Guohai Zhou

Burkholderia Species Infections in Patients with Cystic Fibrosis in British Columbia, Canada. 30 Years’ Experience

RATIONALE We have been collecting Burkholderia species bacteria from patients with cystic fibrosis (CF) for the last 30 years. During this time, our understanding of their multispecies taxonomy and infection control has evolved substantially. OBJECTIVES To evaluate the long-term (30 year) epidemiology and clinical outcome of Burkholderia infection in CF, and fully define the risks associated with infection by each species. METHODS Isolates from Burkholderia-positive patients (n=107) were speciated and typed annually for each infected patient. Microbiological and clinical data were evaluated by thorough review of patient charts, and statistical analyses performed to define significant epidemiological factors. MEASUREMENTS AND MAIN RESULTS Before 1995, the majority of new Burkholderia infections were caused by epidemic clones of Burkholderia cenocepacia. After implementation of new infection control measures in 1995, Burkholderia multivorans became the most prevalent species. Survival analysis showed that patients with CF infected with B. cenocepacia had a significantly worse outcome than those with B. multivorans, and a novel finding was that, after Burkholderia infection, the prognosis for females was significantly worse than for males. CONCLUSIONS B. multivorans and B. cenocepacia have been the predominant Burkholderia species infecting people with CF in Vancouver. The implementation of infection control measures were successful in preventing new acquisition of epidemic strains of B. cenocepacia, leaving nonclonal B. multivorans as the most prevalent species. Historically, survival after infection with B. cenocepacia has been significantly worse than B. multivorans infection, and, of new significance, we show that females tend toward worse clinical outcomes.

Identifying a rapid bolus dose of dexmedetomidine (ED50) with acceptable hemodynamic outcomes in children

Dexmedetomidine is a highly sensitive, specific α2 adrenoceptor agonist with anxiolytic, sedative, and analgesic effects. Administration is recommended as a loading dose infused over 10 min. Clinical experience and a previous study suggested a shorter time frame might be used without causing adverse hemodynamic effects.

Improving the Accuracy and Efficiency of Respiratory Rate Measurements in Children Using Mobile Devices

The recommended method for measuring respiratory rate (RR) is counting breaths for 60 s using a timer. This method is not efficient in a busy clinical setting. There is an urgent need for a robust, low-cost method that can help front-line health care workers to measure RR quickly and accurately. Our aim was to develop a more efficient RR assessment method. RR was estimated by measuring the median time interval between breaths obtained from tapping on the touch screen of a mobile device. The estimation was continuously validated by measuring consistency (% deviation from the median) of each interval. Data from 30 subjects estimating RR from 10 standard videos with a mobile phone application were collected. A sensitivity analysis and an optimization experiment were performed to verify that a RR could be obtained in less than 60 s; that the accuracy improves when more taps are included into the calculation; and that accuracy improves when inconsistent taps are excluded. The sensitivity analysis showed that excluding inconsistent tapping and increasing the number of tap intervals improved the RR estimation. Efficiency (time to complete measurement) was significantly improved compared to traditional methods that require counting for 60 s. There was a trade-off between accuracy and efficiency. The most balanced optimization result provided a mean efficiency of 9.9 s and a normalized root mean square error of 5.6%, corresponding to 2.2 breaths/min at a respiratory rate of 40 breaths/min. The obtained 6-fold increase in mean efficiency combined with a clinically acceptable error makes this approach a viable solution for further clinical testing. The sensitivity analysis illustrating the trade-off between accuracy and efficiency will be a useful tool to define a target product profile for any novel RR estimation device.

Postdischarge mortality in children with acute infectious diseases: derivation of postdischarge mortality prediction models.

Objectives To derive a model of paediatric postdischarge mortality following acute infectious illness. Design Prospective cohort study. Setting 2 hospitals in South-western Uganda. Participants 1307 children of 6 months to 5 years of age were admitted with a proven or suspected infection. 1242 children were discharged alive and followed up 6 months following discharge. The 6-month follow-up rate was 98.3%. Interventions None. Primary and secondary outcome measures The primary outcome was postdischarge mortality within 6 months following the initial hospital discharge. Results 64 children died during admission (5.0%) and 61 died within 6 months of discharge (4.9%). Of those who died following discharge, 31 (51%) occurred within the first 30 days. The final adjusted model for the prediction of postdischarge mortality included the variables mid-upper arm circumference (OR 0.95, 95% CI 0.94 to 0.97, per 1 mm increase), time since last hospitalisation (OR 0.76, 95% CI 0.61 to 0.93, for each increased period of no hospitalisation), oxygen saturation (OR 0.96, 95% CI 0.93 to 0·99, per 1% increase), abnormal Blantyre Coma Scale score (OR 2.39, 95% CI 1·18 to 4.83), and HIV-positive status (OR 2.98, 95% CI 1.36 to 6.53). This model produced a receiver operating characteristic curve with an area under the curve of 0.82. With sensitivity of 80%, our model had a specificity of 66%. Approximately 35% of children would be identified as high risk (11.1% mortality risk) and the remaining would be classified as low risk (1.4% mortality risk), in a similar cohort. Conclusions Mortality following discharge is a poorly recognised contributor to child mortality. Identification of at-risk children is critical in developing postdischarge interventions. A simple prediction tool that uses 5 easily collected variables can be used to identify children at high risk of death after discharge. Improved discharge planning and care could be provided for high-risk children.

Preoperative warming and undesired surgical and anesthesia outcomes in pediatric spinal surgery—a retrospective cohort study

Underbody forced air warming is a method commonly used for intraoperative temperature maintenance in children. We previously reported that preoperative forced air warming of children undergoing spinal surgery substantially reduces the incidence and duration of intraoperative hypothermia (<36°C).

Scheduled Follow-Up Referrals and Simple Prevention Kits Including Counseling to Improve Post-Discharge Outcomes Among Children in Uganda: A Proof-of-Concept Study

Post-hospital discharge is a vulnerable time for recurrent illness and death among children. An intervention package consisting of (1) referrals for scheduled follow-up visits, (2) discharge counseling, and (3) simple prevention items such as soap and oral rehydration salts resulted in much higher health seeking and hospital readmissions compared with historical controls. Post-hospital discharge is a vulnerable time for recurrent illness and death among children. An intervention package consisting of (1) referrals for scheduled follow-up visits, (2) discharge counseling, and (3) simple prevention items such as soap and oral rehydration salts resulted in much higher health seeking and hospital readmissions compared with historical controls. ABSTRACT Background: Recurrent illness following hospital discharge is a major contributor to childhood mortality in resource-poor countries. Yet post-discharge care is largely ignored by health care workers and policy makers due to a lack of resources to identify children with recurrent illness and a lack of cohesive systems to provide care. The purpose of this proof-of-concept study was to evaluate the effectiveness of a bundle of interventions at discharge to improve health outcomes during the vulnerable post-discharge period. Methods: The study was conducted between December 2014 and April 2015. Eligible children were between ages 6 months and 5 years who were admitted with a suspected or proven infectious disease to one of two hospitals in Mbarara, Uganda. A bundle of interventions was provided at the time of discharge. This bundle included post-discharge referrals for follow-up visits and a discharge kit. The post-discharge referral was to ensure follow-up with a nearby health care provider on days 2, 7, and 14 following discharge. The discharge kit included brief educational counseling along with simple preventive items as incentives (soap, a mosquito net, and oral rehydration salts) to reinforce the education. The primary study outcome was the number of post-discharge referral visits completed. Secondary study outcomes included satisfaction with the intervention, rates of readmission after 60 days, and post-discharge mortality rates. In addition, outcomes were compared with a historical control group, enrolled using the same inclusion criteria and outcome-ascertainment methods. Results: During the study, 216 children were admitted, of whom 14 died during hospitalization. Of the 202 children discharged, 85% completed at least 1 of the 3 follow-up referral visits, with 48% completing all 3 visits. Within 60 days after discharge, 22 children were readmitted at least once and 5 children (2.5%) died. Twelve (43%) readmissions occurred during a scheduled follow-up visit. Compared with prospectively enrolled historical controls, the post-discharge referral for follow-up increased the odds of readmission (odds ratio [OR], 1.92; 95% confidence interval [CI], 1.14 to 3.23) and care sought after discharge (OR, 14.61; 95% CI, 9.41 to 22.67). Overall satisfaction with the bundle of interventions was high, with most caregivers strongly agreeing that the discharge kit and post-discharge referrals improved their ability to care for their child. Conclusions: Interventions initiated at the time of discharge have the potential to profoundly affect the landscape of care during illness recovery and lead to significantly improved outcomes among children under 5 years of age.

Sequential allocation trial design in anesthesia: an introduction to methods, modeling, and clinical applications

Estimation of the dose–response curve for new anesthetic protocols typically focuses on identifying minimum effective doses. The application of a sequential experimental method is appropriate, as it minimizes sample size requirements by updating dose assignments based on information accrued from successive subjects. One approach is the up‐and‐down method for estimating the median effective dose in a patient population (ED50). Designs better suited for achieving greater than 50% effectiveness, include the biased coin approach, and continual reassessment method. In this review we introduce different sequential design methods, provide examples of their use, and show through simulation how the method employed influences sample size and the accuracy of the estimated dose. Simulation studies are presented to illustrate the effects of dose parameter and stopping rule choice for up‐and‐down method and biased coin approach. For continual reassessment method, the effects of assumed dose–response model, prior guess, and cohort size are simulated. A binary response regression curve was fit to the data in Saidman and Egers endtidal halothane dose‐finding study to provide a dose–response curve for generating simulations. A range of options exist when designing a study using sequential allocation with biased coin approach or continual reassessment method. Method choice influences the required sample size and confidence in estimated effect. In the halothane example, up‐and‐down method decreases the required sample size by 20–30% when the choice of design parameters is optimal. For both up‐and‐down method and biased coin approach designs, greater sample sizes, arising from adjusted stopping criteria, might be required to achieve reliable estimates. The continual reassessment method is only efficient if a limited range of doses can be chosen a priori. In conclusion the up‐and‐down method can be more efficient than nonsequential designs for the estimation of the median dose/intervention level for a given intervention (ED50). The biased coin approach or continual reassessment method are preferred for the estimation of higher or lower tail quantiles such as ED90 or ED10. Continual reassessment method may be superior if knowledge of the dose–response relationship is available for the drug of interest.

A Cohort Study of Morbidity, Mortality and Health Seeking Behavior following Rural Health Center Visits by Children under 12 in Southwestern Uganda

Background Children discharged from hospitals in developing countries are at high risk of morbidity and mortality. However, few data describe these outcomes among children seen and discharged from rural outpatient centers. Objective The objective of this exploratory study was to identify predictors of immediate and follow-up morbidity and mortality among children visiting a rural health center in Uganda. Methods Subjects 0–12 years of age seeking care with a caregiver were consecutively enrolled from a single rural health center in Southwestern Uganda. Baseline variables were collected by research nurses and outcomes of referral, admission or death were recorded (immediate events). Death, hospital admission and health seeking occurring during the 30 days following the clinic visit were also determined (follow-up events). Univariate logistic regression was performed to identify baseline variables associated with immediate outcome and follow-up outcomes. Results Over the four-month recruitment period 717 subjects were enrolled. There were 85 (11.9%) immediate events (10.1% were admitted, 2.2% were referred, none died). Forty-seven (7.8%) events occurred within 30 days after the visit (7.3% sought care from a health provider, 1.5% were admitted and 0.5% died). Variables associated with immediate events included living more than 30 minutes from the health center, age older than 5 years, having received an antimalarial prior to the visit, having seen a community health worker prior to the visit, elevated respiratory rate or temperature, and depressed weight-for-age z score or decreased oxygen saturation. These variables were not associated with follow-up events. Conclusions Sick-child visits at a rural health center in South Western Uganda were associated with rates of mortality and subsequent admission of less than 2% in the period following the sick child visits. Other types of health seeking behavior occurred in approximately 7% of subjects during this same period. Several variables were associated with immediate events but there were no reliable predictors of follow-up events, possibly due to low statistical power.

Pediatric in-Hospital Death from Infectious Disease in Uganda: Derivation of Clinical Prediction Models.

Background Pediatric hospital mortality from infectious diseases in resource constrained countries remains unacceptably high. Improved methods of risk-stratification can assist in referral decision making and resource allocation. The purpose of this study was to create prediction models for in-hospital mortality among children admitted with suspected infectious diseases. Methods This two-site prospective observational study enrolled children between 6 months and 5 years admitted with a proven or suspected infection. Baseline clinical and laboratory variables were collected on enrolled children. The primary outcome was death during admission. Stepwise logistic regression minimizing Akaike’s information criterion was used to identify the most promising multivariate models. The final model was chosen based on parsimony. Results 1307 children were enrolled consecutively, and 65 (5%) of whom died during their admission. Malaria, pneumonia and gastroenteritis were diagnosed in 50%, 31% and 8% of children, respectively. The primary model included an abnormal Blantyre coma scale, HIV and weight-for-age z-score. This model had an area under the curve (AUC) of 0.85 (95% CI, 0.80–0.89) with a sensitivity and specificity of 83% and 76%, respectively. The positive and negative predictive values were 15% and 99%, respectively. Two alternate models with similar performance characteristics were developed withholding HIV and weight-for-age z-score, for use when these variables are not available. Conclusions Risk stratification of children admitted with infectious diseases can be calculated based on several easily measured variables. Risk stratification at admission can be used for allocation of scarce human and physical resources and to guide referral among children admitted to lower level health facilities.

Development and Internal Validation of a Predictive Model Including Pulse Oximetry for Hospitalization of Under-Five Children in Bangladesh

Background The reduction in the deaths of millions of children who die from infectious diseases requires early initiation of treatment and improved access to care available in health facilities. A major challenge is the lack of objective evidence to guide front line health workers in the community to recognize critical illness in children earlier in their course. Methods We undertook a prospective observational study of children less than 5 years of age presenting at the outpatient or emergency department of a rural tertiary care hospital between October 2012 and April 2013. Study physicians collected clinical signs and symptoms from the facility records, and with a mobile application performed recordings of oxygen saturation, heart rate and respiratory rate. Facility physicians decided the need for hospital admission without knowledge of the oxygen saturation. Multiple logistic predictive models were tested. Findings Twenty-five percent of the 3374 assessed children, with a median (interquartile range) age of 1.02 (0.42–2.24), were admitted to hospital. We were unable to contact 20% of subjects after their visit. A logistic regression model using continuous oxygen saturation, respiratory rate, temperature and age combined with dichotomous signs of chest indrawing, lethargy, irritability and symptoms of cough, diarrhea and fast or difficult breathing predicted admission to hospital with an area under the receiver operating characteristic curve of 0.89 (95% confidence interval -CI: 0.87 to 0.90). At a risk threshold of 25% for admission, the sensitivity was 77% (95% CI: 74% to 80%), specificity was 87% (95% CI: 86% to 88%), positive predictive value was 70% (95% CI: 67% to 73%) and negative predictive value was 91% (95% CI: 90% to 92%). Conclusion A model using oxygen saturation, respiratory rate and temperature in combination with readily obtained clinical signs and symptoms predicted the need for hospitalization of critically ill children. External validation of this model in a community setting will be required before adoption into clinical practice.