviors. 6172 pediatric critical care providers were contacted using World Federation of Pediatric and Intensive Care Societies listserv, with 78 PICUs across 34 countries responding (1.3%). 52% PICUs were classified as belonging to Low and Middle Income countries based on the World Bank Classification. 12/35 centers were recruited for this study. 5 centers are currently involved in baseline data collection phase with 2 centers entering the training phase. 183 decision support cards were designed and reviewed by pediatric critical care experts across the world. Innovative content management, team meetings and remote site co-ordination strategies were utilized using web platforms such as Google docs, Trello, MS Project, etc. Results: Data (demographic, lab, clinical, outcome measures, adherence to guidelines) has been collected on 75 patients from 3 centers with a mean patient age of 4.8 ± 4.9 yr; and ICU Length of Stay of 7 ± 6 days; 59% diagnoses were infection related, commonest being Pneumonia and Malaria; 28-day mortality was 28%. Logistic obstacles operating in 5 countries were time-zone differences, IT infrastructure, regional tropical diseases and varied usage of search engines. To overcome them, mobile and print versions of CERTAINp are being developed. Newer syndrome cards are frequently added. Conclusions: Requirement and opportunities exist for multi-center trials in developing countries. Adaptable research design and utilization of IT resources can overcome the barriers.