Validation of a modified bedside Pediatric Early Warning System score for detection of clinical deterioration in hospitalized pediatric oncology patients: A prospective cohort study.

BACKGROUND: Hospitalized pediatric oncology patients are at risk of severe clinical deterioration. Yet Pediatric Early Warning System (PEWS) scores have not been prospectively validated in these patients. We aimed to determine the predictive performance of the modified BedsidePEWS score for unplanned pediatric intensive care unit (PICU) admission and cardiopulmonary resuscitation (CPR) in this patient population. METHODS: We performed a prospective cohort study in an 80-bed pediatric oncology hospital in the Netherlands, where care has been nationally centralized. All hospitalized pediatric oncology patients aged 0-18 years were eligible for inclusion. A Cox proportional hazard model was estimated to study the association between BedsidePEWS score and unplanned PICU admissions or CPR. The predictive performance of the model was internally validated by bootstrapping. RESULTS: A total of 1137 patients were included. During the study, 103 patients experienced 127 unplanned PICU admissions and three CPRs. The hazard ratio for unplanned PICU admission or CPR was 1.65 (95% confidence interval [CI]: 1.59-1.72) for each point increase in the modified BedsidePEWS score. The discriminative ability was moderate (D-index close to 0 and a C-index of 0.83 [95% CI: 0.79-0.90]). Positive and negative predictive values of modified BedsidePEWS score at the widely used cutoff of 8, at which escalation of care is required, were 1.4% and 99.9%, respectively. CONCLUSION: The modified BedsidePEWS score is significantly associated with requirement of PICU transfer or CPR. In pediatric oncology patients, this PEWS score may aid in clinical decision-making for timing of PICU transfer.

The predictive performance and impact of pediatric early warning systems in hospitalized pediatric oncology patients-A systematic review.

Pediatric early warning systems (PEWS) arewidely used to identify clinically deteriorating patients. Hospitalized pediatric oncology patients are particularly prone to clinical deterioration. We assessed the PEWS performance to predict early clinical deterioration and the effect of PEWS implementation on patient outcomes in pediatric oncology patients. PubMED, EMBASE, and CINAHL databases were systematically searched from inception up to March 2020. Quality assessment was performed using the Prediction model study Risk-Of-Bias Assessment Tool (PROBAST) and the Cochrane Risk-of-Bias Tool. Nine studies were included. Due to heterogeneity of study designs, outcome measures, and diversity of PEWS, it was not possible to conduct a meta-analysis. Although the studies reported high sensitivity, specificity, and area under the receiver operating characteristics curve (AUROC) of PEWS detecting inpatient deterioration, overall risk of bias of the studies was high. This review highlights limited evidence on the predictive performance of PEWS for clinical deterioration and the effect of PEWS implementation.

Associations between intraoperative hypotension, duration of surgery and postoperative myocardial injury after noncardiac surgery: a retrospective single-centre cohort study.

BACKGROUND: Studies of intraoperative hypotension typically specify a blood pressure threshold associated with adverse outcomes. Such thresholds are likely to be study-biased, investigator-biased, or both. We hypothesised that a newly developed modelling method without a threshold, which is biologically more plausible than a threshold-based approach, would reveal a continuous association between exposure to intraoperative hypotension and adverse outcomes. METHODS: Single-centre, retrospective cohort study of subjects ≥60 yr old undergoing noncardiac surgery. We modelled intraoperative hypotension using three different approaches: (1) unweighted, (2) weighted for degree of hypotension (depth), and (3) weighted for duration of hypotension. The primary outcome was myocardial injury, defined as elevated troponin I (>60 ng L-1) measured during the first 3 days after surgery. The associations between the three models, postoperative myocardial injury, and mortality (secondary outcome) were reported as penalised adjusted odds ratios (ORs) scaled between the 75th and 25th percentiles. RESULTS: Myocardial injury occurred in 1812/15 452 (12%) procedures, with 554/15 452 (3.6%) procedures resulting in death before discharge from hospital. The unweighted lower blood pressure measure (OR: 0.26, 95% confidence interval [CI]: 0.12-0.53) and the depth-weighted measure (OR: 4.4, 95% CI: 2.6-7.4) were associated with myocardial injury. The duration-weighted measure was not associated with myocardial injury (OR: 0.89, 95% CI: 0.61-1.3). The unweighted measure (OR 0.08, 95% CI: 0.01-0.40) and the depth-weighted measure (OR: 12, 95% CI, 3.8-35) were associated with in-hospital mortality, but not the duration-weighted measure (OR: 1.3, 95% CI: 0.53-3.0). CONCLUSIONS: Intraoperative hypotension appears to have a graded association with postoperative myocardial injury and mortality, with depth appearing to contribute more than duration.

A Human(e) Factor in Clinical Decision Support Systems.

The overwhelming amount, production speed, multidimensionality, and potential value of data currently available-often simplified and referred to as big data -exceed the limits of understanding of the human brain. At the same time, developments in data analytics and computational power provide the opportunity to obtain new insights and transfer data-provided added value to clinical practice in real time. What is the role of the health care professional in collaboration with the data scientist in the changing landscape of modern care? We discuss how health care professionals should provide expert knowledge in each of the stages of clinical decision support design: data level, algorithm level, and decision support level. Including various ethical considerations, we advocate for health care professionals to responsibly initiate and guide interprofessional teams, including patients, and embrace novel analytic technologies to translate big data into patient benefit driven by human(e) values.

Relationship Between Preoperative Evaluation Blood Pressure and Preinduction Blood Pressure: A Cohort Study in Patients Undergoing General Anesthesia.

BACKGROUND: For outcomes research where changes in intraoperative blood pressure are a possible causative factor, it is important to determine an appropriate source for a reference value. We studied to what extent preinduction blood pressure values in the operating room differ from those obtained during preoperative evaluation outside the operating room. METHODS: Cohort study including 4408 patients aged 60 years or older undergoing noncardiac surgery. The outcome was the difference between the preinduction mean blood pressure (MBP) and the MBP obtained during preoperative evaluation. A difference of ≥10 mm Hg was considered clinically relevant. A paired samples t test was used to estimate the difference. Linear regression was used to obtain estimates adjusted for patient characteristics, comorbidity, medications, type of surgery, and preoperative blood pressure. RESULTS: Complete data were available for 3660 (83%) patients. There were 2228 (61%) patients with a difference of ≥10 mm Hg between the preinduction and preoperative MBP. The overall mean difference between both MBPs was 11 mm Hg (95% confidence interval, 10-11) with important variability among individuals. Patients with higher preoperative MBP values had smaller differences. After adjusting for patient characteristics, comorbidity, medications, type of surgery, and preoperative blood pressure, the difference decreased an estimated 5.0 mm Hg (95% confidence interval, 4.7-5.4) for every increase of 10 mm Hg in preoperative MBP. Patient characteristics, comorbidity, type of surgery, or medication were not strongly associated with the difference. CONCLUSIONS: The average preinduction blood pressure was higher than the preoperative blood pressure. This difference between the measurements can be explained by stress-induced effects and regression to the mean. To define an optimal reference value for research purposes or to arrive at a clinical perioperative blood pressure target, one should consider that there is important variability both within and between patients.

Prediction models: the right tool for the right problem.

PURPOSE OF REVIEW: Perioperative prediction models can help to improve personalized patient care by providing individual risk predictions to both patients and providers. However, the scientific literature on prediction model development and validation can be quite technical and challenging to understand. This article aims to provide the necessary insight for clinicians to assess the value of a prediction model that they intend to use in their clinical practice. RECENT FINDINGS: Recent developments in prediction model research include the continuous development of new performance characteristics for prediction models, increasing insight into the limitations of old characteristics, as well as an improved understanding of the generalizability of prediction models to new populations and practices. SUMMARY: Clinicians can assess the value of a prediction model for their practice by first identifying what the usage of the model will be. Second, they can recognize which performance characteristics are relevant to their assessment of the model. Finally, they need to decide whether the available scientific evidence sufficiently matches their clinical practice to proceed with implementation.

The effect of a preoperative educational film on patients' postoperative pain in relation to their request for opioids.

Guidelines for postoperative pain treatment are based on patients' pain scores. Patients with an intermediate Numeric Rating Scale (NRS) score of 5 or 6 may consider their pain as either bearable or unbearable, which makes it difficult to decide on pain treatment because guidelines advise professionals to treat pain at NRS > 4. Educating patients in using an NRS score for pain might improve adequate pain treatment. A quasi-randomized controlled trial was conducted in which 194 preoperative patients watched the educational film and 183 the control film. Pain scores were considered discordant when patients reported an NRS ≤ 4 and wanted additional opioids or when patients reported an NRS > 4 and did not want additional opioids. Beliefs, fear, and knowledge of pain; pain assessment; and pain treatment were measured by questionnaires. No significant differences in discordant pain scores between the groups were found: relative risk (RR) 0.73, confidence interval (CI) 0.47-1.15 at rest and RR 0.96, CI 0.72-1.28 at movement. Patients in the intervention group had lower NRS pain scores than patients in the control group. In the intervention group, patients had significantly more knowledge and lower barriers to pain management compared with the control group. We did not find a statistically significant reduction in discordant pain scores when comparing the intervention group with the control group. However, patients in the intervention group had significantly lower pain scores, lower barriers, and more knowledge of pain treatment than patients in the control group.

Monocyte hyporesponsiveness and Toll-like receptor expression profiles in coronary artery bypass grafting and its clinical implications for postoperative inflammatory response and pneumonia: An observational cohort study.

BACKGROUND: Cardiac surgery with cardiopulmonary bypass has a major impact on the congenital immune response, in which Toll-like receptors (TLRs) are the first line of defence. Decreased surface expression of TLRs and impaired monocyte responsiveness to TLR ligands occur following surgery. However, the clinical implications of this altered immune response are not clear. OBJECTIVES: To study cardiac surgery induced changes in perioperative TLR expression and monocyte responsiveness, and the association with postoperative inflammatory complications. DESIGN: A prospective cohort study. SETTING: Single university hospital, enrolment March to December 2007. PATIENTS: Eighty-four out of 92 patients who underwent coronary artery bypass grafting (CABG) were followed up until hospital discharge. MAIN OUTCOME MEASURES: We assessed in-vivo TLR-2 and TLR-4 expression and ex-vivo monocyte responsiveness to TLR-2 and TLR-4 ligands, measured by Pam3Cys and lipopolysaccharide (LPS)-induced interleukin (IL)-6 and IL-8, and tumour necrosis factor alpha (TNF-α) secretion until 24 h after surgery. Patients were followed to identify adverse inflammatory and infectious outcomes. RESULTS: Monocyte TLR expression decreased during CABG but returned to baseline after 24 h [linear mixed effects (LME) over time P < 0.0001]. Monocyte responsiveness changed significantly over time, with marked postoperative hyporesponsiveness (LME P < 0.0001). Decreased monocyte responsiveness to LPS was associated with monocyte TLR-4 expression (LME for IL-6 P = 0.04, IL-8 P = 0.002, TNF-α P = 0.05). Intraoperative decrease of monocyte TLR-2 expression was associated with postoperative systemic inflammatory response syndrome (SIRS) and pneumonia [odds ratio (OR) 2.06, 95% confidence interval (95% CI) 1.14 to 3.72], but the perioperative decrease of monocyte TLR-4 expression was not (OR 1.10, 95% CI 0.80 to 1.52). CONCLUSION: CABG surgery induced a decrease in in-vivo monocyte TLR expression and also in ex-vivo monocyte responsiveness, with which monocyte TLR-4 expression and monocyte LPS responsiveness seemed to be associated. Decreased TLR-2 expression was associated with the occurrence of SIRS and pneumonia, suggesting a role in the cause of postoperative inflammatory conditions. REGISTRATION: Clinicaltrials.gov identifier: NCT00356746.

The Relation Between Patients' NRS Pain Scores and Their Desire for Additional Opioids after Surgery.

BACKGROUND: Postoperative pain is commonly assessed through a numerical rating scale (NRS), an 11-point scale where 0 indicates no pain and 10 indicates the worst imaginable pain. Guidelines advise the administration of analgesics at NRS pain scores above 3 or 4. In clinical practice, not all patients with pain scores above the treatment threshold are willing to accept additional analgesic treatment, especially when opioids are offered. The objective of this study is to measure the relation between patients' NRS pain scores and their desire for additional opioids. METHODS: This cross-sectional study examined 1,084 patients in an academic hospital the day after surgery between January 2010 and June 2010. The day after surgery, patients were asked to score their pain and desire for opioids. Sensitivity, specificity, positive predictive value, and negative predictive value of the desire for opioids and the different NRS thresholds were calculated. RESULTS: Only when patients scored an 8 or higher on the NRS did the majority express a need for opioids. Many patients did not desire opioids, because they considered their pain tolerable, even at an NRS score above 4. CONCLUSIONS: With the current guidelines (ie, using pain scores above 3 or 4 for prescribing opioids), many patients could be overtreated. Therefore, scores generated by the NRS should be interpreted individually.

Impact of risk assessments on prophylactic antiemetic prescription and the incidence of postoperative nausea and vomiting: a cluster-randomized trial.

BACKGROUND: Clinical prediction models have been shown to have moderate sensitivity and specificity, yet their use will depend on implementation in clinical practice. The authors hypothesized that implementation of a prediction model for postoperative nausea and vomiting (PONV) would lower the PONV incidence by stimulating anesthesiologists to administer more "risk-tailored" prophylaxis to patients. METHODS: A single-center, cluster-randomized trial was performed in 12,032 elective surgical patients receiving anesthesia from 79 anesthesiologists. Anesthesiologists were randomized to either exposure or nonexposure to automated risk calculations for PONV (without patient-specific recommendations on prophylactic antiemetics). Anesthesiologists who treated less than 50 enrolled patients were excluded during the analysis to avoid too small clusters, yielding 11,613 patients and 57 anesthesiologists (intervention group: 5,471 and 31; care-as-usual group: 6,142 and 26). The 24-h incidence of PONV (primary outcome) and the number of prophylactic antiemetics administered per patient were studied for risk-dependent differences between allocation groups. RESULTS: There were no differences in PONV incidence between allocation groups (crude incidence intervention group 41%, care-as-usual group 43%; odds ratio, 0.97; 95% CI, 0.87-1.1; risk-dependent odds ratio, 0.92; 95% CI, 0.80-1.1). Nevertheless, intervention-group anesthesiologists administered more prophylactic antiemetics (rate ratio, 2.0; 95% CI, 1.6-2.4) and more risk-tailored than care-as-usual-group anesthesiologists (risk-dependent rate ratio, 1.6; 95% CI, 1.3-2.0). CONCLUSIONS: Implementation of a PONV prediction model did not reduce the PONV incidence despite increased antiemetic prescription in high-risk patients by anesthesiologists. Before implementing prediction models into clinical practice, implementation studies that include patient outcomes as an endpoint are needed.

Procedure-specific risk factor analysis for the development of severe postoperative pain.

BACKGROUND: Many studies have analyzed risk factors for the development of severe postoperative pain with contradictory results. To date, the association of risk factors with postoperative pain intensity among different surgical procedures has not been studied and compared. METHODS: The authors selected precisely defined surgical groups (at least 150 patients each) from prospectively collected perioperative data from 105 German hospitals (2004-2010). The association of age, sex, and preoperative chronic pain intensity with worst postoperative pain intensity was studied with multiple linear and logistic regression analyses. Pooled data of the selected surgeries were studied with random-effect analysis. RESULTS: Thirty surgical procedures with a total number of 22,963 patients were compared. In each surgical procedure, preoperative chronic pain intensity and younger age were associated with higher postoperative pain intensity. A linear decline of postoperative pain with age was found. Females reported more severe pain in 21 of 23 surgeries. Analysis of pooled surgical groups indicated that postoperative pain decreased by 0.28 points (95% CI, 0.26 to 0.31) on the numeric rating scale (0 to 10) per decade age increase and postoperative pain increased by 0.14 points (95% CI, 0.13 to 0.15) for each higher score on the preoperative chronic pain scale. Females reported 0.29 points (95% CI, 0.22 to 0.37) higher pain intensity. CONCLUSIONS: Independent of the type and extent of surgery, preoperative chronic pain and younger age were associated with higher postoperative pain. Females consistently reported slightly higher pain scores regardless of the type of surgery. The clinical significance of this small sex difference has to be analyzed in future studies.

The effect of proactive versus reactive treatment of hypotension on postoperative disability and outcome in surgical patients under anaesthesia (PRETREAT): clinical trial protocol and considerations.

Background: Intraoperative hypotension has been extensively studied for its association with adverse outcomes. However, small sample sizes and methodological issues limit the causal inference that can be drawn. Methods: In this multicentre, adaptive, randomised controlled trial, we will include 5000 adult inpatients scheduled for elective non-cardiac surgery under general or central neuraxial anaesthesia. Patients will be either randomly allocated to the intervention or care-as-usual group using computer-generated blocks of four, six, or eight, with an allocation ratio of 1:1. In the intervention arm patients will be divided into low-, intermediate-, and high-risk groups based on their likelihood to experience intraoperative hypotension, with resulting mean blood pressure targets of 70, 80, and 90 mm Hg, respectively. Anaesthesia teams will be provided with a clinical guideline on how to keep patients at their target blood pressure. During the first 6 months of the trial the intervention strategy will be evaluated and further revised in adaptation cycles of 3 weeks if necessary, to improve successful impact on the clinical process. The primary outcome is postoperative disability after 6 months measured with the World Health Organization Disability Assessment Score (WHODAS) 2.0 questionnaire. Ethics and dissemination: This study protocol has been approved by the Medical Ethics Committee of the University Medical Centre Utrecht (20-749) and all protocol amendments will be communicated to the Medical Ethics Committee. The study protocol is in adherence with the Declaration of Helsinki and the guideline of Good Clinical Practice. Dissemination plans include publication in a peer-reviewed journal. Clinical trial registration: The Dutch Trial Register, NL9391. Registered on 22 March 2021.

Prediction models for clustered data: comparison of a random intercept and standard regression model.

BACKGROUND: When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. METHODS: Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. RESULTS: The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. CONCLUSION: The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters.

Association of a Liberal Fasting Policy of Clear Fluids Before Surgery With Fasting Duration and Patient Well-being and Safety.

Importance: Current fasting guidelines for procedures under anesthesia are poorly implemented, leading to negative metabolic sequelae. Recent studies in children showed support of liberal clear fluid intake; adult physiology can support clear fluid intake, but implementation studies are lacking. Objective: To evaluate the successfulness of implementation of a liberal clear fluid policy with regard to fasting duration, well-being, and safety in adults scheduled for anesthesia. Design, Setting, and Participants: This was a quality improvement study conducted from January 2016 to July 2021 at a tertiary referral hospital in the Netherlands. Adults scheduled for nonemergency procedures under anesthesia were included in the study. Patients undergoing obstetrics procedures or those who were intubated preoperatively were excluded. Interventions: Stepwise introduction of a liberal fluid fasting policy, allowing for ingestion of clear fluids until arrival at the operating room. Main Outcomes and Measures: The primary outcome was change in fasting duration. Secondary outcomes were patient well-being, measured as preoperative thirst, amount of fluid ingested, postoperative nausea and vomiting (PONV), and administration of antiemetics. Safety was measured as incidence of regurgitation and aspiration (pneumonia). Results: Of the 76 451 patients (mean [SD] age, 56 [17] years; 39 530 male individuals [52%] 36 921) included in the study, 59 036 (78%) followed the standard policy, and 16 815 (22%) followed the liberal policy. Time series analysis showed an estimated fasting duration decrease of 3:07 hours (IQR, 1:36-7:22; P < .001) after implementation of the liberal policy. Postimplementation median (IQR) fasting duration was 1:20 (0:48-2:24) hours. The incidence of regurgitation changed from 18 (95% CI, 14-21) to 24 (95% CI, 17-32) in 10 000 patients, and the incidence of aspiration changed from 1.7 (95% CI, 0.6-2.7) to 2.4 (95% CI, 0.5-4.7) in 10 000 patients. In the liberal policy, thirst feelings decreased (37% [4982 of 8615] vs 46% [3373 of 7362]; P < .001). PONV incidence decreased from 10.6% (6339 of 59 636) to 9.4% (1587 of 16 815; P < .001) and antiemetic administration decreased from 11.0% (6538 of 59 636) to 9.5% (1592 of 16 815; P < .001). Conclusions and Relevance: Results of this quality improvement study suggest that a liberal fasting policy was associated with a clinically relevant reduction in fasting duration and improved patient well-being with regard to preoperative thirst and PONV. Although a slightly higher incidence of regurgitation could not be ruled out, wider implementation of such a policy may be advocated as results are still within the clinically accepted risks margins. Results suggest that surgical procedures in patients who drink clear fluids within 2 hours before anticipated anesthesia should not be postponed or canceled.

Continuous Data-Driven Monitoring in Critical Congenital Heart Disease: Clinical Deterioration Model Development.

BACKGROUND: Critical congenital heart disease (cCHD)-requiring cardiac intervention in the first year of life for survival-occurs globally in 2-3 of every 1000 live births. In the critical perioperative period, intensive multimodal monitoring at a pediatric intensive care unit (PICU) is warranted, as their organs-especially the brain-may be severely injured due to hemodynamic and respiratory events. These 24/7 clinical data streams yield large quantities of high-frequency data, which are challenging in terms of interpretation due to the varying and dynamic physiology innate to cCHD. Through advanced data science algorithms, these dynamic data can be condensed into comprehensible information, reducing the cognitive load on the medical team and providing data-driven monitoring support through automated detection of clinical deterioration, which may facilitate timely intervention. OBJECTIVE: This study aimed to develop a clinical deterioration detection algorithm for PICU patients with cCHD. METHODS: Retrospectively, synchronous per-second data of cerebral regional oxygen saturation (rSO2) and 4 vital parameters (respiratory rate, heart rate, oxygen saturation, and invasive mean blood pressure) in neonates with cCHD admitted to the University Medical Center Utrecht, the Netherlands, between 2002 and 2018 were extracted. Patients were stratified based on mean oxygen saturation during admission to account for physiological differences between acyanotic and cyanotic cCHD. Each subset was used to train our algorithm in classifying data as either stable, unstable, or sensor dysfunction. The algorithm was designed to detect combinations of parameters abnormal to the stratified subpopulation and significant deviations from the patient's unique baseline, which were further analyzed to distinguish clinical improvement from deterioration. Novel data were used for testing, visualized in detail, and internally validated by pediatric intensivists. RESULTS: A retrospective query yielded 4600 hours and 209 hours of per-second data in 78 and 10 neonates for, respectively, training and testing purposes. During testing, stable episodes occurred 153 times, of which 134 (88%) were correctly detected. Unstable episodes were correctly noted in 46 of 57 (81%) observed episodes. Twelve expert-confirmed unstable episodes were missed in testing. Time-percentual accuracy was 93% and 77% for, respectively, stable and unstable episodes. A total of 138 sensorial dysfunctions were detected, of which 130 (94%) were correct. CONCLUSIONS: In this proof-of-concept study, a clinical deterioration detection algorithm was developed and retrospectively evaluated to classify clinical stability and instability, achieving reasonable performance considering the heterogeneous population of neonates with cCHD. Combined analysis of baseline (ie, patient-specific) deviations and simultaneous parameter-shifting (ie, population-specific) proofs would be promising with respect to enhancing applicability to heterogeneous critically ill pediatric populations. After prospective validation, the current-and comparable-models may, in the future, be used in the automated detection of clinical deterioration and eventually provide data-driven monitoring support to the medical team, allowing for timely intervention.

Prognostic factors for multi-organ dysfunction in pediatric oncology patients admitted to the pediatric intensive care unit.

Background: Pediatric oncology patients who require admission to the pediatric intensive care unit (PICU) have worse outcomes compared to their non-cancer peers. Although multi-organ dysfunction (MOD) plays a pivotal role in PICU mortality and morbidity, risk factors for MOD have not yet been identified. We aimed to identify risk factors at PICU admission for new or progressive MOD (NPMOD) during the first week of PICU stay. Methods: This retrospective cohort study included all pediatric oncology patients aged 0 to 18 years admitted to the PICU between June 2018 and June 2021. We used the recently published PODIUM criteria for defining multi-organ dysfunction and estimated the association between covariates at PICU baseline and the outcome NPMOD using a multivariable logistic regression model, with PICU admission as unit of study. To study the predictive performance, the model was internally validated by using bootstrap. Results: A total of 761 PICU admissions of 571 patients were included. NPMOD was present in 154 PICU admissions (20%). Patients with NPMOD had a high mortality compared to patients without NPMOD, 14% and 1.0% respectively. Hemato-oncological diagnosis, number of failing organs and unplanned admission were independent risk factors for NPMOD. The prognostic model had an overall good discrimination and calibration. Conclusion: The risk factors at PICU admission for NPMOD may help to identify patients who may benefit from closer monitoring and early interventions. When applying the PODIUM criteria, we found some opportunities for fine-tuning these criteria for pediatric oncology patients, that need to be validated in future studies.

Automated feedback modestly improves perioperative treatment adherence of postoperative nausea and vomiting.

STUDY OBJECTIVE: Extensive evidence demonstrates that medical record modernization and a vast amount of available data have not overcome the gap between recommended and delivered care. This study aimed to evaluate the use of clinical decision support (CDS) in conjunction with feedback (post-hoc reporting) to improve PONV medication administration compliance and postoperative nausea and vomiting (PONV) outcomes. DESIGN: Single center, prospective observational study between January 1, 2015, and June 30, 2017. SETTING: Perioperative care at a university-affiliated tertiary care center. PATIENTS: 57,401 adult patients who received general anesthesia in a non-emergency setting. INTERVENTION: A multi-phased intervention that consisted of post-hoc reporting for individual providers by email about PONV occurrences in their patients, followed by directive CDS through preoperative daily case emails that provided therapeutic PONV prophylaxis recommendations based on patients' PONV risk scores. MEASUREMENT: Compliance with PONV medication recommendations, as well as hospital rates of PONV were measured. MAIN RESULT: Over the study period, there was a 5.5% (95% CI, 4.2% to 6.4%; p < 0.001) improvement in the compliance of PONV medication administration along with an 8.7% (95% CI, 7.1% to 10.2%, p < 0.001) reduction in PONV rescue medication administration in the PACU. However, there was no statistically or clinically significant reduction in the prevalence of PONV in the PACU. The prevalence of PONV rescue medication administration decreased during the Intervention Rollout Period (odds ratio 0.95 [per month]; 95% CI, 0.91 to 0.99; p = 0.017), and during the Feedback with CDS Recommendation Period (odds ratio, 0.96 [per month]; 95% CI, 0.94 to 0.99; p = 0.013). CONCLUSION: PONV medication administration compliance modestly improves with CDS in conjunction with post-hoc reporting; however, no improvement in PACU rates of PONV occurred.