Cancer prevention recommendations: awareness in a Mexican public hospital.

Background: The recommendations of both the World Cancer Research Fund (WCRF) and the American Institute for Cancer Research (AICR) for the prevention of cancer are important public health tools. These recommendations for the prevention of specific cancers are related to body weight maintenance; physical activity; foods and drinks that promote weight gain; plant foods; foods of animal origin; alcoholic beverages; preservation, processing, and preparation of food; food supplements; and breastfeeding. Methods: This study was a descriptive, cross-sectional, retrospective study. All patients provided written informed consent prior to enrollment in the study. Stratified random sampling was carried out with a convenience sample size of ≥280 participants. The characteristics of the participants were investigated using validated questions. Knowledge about the WCRF/AICR recommendations for the primary prevention of cancer was determined using 14 multiple choice questions validated in this study. Group A included participants who answered that cancer can be prevented and that lifestyle is the main factor related to the onset of cancer; the remaining participants were assigned to Group B. The χ2 test and Mann‒Whitney U test were used to determine differences in the groups. A p-value of ≤0.05 was considered statistically significant. A multiple linear regression analysis with gamma response was performed to assess the knowledge score. Results: A total of 289 participants were included; 168 (58%) participants were in group A, and 121 (42%) participants were in group B. Using a 0 to 14 scale, the median (P25, P75) number of correct answers was 11 (10, 12). There was no evidence of a difference between groups in sex, relationship status, literacy skills, years of education, occupation, monthly income per person, and BMI. Most of the participants reported that they did not consume tobacco (n = 259/289) or alcohol (n = 261/289) in the week prior to completing the survey. Discussion: Most of the participants (58%) considered cancer preventable and agreed that lifestyle factors were the most important factors in cancer development. The results also showed a high level of public awareness of some evidence-based associations between cancer and lifestyle factors, such as tobacco use. Some confusion among the public on other risk factors was also identified: waist circumference, a variable related to excess weight, was not identified as a risk factor for cancer by most of the participants, but the consumption of foods and beverages high in calories was identified as a risk factor by the majority of participants. Awareness of cancer protective and risk factors may lead to positive behavioral changes and eventually reduce the burden of cancer.

Advance Care Planning for Children With Rare Diseases: A Pilot RCT.

BACKGROUND AND OBJECTIVE: Pediatric rare diseases are often life-limiting conditions and/or require constant caregiving. Investigators assessed the initial efficacy of the FAmily CEntered (FACE) pediatric advance care planning (pACP), FACE-Rare, intervention on families' quality of life. METHODS: A pilot-phase, single-blinded, intent-to-treat, randomized controlled clinical trial enrolled families from 1 pediatric quaternary hospital between 2021 and 2023. Intervention families received 3 weekly 60-minute (FACE-Rare pACP) sessions: (1) Carer Support Needs Assessment Tool or Action Plan, (2) Carer Support Needs Assessment Tol Action Plan Review, and (3) Pediatric Next Steps: Respecting Choices pACP. Controls received treatment as usual (TAU). Outcome measures were Beck Anxiety Inventory, Family Appraisal of Caregiving, Functional Assessment of Chronic Illness Therapy (FACIT)-Spirituality, and health care utilization. Generalized mixed effect models with γ response assessed the intervention effect at 3-month follow-up. RESULTS: Children (n = 21) were aged 1 to 10 years, 48% male, 24% Black; and 100% technology dependent. Primary family caregivers (n = 21) were aged 30 to 43 years, 19% male, 19% Black; and 27% household income below the Federal poverty level. Dyads underwent 1:1 randomization: 9 to FACE-Rare and 12 to TAU. TAU caregivers reported statistically lower meaning and peace than FACE-Rare caregivers (0.9, P = .03, confidence interval [CI]: 0.75-0.99). Black caregivers reported significantly less caregiver distress (0.7, P = .04, CI: 0.47-0.98) than non-Black caregivers. Poor families reported more anxiety (3.5, P = .002, CI: 1.62-7.94), more caregiver strain (1.2, P = .006, CI: 1.07-1.42); and less family well-being (0.8, P = .02, CI: 0.64-0.95). CONCLUSIONS: FACE®-Rare was feasible, acceptable, safe, and demonstrated initial efficacy, providing greater feelings of meaning and peace to caregivers. Poverty impacted well-being. A multisite trial is needed to determine generalizability.

PedBotLab: A Novel Video Game-Based Robotic Ankle Platform Created for Therapeutic Exercise for Children With Neurological Impairments.

AIMS: Assess the potential benefits of using PedBotLab, a clinic based robotic ankle platform with integrated video game software, to improve ankle active and passive range of motion, strength, selective motor control, gait efficiency, and balance. METHODS: Ten participants with static neurological injuries and independent ambulation participated in a 10-week pilot study (Pro00013680) to assess feasibility and efficacy of PedBotLab as a therapeutic device twice weekly. Isometric ankle strength, passive and active ankle range of motion, plantarflexor spasticity, selective motor control of the lower extremity, balance, and gait speed were measured pre- and post-trial. RESULTS: Statistically significant improvements were seen in flexibility, active range of motion, and strength in multiple planes of ankle motion. Ankle dorsiflexion with knee flexion and knee extension demonstrated statistically significant results in all outcome measures. No significant changes were observed in gait speed outcomes. CONCLUSIONS: The use of PedbotLab can lead to improvements in ankle strength, flexibility, and active range of motion for children with static neurological injuries. Future studies aim to evaluate the effect on gait quality and work toward developing a home-based device.

External evaluation of the Dynamic Criticality Index: A machine learning model to predict future need for ICU care in hospitalized pediatric patients.

OBJECTIVE: To assess the single site performance of the Dynamic Criticality Index (CI-D) models developed from a multi-institutional database to predict future care. Secondarily, to assess future care-location predictions in a single institution when CI-D models are re-developed using single-site data with identical variables and modeling methods. Four CI-D models were assessed for predicting care locations >6-12 hours, >12-18 hours, >18-24 hours, and >24-30 hours in the future. DESIGN: Prognostic study comparing multi-institutional CI-D models' performance in a single-site electronic health record dataset to an institution-specific CI-D model developed using identical variables and modelling methods. The institution did not participate in the multi-institutional dataset. PARTICIPANTS: All pediatric inpatients admitted from January 1st 2018 -February 29th 2020 through the emergency department. MAIN OUTCOME(S) AND MEASURE(S): The main outcome was inpatient care in routine or ICU care locations. RESULTS: A total of 29,037 pediatric hospital admissions were included, with 5,563 (19.2%) admitted directly to the ICU, 869 (3.0%) transferred from routine to ICU care, and 5,023 (17.3%) transferred from ICU to routine care. Patients had a median [IQR] age 68 months (15-157), 47.5% were female and 43.4% were black. The area under the receiver operating characteristic curve (AUROC) for the multi-institutional CI-D models applied to a single-site test dataset was 0.493-0.545 and area under the precision-recall curve (AUPRC) was 0.262-0.299. The single-site CI-D models applied to an independent single-site test dataset had an AUROC 0.906-0.944 and AUPRC range from 0.754-0.824. Accuracy at 0.95 sensitivity for those transferred from routine to ICU care was 72.6%-81.0%. Accuracy at 0.95 specificity was 58.2%-76.4% for patients who transferred from ICU to routine care. CONCLUSION AND RELEVANCE: Models developed from multi-institutional datasets and intended for application to individual institutions should be assessed locally and may benefit from re-development with site-specific data prior to deployment.

Impact of the COVID-19 Pandemic on the Provision of Dialysis Service and Mortality in Veterans Receiving Maintenance Hemodialysis in the VA: An Interrupted Time-Series Analysis.

INTRODUCTION: According to the US Renal Data System (USRDS), patients with end-stage kidney disease (ESKD) on maintenance dialysis had higher mortality during early COVID-19 pandemic. Less is known about the effect of the pandemic on the delivery of outpatient maintenance hemodialysis and its impact on death. We examined the effect of pandemic-related disruption on the delivery of dialysis treatment and mortality in patients with ESKD receiving maintenance hemodialysis in the Veterans Health Administration (VHA) facilities, the largest integrated national healthcare system in the USA. METHODS: Using national VHA electronic health records data, we identified 7,302 Veterans with ESKD who received outpatient maintenance hemodialysis in VHA healthcare facilities during the COVID-19 pandemic (February 1, 2020, to December 31, 2021). We estimated the average change in the number of hemodialysis treatments received and deaths per 1,000 patients per month during the pandemic by conducting interrupted time-series analyses. We used seasonal autoregressive moving average (SARMA) models, in which February 2020 was used as the conditional intercept and months thereafter as conditional slope. The models were adjusted for seasonal variations and trends in rates during the pre-pandemic period (January 1, 2007, to January 31, 2020). RESULTS: The number (95% CI) of hemodialysis treatments received per 1,000 patients per month during the pre-pandemic and pandemic periods were 12,670 (12,525-12,796) and 12,865 (12,729-13,002), respectively. Respective all-cause mortality rates (95% CI) were 17.1 (16.7-17.5) and 19.6 (18.5-20.7) per 1,000 patients per month. Findings from SARMA models demonstrate that there was no reduction in the dialysis treatments delivered during the pandemic (rate ratio: 0.999; 95% CI: 0.998-1.001), but there was a 2.3% (95% CI: 1.5-3.1%) increase in mortality. During the pandemic, the non-COVID hospitalization rate was 146 (95% CI: 143-149) per 1,000 patients per month, which was lower than the pre-pandemic rate of 175 (95% CI: 173-176). In contrast, there was evidence of higher use of telephone encounters during the pandemic (3,023; 95% CI: 2,957-3,089), compared with the pre-pandemic rate (1,282; 95% CI: 1,241-1,324). CONCLUSIONS: We found no evidence that there was a disruption in the delivery of outpatient maintenance hemodialysis treatment in VHA facilities during the COVID-19 pandemic and that the modest rise in deaths during the pandemic is unlikely to be due to missed dialysis.

Clinical Instability Is a Sign of Severity of Illness: A Cohort Study.

OBJECTIVES: Test the hypothesis that within patient clinical instability measured by deterioration and improvement in mortality risk over 3-, 6-, 9-, and 12-hour time intervals is indicative of increasing severity of illness. DESIGN: Analysis of electronic health data from January 1, 2018, to February 29, 2020. SETTING: PICU and cardiac ICU at an academic children's hospital. PATIENTS: All PICU patients. Data included descriptive information, outcome, and independent variables used in the Criticality Index-Mortality. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: There were 8,399 admissions with 312 deaths (3.7%). Mortality risk determined every three hours using the Criticality Index-Mortality, a machine learning algorithm calibrated to this hospital. Since the sample sizes were sufficiently large to expect statical differences, we also used two measures of effect size, the proportion of time deaths had greater instability than survivors, and the rank-biserial correlation, to assess the magnitude of the effect and complement our hypothesis tests. Within patient changes were compared for survivors and deaths. All comparisons of survivors versus deaths were less than 0.001. For all time intervals, two measures of effect size indicated that the differences between deaths and survivors were not clinically important. However, the within-patient maximum risk increase (clinical deterioration) and maximum risk decrease (clinical improvement) were both substantially greater in deaths than survivors for all time intervals. For deaths, the maximum risk increase ranged from 11.1% to 16.1% and the maximum decrease ranged from -7.3% to -10.0%, while the median maximum increases and decreases for survivors were all less than ± 0.1%. Both measures of effect size indicated moderate to high clinical importance. The within-patient volatility was greater than 4.5-fold greater in deaths than survivors during the first ICU day, plateauing at ICU days 4-5 at 2.5 greater volatility. CONCLUSIONS: Episodic clinical instability measured with mortality risk is a reliable sign of increasing severity of illness. Mortality risk changes during four time intervals demonstrated deaths have greater maximum and within-patient clinical instability than survivors. This observation confirms the clinical teaching that clinical instability is a sign of severity of illness.

The criticality Index-mortality: A dynamic machine learning prediction algorithm for mortality prediction in children cared for in an ICU.

Background: The Criticality Index-Mortality uses physiology, therapy, and intensity of care to compute mortality risk for pediatric ICU patients. If the frequency of mortality risk computations were increased to every 3 h with model performance that could improve the assessment of severity of illness, it could be utilized to monitor patients for significant mortality risk change. Objectives: To assess the performance of a dynamic method of updating mortality risk every 3 h using the Criticality Index-Mortality methodology and identify variables that are significant contributors to mortality risk predictions. Population: There were 8,399 pediatric ICU admissions with 312 (3.7%) deaths from January 1, 2018 to February 29, 2020. We randomly selected 75% of patients for training, 13% for validation, and 12% for testing. Model: A neural network was trained to predict hospital survival or death during or following an ICU admission. Variables included age, gender, laboratory tests, vital signs, medications categories, and mechanical ventilation variables. The neural network was calibrated to mortality risk using nonparametric logistic regression. Results: Discrimination assessed across all time periods found an AUROC of 0.851 (0.841-0.862) and an AUPRC was 0.443 (0.417-0.467). When assessed for performance every 3 h, the AUROCs had a minimum value of 0.778 (0.689-0.867) and a maximum value of 0.885 (0.841,0.862); the AUPRCs had a minimum value 0.148 (0.058-0.328) and a maximum value of 0.499 (0.229-0.769). The calibration plot had an intercept of 0.011, a slope of 0.956, and the R2 was 0.814. Comparison of observed vs. expected proportion of deaths revealed that 95.8% of the 543 risk intervals were not statistically significantly different. Construct validity assessed by death and survivor risk trajectories analyzed by mortality risk quartiles and 7 high and low risk diseases confirmed a priori clinical expectations about the trajectories of death and survivors. Conclusions: The Criticality Index-Mortality computing mortality risk every 3 h for pediatric ICU patients has model performance that could enhance the clinical assessment of severity of illness. The overall Criticality Index-Mortality framework was effectively applied to develop an institutionally specific, and clinically relevant model for dynamic risk assessment of pediatric ICU patients.

National Intravenous Acetaminophen Use in Pediatric Inpatients From 2011-2016.

OBJECTIVE: To 1) determine current intravenous (IV) acetaminophen use in pediatric inpatients; and 2) determine the association between opioid medication duration when used with or without IV acetaminophen. METHODS: A retrospective analysis of pediatric inpatients exposed to IV acetaminophen from January 2011 to June 2016, using the national database Health Facts. RESULTS: Eighteen thousand one hundred ninety-seven (2.0%) of 893,293 pediatric inpatients received IV acetaminophen for a median of 14 doses per patient (IQR, 8-56). A greater proportion of IV acetaminophen patients were admitted to the intensive care unit (ICU) (14.8% vs 5.1%, p < 0.0001), received positive pressure ventilation (2.0% vs 1.5%, p < 0.0001), had a higher hospital mortality rate (0.9% vs 0.3%, p < 0.0001), and were operative (35.5% vs 12.8%, p < 0.001) than those not receiving IV acetaminophen. The most common operations associated with IV acetaminophen use were musculoskeletal and digestive system operations. Prescription of IV acetaminophen increased over time, both in prescription rates and number of per patient doses. Of the 18,197 patients prescribed IV acetaminophen, 16,241 (89.2%) also were prescribed opioids during their hospitalization. A multivariate analysis revealed patients prescribed both IV acetaminophen and opioids had a 54.8% increase in opioid duration as compared with patients who received opioids alone. CONCLUSIONS: This is the first study to assess IV acetaminophen prescription practices for pediatric inpatients. Intravenous acetaminophen prescription was greater in the non-operative pediatric inpatient population than operative patients. Intravenous acetaminophen prescription was associated with an increase in opioid duration as compared with patients who received opioids alone, suggesting that it is commonly used to supplement opioids for pain relief.

Dynamic Mortality Risk Predictions for Children in ICUs: Development and Validation of Machine Learning Models.

OBJECTIVES: Assess a machine learning method of serially updated mortality risk. DESIGN: Retrospective analysis of a national database (Health Facts; Cerner Corporation, Kansas City, MO). SETTING: Hospitals caring for children in ICUs. PATIENTS: A total of 27,354 admissions cared for in ICUs from 2009 to 2018. INTERVENTIONS: None. MAIN OUTCOME: Hospital mortality risk estimates determined at 6-hour time periods during care in the ICU. Models were truncated at 180 hours due to decreased sample size secondary to discharges and deaths. MEASUREMENTS AND MAIN RESULTS: The Criticality Index, based on physiology, therapy, and care intensity, was computed for each admission for each time period and calibrated to hospital mortality risk (Criticality Index-Mortality [CI-M]) at each of 29 time periods (initial assessment: 6 hr; last assessment: 180 hr). Performance metrics and clinical validity were determined from the held-out test sample (n = 3,453, 13%). Discrimination assessed with the area under the receiver operating characteristic curve was 0.852 (95% CI, 0.843-0.861) overall and greater than or equal to 0.80 for all individual time periods. Calibration assessed by the Hosmer-Lemeshow goodness-of-fit test showed good fit overall (p = 0.196) and was statistically not significant for 28 of the 29 time periods. Calibration plots for all models revealed the intercept ranged from--0.002 to 0.009, the slope ranged from 0.867 to 1.415, and the R2 ranged from 0.862 to 0.989. Clinical validity assessed using population trajectories and changes in the risk status of admissions (clinical volatility) revealed clinical trajectories consistent with clinical expectations and greater clinical volatility in deaths than survivors (p < 0.001). CONCLUSIONS: Machine learning models incorporating physiology, therapy, and care intensity can track changes in hospital mortality risk during intensive care. The CI-M's framework and modeling method are potentially applicable to monitoring clinical improvement and deterioration in real time.

Association of Intravenous Acetaminophen Administration With the Duration of Intravenous Opioid Use Among Hospitalized Pediatric Patients.

Importance: Adoption of multimodal pain regimens that incorporate nonopioid analgesic medications to reduce inpatient opioid administration can prevent serious opioid-related adverse effects in children, including tolerance, withdrawal, delirium, and respiratory depression. Intravenous (IV) acetaminophen is in widespread pediatric use; however, its effectiveness as an opioid-sparing agent has not been evaluated in general pediatric inpatients. Objective: To determine if IV acetaminophen administered prior to IV opioids is associated with a reduction in the total duration of IV opioids administered compared with IV opioids administered without IV acetaminophen in general pediatric inpatients. Design, Setting, and Participants: This comparative effectiveness research study included data on pediatric inpatients from 274 US hospitals between January 2011 and June 2016 collected from a national database. Outcomes were compared with a propensity score-matched analysis of pediatric inpatients administered IV opioids without IV acetaminophen (control) and those administered IV acetaminophen prior to IV opioids (intervention). Data were analyzed from January 2020 through October 2021. Exposures: Patients in the intervention group received IV acetaminophen prior to IV opioids. Patients in the control group received IV opioids without IV acetaminophen. Main Outcomes and Measures: Total duration of all IV opioids administered during a patient's hospitalization. Results: Of 893 293 pediatric inpatients, a total of 104 579 were included in analysis (median [IQR] age, 1.3 [0-14.7] years; 59 806 [57.2%] female; 21 485 [21.5%] African American, 56 309 [53.8%] White), of whom 18 197 (2.0%) received IV acetaminophen, and 287 504 (34.0%) received IV opioids. After applying exclusion criteria, among patients who received IV acetaminophen, 1739 (10.8%) received IV acetaminophen prior to IV opioids within a median (IQR) treatment time of 1.5 (0.02-7.3) hours. After propensity score matching produced comparable groups in the control and intervention groups (with 839 patients in each group), the multivariable model estimated a 15.5% shorter duration of IV opioid use in the intervention group, with an absolute IV opioid reduction of 7.5 hours (95% CI, 0.7-15.8 hours). Conclusions and Relevance: In this comparative effectiveness study, IV acetaminophen administered prior to IV opioids was associated with a reduction in IV opioid duration by 15.5%. Multimodal pain regimens that use IV acetaminophen prior to IV opioids could reduce IV opioid duration.

Predicting Future Care Requirements Using Machine Learning for Pediatric Intensive and Routine Care Inpatients.

Develop and compare separate prediction models for ICU and non-ICU care for hospitalized children in four future time periods (6-12, 12-18, 18-24, and 24-30 hr) and assess these models in an independent cohort and simulated children's hospital. DESIGN: Predictive modeling used cohorts from the Health Facts database (Cerner Corporation, Kansas City, MO). SETTING: Children hospitalized in ICUs. PATIENTS: Children with greater than or equal to one ICU admission (n = 20,014) and randomly selected routine care children without ICU admission (n = 20,130) from 2009 to 2016 were used for model development and validation. An independent 2017-2018 cohort consisted of 80,089 children. INTERVENTIONS: None. MEASUREMENT AND MAIN RESULTS: Initially, we undersampled non-ICU patients for development and comparison of the models. We randomly assigned 64% of patients for training, 8% for validation, and 28% for testing in both clinical groups. Two additional validation cohorts were tested: a simulated children's hospitals and the 2017-2018 cohort. The main outcome was ICU care or non-ICU care in four future time periods based on physiology, therapy, and care intensity. Four independent, sequential, and fully connected neural networks were calibrated to risk of ICU care at each time period. Performance for all models in the test sample were comparable including sensitivity greater than or equal to 0.727, specificity greater than or equal to 0.885, accuracy greater than 0.850, area under the receiver operating characteristic curves greater than or equal to 0.917, and all had excellent calibration (all R2 s > 0.98). Model performance in the 2017-2018 cohort was sensitivity greater than or equal to 0.545, specificity greater than or equal to 0.972, accuracy greater than or equal to 0.921, area under the receiver operating characteristic curves greater than or equal to 0.946, and R2 s greater than or equal to 0.979. Performance metrics were comparable for the simulated children's hospital and for hospitals stratified by teaching status, bed numbers, and geographic location. CONCLUSIONS: Machine learning models using physiology, therapy, and care intensity predicting future care needs had promising performance metrics. Notably, performance metrics were similar as the prediction time periods increased from 6-12 hours to 24-30 hours.

Healthy Lifestyle and Mood: A Biomedical Informatics Citizen Science Project in a High School Classroom.

Mental health is an increasing concern in adolescents. Mental health disorders can affect academic performance, affect the cultivation of healthy relationships, and even lead to suicide. Healthy lifestyle can improve mental health, though there are gaps in the research, partly resulted from the lack of detailed longitudinal datasets on lifestyle and mental health. To inform and engage students in the research on adolescent lifestyle and mood, the George Washington University and the T.C. Williams High School in Alexandria, Virginia teamed up in a citizen science project. Students generated questions, collected data on themselves, analyzed the data, and produced research reports relating to their mental health and lifestyle. Student feedbacks suggest that the students find the project to be generally interesting and some students (46%) reported that the participation in the project may influence their college and career plans. The anonymized dataset resulted from the project provides another contribution to science.

Medications for Children Receiving Intensive Care: A National Sample.

OBJECTIVE: To examine medication administration records through electronic health record data to provide a broad description of the pharmaceutical exposure of critically ill children. DESIGN: Retrospective cohort study using the Cerner Health Facts database. SETTING: United States. PATIENTS: A total of 43,374 children 7 days old to less than 22 years old receiving intensive care with available pharmacy data. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 907,440 courses of 1,080 unique medications were prescribed with a median of nine medications (range, 1-99; 25-75th percentile, 5-16) per patient. The most common medications were acetaminophen, ondansetron, and morphine. Only 45 medications (4.2%) were prescribed to more than 5% of patients, and these accounted for 442,067 (48.7%) of the total courses of medications. Each additional medication was associated with increased univariate risk of mortality (odds ratio, 1.05; 95% CI, 1.05-1.06; p < 0.001). CONCLUSIONS: Children receiving intensive care receive a median of nine medications per patient and one quarter are prescribed at least than 16 medications. Only 45 medications were prescribed to more than 5% of patients, but these accounted for almost half of all medication courses.

Sedation, Analgesia, and Neuromuscular Blockade: An Assessment of Practices From 2009 to 2016 in a National Sample of 66,443 Pediatric Patients Cared for in the ICU.

OBJECTIVES: To describe the pharmaceutical management of sedation, analgesia, and neuromuscular blockade medications administered to children in ICUs. DESIGN: A retrospective analysis using data extracted from the national database Health Facts. SETTING: One hundred sixty-one ICUs in the United States with pediatric admissions. PATIENTS: Children in ICUs receiving medications from 2009 to 2016. EXPOSURE/INTERVENTION: Frequency and duration of administration of sedation, analgesia, and neuromuscular blockade medications. MEASUREMENTS AND MAIN RESULTS: Of 66,443 patients with a median age of 1.3 years (interquartile range, 0-14.5), 63.3% (n = 42,070) received nonopioid analgesic, opioid analgesic, sedative, and/or neuromuscular blockade medications consisting of 83 different agents. Opioid and nonopioid analgesics were dispensed to 58.4% (n = 38,776), of which nonopioid analgesics were prescribed to 67.4% (n = 26,149). Median duration of opioid analgesic administration was 32 hours (interquartile range, 7-92). Sedatives were dispensed to 39.8% (n = 26,441) for a median duration of 23 hours (interquartile range, 3-84), of which benzodiazepines were most common (73.4%; n = 19,426). Neuromuscular-blocking agents were dispensed to 17.3% (n = 11,517) for a median duration of 2 hours (interquartile range, 1-15). Younger age was associated with longer durations in all medication classes. A greater proportion of operative patients received these medication classes for a longer duration than nonoperative patients. A greater proportion of patients with musculoskeletal and hematologic/oncologic diseases received these medication classes. CONCLUSIONS: Analgesic, sedative, and neuromuscular-blocking medications were prescribed to 63.3% of children in ICUs. The durations of opioid analgesic and sedative medication administration found in this study can be associated with known complications, including tolerance and withdrawal. Several medications dispensed to pediatric patients in this analysis are in conflict with Food and Drug Administration warnings, suggesting that there is potential risk in current sedation and analgesia practice that could be reduced with practice changes to improve efficacy and minimize risks.

Reintroducing plant coverage in a tropical wetland contaminated with oil and sulfate: rhizosphere effects on Desulfovibrio populations / Reintroducción de cobertura vegetal en un humedal tropical contaminado con petróleo y sulfato: efecto de la rizosfera sobre poblaciones de Desulfovibrio

Abstract The Mexican tropical wetland is a coastal system with capacity to support the contamination derived from the extractive industry and the transformation of crude oil, due to its high plant biodiversity and the presence of rhizospheric reducing sulphate bacteria from plants tolerant to crude oil. A field experiment was carried out for nine months to evaluate the adaptation of aquatic plants Leersia hexandra grass and Eleocharis palustris spikerush reintroduced in a wetland contaminated with 75 560 to 118 789 mg kg-1 of weathered petroleum and also with sulfate, derived from oil and gas pipeline leaks, and gaseous emissions. The effect of the weathered oil and sulfate on the dry matter production and the population density of the bacterium Desulfovibrio spp, isolated from the rhizosphere and soil of both plants, were evaluated. The means of the variables had statistical differences (p< 0.05). Weathered oil inhibited dry matter production of L. hexandra but not E. palustris; the effect of petroleum on Desulfovibrio density was very significant negative in the rhizosphere and in the soil of both plants. Sulfate reduced the dry matter of grass. The exposure of Desulfovibrio to sulfate significantly reduced its density in rhizosphere and soil (p< 0.01). We recommend the use of E. palustris for the decontamination of flooded soils contaminated with weathered oil and sulfate. Rev. Biol. Trop. 66(2): 908-917. Epub 2018 June 01.

Resumen El humedal tropical mexicano es un sistema costero con capacidad para resistir la contaminación derivada de la industria extractiva y la transformación del petróleo crudo, debido a su alta biodiversidad de plantas y la presencia de bacterias rizosféricas reductoras de sulfato de plantas tolerantes al petróleo crudo. Se realizó un experimento en campo durante nueve meses para evaluar la adaptación de las plantas acuáticas Leersia hexandra y Eleocharis palustris reintroducidas en un humedal contaminado con 75 560 a 118 789 mg kg-1 de petróleo intemperizado y también con sulfato, derivados de fugas de oleoductos y de emisiones gaseosas crónicas. Se evaluó el efecto del petróleo intemperizado y del sulfato en la producción de materia seca vegetal y en la densidad poblacional de la bacteria Desulfovibrio spp, aislada de la rizosfera y del rizoplano de ambas especies vegetales. Las medias de las variables tuvieron diferencias estadísticas (p< 0.05). El petróleo intemperizado inhibió la producción de materia seca de L. hexandra pero no de E. palustris; el efecto del petróleo en la densidad de Desulfovibrio fue negativo muy significativo en la rizosfera y en el rizoplano de ambas plantas. El sulfato redujo la materia seca de L. hexandra. La exposición de Desulfovibrio a sulfato redujo muy significativamente (p< 0.01) su densidad en rizosfera y en rizoplano. Recomendamos el uso de E. palustris para la descontaminación de suelos inundables afectados con petróleo intemperizado y con sulfato.

Natural attenuation of weathered oil using aquatic plants in a farm in Southeast Mexico.

An experiment was conducted in field for three years to assess the sustainability of aquatic plants Leersia hexandra, Cyperus articulatus, and Eleocharis palustris for use in the removal of total hydrocarbons of weathered oil in four areas contaminated with 60916-119373 mg/kg of hydrocarbons. The variables evaluated were coverage of plant, dry matter, density of plant growth-promoting rhizobacteria, and the removal of total weathered oil. The variables showed statistical differences (p = 0.05) due to the effects of time and the amount of oil in the soil. The three aquatic plants survived on the farm during the 36-month evaluation. The grass L. hexandra yielded the greatest coverage of plant but was inhibited by the toxicity of the oil, which, in contrast, stimulated the coverage of C. articulatus. The rhizosphere of L. hexandra in control soil was more densely colonized by N-fixing bacteria, while the density of phosphate and potassium solubilizing rhizobacteria was stimulated by exposure to oil. C. articulatus coverage showed positive relationship with the removal of weathered oil; positive effect between rhizosphere and L. hexandra grass coverage was also identified. These results contributed to the removal of weathered oil in Gleysols flooded and affected by chronic discharges of crude oil.