Assessment of the CLOT (children's likelihood of thrombosis) real-time risk prediction model of hospital-associated venous thromboembolism in children with congenital heart disease.

BACKGROUND: Children with congenital heart disease (CHD) are at high risk for hospital-associated venous thromboembolism (HA-VTE). The children's likelihood of thrombosis (CLOT) trial validated a real-time predictive model for HA-VTE using data extracted from the EHR for pediatric inpatients. We tested the hypothesis that addition of CHD specific data would improve model prediction in the CHD population. METHODS: Model performance in CHD patients from 2010 to 2022, was assessed using 3 iterations of the CLOT model: 1) the original CLOT model, 2) the original model refit using only data from the CHD cohort, and 3) the model updated with the addition of cardiopulmonary bypass time, STAT Mortality Category, height, and weight as covariates. The discrimination of the three models was quantified and compared using AUROC. RESULTS: Our CHD cohort included 1457 patient encounters (median 2.0 IQR [0.5-5.2] years-old). HA-VTE was present in 5% of our CHD cohort versus 1% in the general pediatric population. Several features from the original model were associated with thrombosis in the CHD cohort including younger age, thrombosis history, infectious disease consultation, and EHR coding of a central venous line. Lower height and weight were associated with thrombosis. HA-VTE rate was 12% (18/149) amongst those with STAT Category 4-5 operation versus 4% (49/1256) with STAT Category 1-3 operation (P < .001). Longer cardiopulmonary bypass time (124 [92-205] vs. 94 [65-136] minutes, P < .001) was associated with thrombosis. The AUROC for the original (0.80 95% CI [0.75-0.85]), refit (0.85 [0.81-0.89]), and updated (0.86 [0.81-0.90]) models demonstrated excellent discriminatory ability within the CHD cohort. CONCLUSION: The automated approach with EHR data extraction makes the applicability of such models appealing for ease of clinical use. The addition of cardiac specific features improved model discrimination; however, this benefit was marginal compared to refitting the original model to the CHD cohort. This suggests strong predictive generalized models, such as CLOT, can be optimized for cohort subsets without additional data extraction, thus reducing cost of model development and deployment.

Balanced Crystalloids versus Saline in Critically Ill Adults.

BACKGROUND: Both balanced crystalloids and saline are used for intravenous fluid administration in critically ill adults, but it is not known which results in better clinical outcomes. METHODS: In a pragmatic, cluster-randomized, multiple-crossover trial conducted in five intensive care units at an academic center, we assigned 15,802 adults to receive saline (0.9% sodium chloride) or balanced crystalloids (lactated Ringer's solution or Plasma-Lyte A) according to the randomization of the unit to which they were admitted. The primary outcome was a major adverse kidney event within 30 days - a composite of death from any cause, new renal-replacement therapy, or persistent renal dysfunction (defined as an elevation of the creatinine level to ≥200% of baseline) - all censored at hospital discharge or 30 days, whichever occurred first. RESULTS: Among the 7942 patients in the balanced-crystalloids group, 1139 (14.3%) had a major adverse kidney event, as compared with 1211 of 7860 patients (15.4%) in the saline group (marginal odds ratio, 0.91; 95% confidence interval [CI], 0.84 to 0.99; conditional odds ratio, 0.90; 95% CI, 0.82 to 0.99; P=0.04). In-hospital mortality at 30 days was 10.3% in the balanced-crystalloids group and 11.1% in the saline group (P=0.06). The incidence of new renal-replacement therapy was 2.5% and 2.9%, respectively (P=0.08), and the incidence of persistent renal dysfunction was 6.4% and 6.6%, respectively (P=0.60). CONCLUSIONS: Among critically ill adults, the use of balanced crystalloids for intravenous fluid administration resulted in a lower rate of the composite outcome of death from any cause, new renal-replacement therapy, or persistent renal dysfunction than the use of saline. (Funded by the Vanderbilt Institute for Clinical and Translational Research and others; SMART-MED and SMART-SURG ClinicalTrials.gov numbers, NCT02444988 and NCT02547779 .).

Balanced Crystalloids versus Saline in Noncritically Ill Adults.

BACKGROUND: Comparative clinical effects of balanced crystalloids and saline are uncertain, particularly in noncritically ill patients cared for outside an intensive care unit (ICU). METHODS: We conducted a single-center, pragmatic, multiple-crossover trial comparing balanced crystalloids (lactated Ringer's solution or Plasma-Lyte A) with saline among adults who were treated with intravenous crystalloids in the emergency department and were subsequently hospitalized outside an ICU. The type of crystalloid that was administered in the emergency department was assigned to each patient on the basis of calendar month, with the entire emergency department crossing over between balanced crystalloids and saline monthly during the 16-month trial. The primary outcome was hospital-free days (days alive after discharge before day 28). Secondary outcomes included major adverse kidney events within 30 days - a composite of death from any cause, new renal-replacement therapy, or persistent renal dysfunction (defined as an elevation of the creatinine level to ≥200% of baseline) - all censored at hospital discharge or 30 days, whichever occurred first. RESULTS: A total of 13,347 patients were enrolled, with a median crystalloid volume administered in the emergency department of 1079 ml and 88.3% of the patients exclusively receiving the assigned crystalloid. The number of hospital-free days did not differ between the balanced-crystalloids and saline groups (median, 25 days in each group; adjusted odds ratio with balanced crystalloids, 0.98; 95% confidence interval [CI], 0.92 to 1.04; P=0.41). Balanced crystalloids resulted in a lower incidence of major adverse kidney events within 30 days than saline (4.7% vs. 5.6%; adjusted odds ratio, 0.82; 95% CI, 0.70 to 0.95; P=0.01). CONCLUSIONS: Among noncritically ill adults treated with intravenous fluids in the emergency department, there was no difference in hospital-free days between treatment with balanced crystalloids and treatment with saline. (Funded by the Vanderbilt Institute for Clinical and Translational Research and others; SALT-ED ClinicalTrials.gov number, NCT02614040 .).

The first 1000 symptomatic pediatric SARS-CoV-2 infections in an integrated health care system: a prospective cohort study.

BACKGROUND: The spectrum of illness and predictors of severity among children with SARS-CoV-2 infection are incompletely understood. METHODS: Active surveillance was performed for SARS-CoV-2 by polymerase chain reaction among symptomatic pediatric patients in a quaternary care academic hospital laboratory beginning March 12, 2020. We obtained sociodemographic and clinical data 5 (+/-3) and 30 days after diagnosis via phone follow-up and medical record review. Logistic regression was used to assess predictors of hospitalization. RESULTS: The first 1000 symptomatic pediatric patients were diagnosed in our institution between March 13, 2020 and September 28, 2020. Cough (52 %), headache (43 %), and sore throat (36 %) were the most common symptoms. Forty-one (4 %) were hospitalized; 8 required ICU admission, and 2 required mechanical ventilation (< 1 %). One patient developed multisystem inflammatory syndrome in children; one death was possibly associated with SARS-CoV-2 infection. Symptom resolution occurred by follow-up day 5 in 398/892 (45 %) patients and by day 30 in 443/471 (94 %) patients. Pre-existing medical condition (OR 7.7; 95 % CI 3.9-16.0), dyspnea (OR 6.8; 95 % CI 3.2-14.1), Black race or Hispanic ethnicity (OR 2.7; 95 % CI 1.3-5.5), and vomiting (OR 5.4; 95 % CI 1.2-20.6) were the strongest predictors of hospitalization. The model displayed excellent discriminative ability (AUC = 0.82, 95 % CI 0.76-0.88, Brier score = 0.03). CONCLUSIONS: In 1000 pediatric patients with systematic follow-up, most SARS-CoV-2 infections were mild, brief, and rarely required hospitalization. Pediatric predictors of hospitalization included comorbid conditions, Black race, Hispanic ethnicity, dyspnea and vomiting and were distinct from those reported among adults.

Impact of a Follow-up Telephone Call Program on 30-Day Readmissions (FUTR-30): A Pragmatic Randomized Controlled Real-world Effectiveness Trial.

BACKGROUND: Telephone call programs are a common intervention used to improve patients' transition to outpatient care after hospital discharge. OBJECTIVE: To examine the impact of a follow-up telephone call program as a readmission reduction initiative. RESEARCH DESIGN: Pragmatic randomized controlled real-world effectiveness trial. SUBJECTS: We enrolled and randomized all patients discharged home from a hospital general medicine service to a follow-up telephone call program or usual care discharge. Patients discharged against medical advice were excluded. The intervention was a hospital program, delivering a semistructured follow-up telephone call from a nurse within 3-7 days of discharge, designed to assess understanding and provide education, and assistance to support discharge plan implementation. MEASURES: Our primary endpoint was hospital inpatient readmission within 30 days identified by the electronic health record. Secondary endpoints included observation readmission, emergency department revisit, and mortality within 30 days, and patient experience ratings. RESULTS: All 3054 patients discharged home were enrolled and randomized to the telephone call program (n=1534) or usual care discharge (n=1520). Using a prespecified intention-to-treat analysis, we found no evidence supporting differences in 30-day inpatient readmissions [14.9% vs. 15.3%; difference -0.4 (95% confidence interval, 95% CI), -2.9 to 2.1; P=0.76], observation readmissions [3.8% vs. 3.6%; difference 0.2 (95% CI, -1.1 to 1.6); P=0.74], emergency department revisits [6.1% vs. 5.4%; difference 0.7 (95% CI, -1.0 to 2.3); P=0.43], or mortality [4.4% vs. 4.9%; difference -0.5 (95% CI, -2.0 to 1.0); P=0.51] between telephone call and usual care groups. CONCLUSIONS: We found no evidence of an impact on 30-day readmissions or mortality due to the postdischarge telephone call program.

Acute kidney injury risk-based screening in pediatric inpatients: a pragmatic randomized trial.

BACKGROUND: Pediatric acute kidney injury (AKI) is common and associated with increased morbidity, mortality, and length of stay. We performed a pragmatic randomized trial testing the hypothesis that AKI risk alerts increase AKI screening. METHODS: All intensive care and ward admissions of children aged 28 days through 21 years without chronic kidney disease from 12/6/2016 to 11/1/2017 were included. The intervention alert displayed if calculated AKI risk was > 50% and no serum creatinine (SCr) was ordered within 24 h. The primary outcome was SCr testing within 48 h of AKI risk > 50%. RESULTS: Among intensive care admissions, 973/1909 (51%) were randomized to the intervention. Among those at risk, more SCr tests were ordered for the intervention group than for controls (418/606, 69% vs. 361/597, 60%, p = 0.002). AKI incidence and severity were the same in intervention and control groups. Among ward admissions, 5492/10997 (50%) were randomized to the intervention, and there were no differences between groups in SCr testing, AKI incidence, or severity of AKI. CONCLUSIONS: Alerts based on real-time prediction of AKI risk increased screening rates in intensive care but not pediatric ward settings. Pragmatic clinical trials provide the opportunity to assess clinical decision support and potentially eliminate ineffective alerts.

Balanced Crystalloids versus Saline in Sepsis. A Secondary Analysis of the SMART Clinical Trial.

Rationale: Administration of intravenous crystalloid solutions is a fundamental therapy for sepsis, but the effect of crystalloid composition on patient outcomes remains unknown.Objectives: To compare the effect of balanced crystalloids versus saline on 30-day in-hospital mortality among critically ill adults with sepsis.Methods: Secondary analysis of patients from SMART (Isotonic Solutions and Major Adverse Renal Events Trial) admitted to the medical ICU with an International Classification of Diseases, 10th Edition, Clinical Modification System code for sepsis, using multivariable regression to control for potential confounders.Measurements and Main Results: Of 15,802 patients enrolled in SMART, 1,641 patients were admitted to the medical ICU with a diagnosis of sepsis. A total of 217 patients (26.3%) in the balanced crystalloids group experienced 30-day in-hospital morality compared with 255 patients (31.2%) in the saline group (adjusted odds ratio [aOR], 0.74; 95% confidence interval [CI], 0.59-0.93; P = 0.01). Patients in the balanced group experienced a lower incidence of major adverse kidney events within 30 days (35.4% vs. 40.1%; aOR, 0.78; 95% CI, 0.63-0.97) and a greater number of vasopressor-free days (20 ± 12 vs. 19 ± 13; aOR, 1.25; 95% CI, 1.02-1.54) and renal replacement therapy-free days (20 ± 12 vs. 19 ± 13; aOR, 1.35; 95% CI, 1.08-1.69) compared with the saline group.Conclusions: Among patients with sepsis in a large randomized trial, use of balanced crystalloids was associated with a lower 30-day in-hospital mortality compared with use of saline.Clinical trial registered with www.clinicaltrials.gov (NCT02444988).

Randomized Clinical Trial of an ICU Recovery Pilot Program for Survivors of Critical Illness.

OBJECTIVES: To examine the effect of an interdisciplinary ICU recovery program on process measures and clinical outcomes. DESIGN: A prospective, single-center, randomized pilot trial. SETTING: Academic, tertiary-care medical center. PATIENTS: Adult patients admitted to the medical ICU for at least 48 hours with a predicted risk of 30-day same-hospital readmission of at least 15%. INTERVENTIONS: Patients randomized to the ICU recovery program group were offered a structured 10-intervention program, including an inpatient visit by a nurse practitioner, an informational pamphlet, a 24 hours a day, 7 days a week phone number for the recovery team, and an outpatient ICU recovery clinic visit with a critical care physician, nurse practitioner, pharmacist, psychologist, and case manager. For patients randomized to the usual care group, all aspects of care were determined by treating clinicians. MEASUREMENTS AND MAIN RESULTS: Among the primary analysis of enrolled patients who survived to hospital discharge, patients randomized to the ICU recovery program (n = 111) and usual care (n = 121) were similar at baseline. Patients in the ICU recovery program group received a median of two interventions compared with one intervention in the usual care group (p < 0.001). A total of 16 patients (14.4%) in the ICU recovery program group and 26 patients (21.5%) in the usual care group were readmitted to the study hospital within 30 days of discharge (p = 0.16). For these patients, the median time to readmission was 21.5 days (interquartile range, 11.5-26.2 d) in the ICU recovery program group and 7 days (interquartile range, 4-21.2 d) in the usual care group (p = 0.03). Four patients (3.6%) in the ICU recovery program and 14 patients (11.6%) in the usual care group were readmitted within 7 days of hospital discharge (p = 0.02). The composite outcome of death or readmission within 30 days of hospital discharge occurred in 20 patients (18%) in the ICU recovery program group and 36 patients (29.8%) in usual care group (p = 0.04). CONCLUSIONS: This randomized pilot trial found that a multidisciplinary ICU recovery program could deliver more interventions for post ICU recovery than usual care. The finding of longer time-to-readmission with an ICU recovery program should be examined in future trials.

Putting the National Diabetes Prevention Program to Work: Predictors of Achieving Weight-Loss Goals in an Employee Population.

INTRODUCTION: Differences in eligibility criteria and intervention characteristics have limited the generalizability of findings from studies of worksite translations of the National Diabetes Prevention Program (DPP). The objective of our study was to identify factors associated with achievement of the DPP's 5% weight-loss goal in the Vanderbilt University Medical Center (VUMC) Faculty and Staff Health and Wellness DPP from 2014 to 2017. METHODS: We analyzed data from a DPP worksite translation that adhered to national standards for program quality and intervention fidelity. We compared baseline characteristics and program metrics for participants who did and did not achieve the program's 5% weight-loss goal, and we developed a multivariable logistic regression model to identify independent predictors of achieving this goal. RESULTS: Of the 165 employees enrolled in the DPP from 2014 to 2017, 43.6% (n = 72) met the 5% weight-loss goal. Mean (standard deviation) percentage weight loss for the program was 5.2% (6.0%), or 4.8 (6.0) kg. The median (interquartile range) body mass index at baseline was lower among participants who achieved the 5% weight-loss goal than among those who did not (31.6 [29.4-37.4] vs 34.7 [31.5-39.2], P = .009), and participants who achieved the goal reported more physical activity minutes per week (166.0 [135.2-223.0] min vs 128.5 [83.2-169.8] min, P < .001). Session attendance was greater for participants achieving the 5% weight-loss goal (23 [21-25]) sessions vs 18 [12-21] sessions, P < .001). In the adjusted analysis, physical activity and session attendance remained significant predictors of achieving the 5% weight-loss goal. CONCLUSION: Session attendance and physical activity independently predicted achievement of the 5% weight-loss goal in this worksite translation of the DPP. Strategies designed to improve these metrics may increase DPP success rates.

Balanced Crystalloids versus Saline in the Intensive Care Unit. The SALT Randomized Trial.

RATIONALE: Saline is the intravenous fluid most commonly administered to critically ill adults, but it may be associated with acute kidney injury and death. Whether use of balanced crystalloids rather than saline affects patient outcomes remains unknown. OBJECTIVES: To pilot a cluster-randomized, multiple-crossover trial using software tools within the electronic health record to compare saline to balanced crystalloids. METHODS: This was a cluster-randomized, multiple-crossover trial among 974 adults admitted to a tertiary medical intensive care unit from February 3, 2015 to May 31, 2015. The intravenous crystalloid used in the unit alternated monthly between saline (0.9% sodium chloride) and balanced crystalloids (lactated Ringer's solution or Plasma-Lyte A). Enrollment, fluid delivery, and data collection were performed using software tools within the electronic health record. The primary outcome was the difference between study groups in the proportion of isotonic crystalloid administered that was saline. The secondary outcome was major adverse kidney events within 30 days (MAKE30), a composite of death, dialysis, or persistent renal dysfunction. MEASUREMENTS AND MAIN RESULTS: Patients assigned to saline (n = 454) and balanced crystalloids (n = 520) were similar at baseline and received similar volumes of crystalloid by 30 days (median [interquartile range]: 1,424 ml [500-3,377] vs. 1,617 ml [500-3,628]; P = 0.40). Saline made up a larger proportion of the isotonic crystalloid given in the saline group than in the balanced crystalloid group (91% vs. 21%; P < 0.001). MAKE30 did not differ between groups (24.7% vs. 24.6%; P = 0.98). CONCLUSIONS: An electronic health record-embedded, cluster-randomized, multiple-crossover trial comparing saline with balanced crystalloids can produce well-balanced study groups and separation in crystalloid receipt. Clinical trial registered with www.clinicaltrials.gov (NCT 02345486).

Electronic health record-based predictive models for acute kidney injury screening in pediatric inpatients.

BackgroundAcute kidney injury (AKI) is common in pediatric inpatients and is associated with increased morbidity, mortality, and length of stay. Its early identification can reduce severity.MethodsTo create and validate an electronic health record (EHR)-based AKI screening tool, we generated temporally distinct development and validation cohorts using retrospective data from our tertiary care children's hospital, including children aged 28 days through 21 years with sufficient serum creatinine measurements to determine AKI status. AKI was defined as 1.5-fold or 0.3 mg/dl increase in serum creatinine. Age, medication exposures, platelet count, red blood cell distribution width, serum phosphorus, serum transaminases, hypotension (ICU only), and pH (ICU only) were included in AKI risk prediction models.ResultsFor ICU patients, 791/1,332 (59%) of the development cohort and 470/866 (54%) of the validation cohort had AKI. In external validation, the ICU prediction model had a c-statistic=0.74 (95% confidence interval 0.71-0.77). For non-ICU patients, 722/2,337 (31%) of the development cohort and 469/1,474 (32%) of the validation cohort had AKI, and the prediction model had a c-statistic=0.69 (95% confidence interval 0.66-0.72).ConclusionsAKI screening can be performed using EHR data. The AKI screening tool can be incorporated into EHR systems to identify high-risk patients without serum creatinine data, enabling targeted laboratory testing, early AKI identification, and modification of care.

Emergency Preparedness in the Workplace: The Flulapalooza Model for Mass Vaccination.

OBJECTIVES: To explore whether an emergency preparedness structure is a feasible, efficient, and sustainable way for health care organizations to manage mass vaccination events. METHODS: We used the Hospital Incident Command System to conduct a 1-day annual mass influenza vaccination event at Vanderbilt University Medical Center over 5 successive years (2011-2015). Using continuous quality improvement principles, we assessed whether changes in layout, supply management, staffing, and documentation systems improved efficiency. RESULTS: A total of 66 591 influenza vaccines were administered at 5 annual Flulapalooza events; 13 318 vaccines per event on average. Changes to the physical layout, staffing mix, and documentation processes improved vaccination efficiency 74%, from approximately 38 to 67 vaccines per hour per vaccinator, while reducing overall staffing needs by 38%. An unexpected finding was the role of social media in facilitating active engagement. CONCLUSIONS: Health care organizations can use a closed point-of-dispensing model and Hospital Incident Command System to conduct mass vaccination events, and can adopt the "Flulapalooza method" as a best practice model to enhance efficiency.

Acute Kidney Injury Incidence in Noncritically Ill Hospitalized Children, Adolescents, and Young Adults: A Retrospective Observational Study.

BACKGROUND: Acute kidney injury (AKI) has been characterized in high-risk pediatric hospital inpatients, in whom AKI is frequent and associated with increased mortality, morbidity, and length of stay. The incidence of AKI among patients not requiring intensive care is unknown. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: 13,914 noncritical admissions during 2011 and 2012 at our tertiary referral pediatric hospital were evaluated. Patients younger than 28 days or older than 21 years of age or with chronic kidney disease (CKD) were excluded. Admissions with 2 or more serum creatinine measurements were evaluated. FACTORS: Demographic features, laboratory measurements, medication exposures, and length of stay. OUTCOME: AKI defined as increased serum creatinine level in accordance with KDIGO (Kidney Disease: Improving Global Outcomes) criteria. Based on time of admission, time interval requirements were met in 97% of cases, but KDIGO time window criteria were not strictly enforced to allow implementation using clinically obtained data. RESULTS: 2 or more creatinine measurements (one baseline before or during admission and a second during admission) in 2,374 of 13,914 (17%) patients allowed for AKI evaluation. A serum creatinine difference ≥0.3mg/dL or ≥1.5 times baseline was seen in 722 of 2,374 (30%) patients. A minimum of 5% of all noncritical inpatients without CKD in pediatric wards have an episode of AKI during routine hospital admission. LIMITATIONS: Urine output, glomerular filtration rate, and time interval criteria for AKI were not applied secondary to study design and available data. The evaluated cohort was restricted to patients with 2 or more clinically obtained serum creatinine measurements, and baseline creatinine level may have been measured after the AKI episode. CONCLUSIONS: AKI occurs in at least 5% of all noncritically ill hospitalized children, adolescents, and young adults without known CKD. Physicians should increase their awareness of AKI and improve surveillance strategies with serum creatinine measurements in this population so that exacerbating factors such as nephrotoxic medication exposures may be modified as indicated.

Identification of Major Adverse Kidney Events Within the Electronic Health Record.

Acute kidney injury is common among critically ill adults and is associated with increased mortality and morbidity. The Major Adverse Kidney Events by 30 days (MAKE30) composite of death, new renal replacement therapy, or persistent renal dysfunction is recommended as a patient-centered outcome for pragmatic trials involving acute kidney injury. Accurate electronic detection of the MAKE30 endpoint using data within the electronic health record (EHR) could facilitate the use of the EHR in large-scale kidney injury research. In an observational study using prospectively collected data from 200 admissions to a single medical intensive care unit, we tested the performance of electronically-extracted data in identifying the MAKE30 composite compared to the reference standard of two-physician manual chart review. The incidence of MAKE30 on manual-review was 16 %, which included 8.5 % for in-hospital mortality, 3.5 % for new renal replacement therapy, and 8.5 % for persistent renal dysfunction. There was strong agreement between the electronic and manual assessment of MAKE30 (98.5 % agreement [95 % CI 96.5-100.0 %]; kappa 0.95 [95 % CI 0.87-1.00]; P < 0.001), with only three patients misclassified by electronic assessment. Performance of the electronic MAKE30 assessment was similar among patients with and without CKD and with and without a measured serum creatinine in the 12 months prior to hospital admission. In summary, accurately identifying the MAKE30 composite outcome using EHR data collected as a part of routine care appears feasible.

Chlorhexidine bathing and health care-associated infections: a randomized clinical trial.

IMPORTANCE: Daily bathing of critically ill patients with the broad-spectrum, topical antimicrobial agent chlorhexidine is widely performed and may reduce health care-associated infections. OBJECTIVE: To determine if daily bathing of critically ill patients with chlorhexidine decreases the incidence of health care-associated infections. DESIGN, SETTING, AND PARTICIPANTS: A pragmatic cluster randomized, crossover study of 9340 patients admitted to 5 adult intensive care units of a tertiary medical center in Nashville, Tennessee, from July 2012 through July 2013. INTERVENTIONS: Units performed once-daily bathing of all patients with disposable cloths impregnated with 2% chlorhexidine or nonantimicrobial cloths as a control. Bathing treatments were performed for a 10-week period followed by a 2-week washout period during which patients were bathed with nonantimicrobial disposable cloths, before crossover to the alternate bathing treatment for 10 weeks. Each unit crossed over between bathing assignments 3 times during the study. MAIN OUTCOMES AND MEASURES: The primary prespecified outcome was a composite of central line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), ventilator-associated pneumonia (VAP), and Clostridium difficile infections. Secondary outcomes included rates of clinical cultures that tested positive for multidrug-resistant organisms, blood culture contamination, health care-associated bloodstream infections, and rates of the primary outcome by ICU. RESULTS: During the chlorhexidine bathing period, 55 infections occurred: 4 CLABSI, 21 CAUTI, 17 VAP, and 13 C difficile. During the control bathing period, 60 infections occurred: 4 CLABSI, 32 CAUTI, 8 VAP, and 16 C difficile. The primary outcome rate was 2.86 per 1000 patient-days during the chlorhexidine and 2.90 per 1000 patient-days during the control bathing periods (rate difference, -0.04; 95% CI, -1.10 to 1.01; P = .95). After adjusting for baseline variables, no difference between groups in the rate of the primary outcome was detected. Chlorhexidine bathing did not change rates of infection-related secondary outcomes including hospital-acquired bloodstream infections, blood culture contamination, or clinical cultures yielding multidrug-resistant organisms. In a prespecified subgroup analysis, no difference in the primary outcome was detected in any individual intensive care unit. CONCLUSION AND RELEVANCE: In this pragmatic trial, daily bathing with chlorhexidine did not reduce the incidence of health care-associated infections including CLABSIs, CAUTIs, VAP, or C difficile. These findings do not support daily bathing of critically ill patients with chlorhexidine. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT02033187.

A real-time prognostic model for venous thromboembolic events among hospitalized adults.

Background: Hospital-acquired venous thromboembolism (HA-VTE) is a leading cause of morbidity and mortality among hospitalized adults. Guidelines recommend use of a risk-prediction model to estimate HA-VTE risk for individual patients. Extant models do not perform well for broad patient populations and are not conducive to automation in clinical practice. Objectives: To develop an automated, real-time prognostic model for venous thromboembolism during hospitalization among all adult inpatients using readily available data from the electronic health record. Methods: The derivation cohort included inpatient hospitalizations ("encounters") for patients ≥16 years old at Vanderbilt University Medical Center between 2018 and 2020 (n = 132,330). HA-VTE events were identified using International Classification of Diseases, 10th Revision, codes. The prognostic model was developed using least absolute shrinkage and selection operator regression. Temporal external validation was performed in a validation cohort of encounters between 2021 and 2022 (n = 62,546). Prediction performance was assessed by discrimination accuracy (C statistic) and calibration (integrated calibration index). Results: There were 1187 HA-VTEs in the derivation cohort (9.0 per 1000 encounters) and 864 in the validation cohort (13.8 per 1000 encounters). The prognostic model included 25 variables, with placement of a central line among the most important predictors. Prediction performance of the model was excellent (C statistic, 0.891; 95% CI, 0.882-0.900; integrated calibration index, 0.001). The model performed similarly well across subgroups of patients defined by age, sex, race, and type of admission. Conclusion: This fully automated prognostic model uses readily available data from the electronic health record, exhibits superior prediction performance compared with existing models, and generates granular risk stratification in the form of a predicted probability of HA-VTE for each patient.

Development and Validation of an Automated, Real-Time Predictive Model for Postpartum Hemorrhage.

OBJECTIVE: To develop and validate a predictive model for postpartum hemorrhage that can be deployed in clinical care using automated, real-time electronic health record (EHR) data and to compare performance of the model with a nationally published risk prediction tool. METHODS: A multivariable logistic regression model was developed from retrospective EHR data from 21,108 patients delivering at a quaternary medical center between January 1, 2018, and April 30, 2022. Deliveries were divided into derivation and validation sets based on an 80/20 split by date of delivery. Postpartum hemorrhage was defined as blood loss of 1,000 mL or more in addition to postpartum transfusion of 1 or more units of packed red blood cells. Model performance was evaluated by the area under the receiver operating characteristic curve (AUC) and was compared with a postpartum hemorrhage risk assessment tool published by the CMQCC (California Maternal Quality Care Collaborative). The model was then programmed into the EHR and again validated with prospectively collected data from 928 patients between November 7, 2023, and January 31, 2024. RESULTS: Postpartum hemorrhage occurred in 235 of 16,862 patients (1.4%) in the derivation cohort. The predictive model included 21 risk factors and demonstrated an AUC of 0.81 (95% CI, 0.79-0.84) and calibration slope of 1.0 (Brier score 0.013). During external temporal validation, the model maintained discrimination (AUC 0.80, 95% CI, 0.72-0.84) and calibration (calibration slope 0.95, Brier score 0.014). This was superior to the CMQCC tool (AUC 0.69 [95% CI, 0.67-0.70], P <.001). The model maintained performance in prospective, automated data collected with the predictive model in real time (AUC 0.82 [95% CI, 0.73-0.91]). CONCLUSION: We created and temporally validated a postpartum hemorrhage prediction model, demonstrated its superior performance over a commonly used risk prediction tool, successfully coded the model into the EHR, and prospectively validated the model using risk factor data collected in real time. Future work should evaluate external generalizability and effects on patient outcomes; to facilitate this work, we have included the model coefficients and examples of EHR integration in the article.

Implementable Prediction of Pressure Injuries in Hospitalized Adults: Model Development and Validation.

Background: Numerous pressure injury prediction models have been developed using electronic health record data, yet hospital-acquired pressure injuries (HAPIs) are increasing, which demonstrates the critical challenge of implementing these models in routine care. Objective: To help bridge the gap between development and implementation, we sought to create a model that was feasible, broadly applicable, dynamic, actionable, and rigorously validated and then compare its performance to usual care (ie, the Braden scale). Methods: We extracted electronic health record data from 197,991 adult hospital admissions with 51 candidate features. For risk prediction and feature selection, we used logistic regression with a least absolute shrinkage and selection operator (LASSO) approach. To compare the model with usual care, we used the area under the receiver operating curve (AUC), Brier score, slope, intercept, and integrated calibration index. The model was validated using a temporally staggered cohort. Results: A total of 5458 HAPIs were identified between January 2018 and July 2022. We determined 22 features were necessary to achieve a parsimonious and highly accurate model. The top 5 features included tracheostomy, edema, central line, first albumin measure, and age. Our model achieved higher discrimination than the Braden scale (AUC 0.897, 95% CI 0.893-0.901 vs AUC 0.798, 95% CI 0.791-0.803). Conclusions: We developed and validated an accurate prediction model for HAPIs that surpassed the standard-of-care risk assessment and fulfilled necessary elements for implementation. Future work includes a pragmatic randomized trial to assess whether our model improves patient outcomes.

External validation of a predictive model for reintubation after cardiac surgery: A retrospective, observational study.

STUDY OBJECTIVE: Explore validation of a model to predict patients' risk of failing extubation, to help providers make informed, data-driven decisions regarding the optimal timing of extubation. DESIGN: We performed temporal, geographic, and domain validations of a model for the risk of reintubation after cardiac surgery by assessing its performance on data sets from three academic medical centers, with temporal validation using data from the institution where the model was developed. SETTING: Three academic medical centers in the United States. PATIENTS: Adult patients arriving in the cardiac intensive care unit with an endotracheal tube in place after cardiac surgery. INTERVENTIONS: Receiver operating characteristic (ROC) curves and concordance statistics were used as measures of discriminative ability, and calibration curves and Brier scores were used to assess the model's predictive ability. MEASUREMENTS: Temporal validation was performed in 1642 patients with a reintubation rate of 4.8%, with the model demonstrating strong discrimination (optimism-corrected c-statistic 0.77) and low predictive error (Brier score 0.044) but poor model precision and recall (Optimal F1 score 0.29). Combined domain and geographic validation were performed in 2041 patients with a reintubation rate of 1.5%. The model displayed solid discriminative ability (optimism-corrected c-statistic = 0.73) and low predictive error (Brier score = 0.0149) but low precision and recall (Optimal F1 score = 0.13). Geographic validation was performed in 2489 patients with a reintubation rate of 1.6%, with the model displaying good discrimination (optimism-corrected c-statistic = 0.71) and predictive error (Brier score = 0.0152) but poor precision and recall (Optimal F1 score = 0.13). MAIN RESULTS: The reintubation model displayed strong discriminative ability and low predictive error within each validation cohort. CONCLUSIONS: Future work is needed to explore how to optimize models before local implementation.

Identifying antinuclear antibody positive individuals at risk for developing systemic autoimmune disease: development and validation of a real-time risk model.

Objective: Positive antinuclear antibodies (ANAs) cause diagnostic dilemmas for clinicians. Currently, no tools exist to help clinicians interpret the significance of a positive ANA in individuals without diagnosed autoimmune diseases. We developed and validated a risk model to predict risk of developing autoimmune disease in positive ANA individuals. Methods: Using a de-identified electronic health record (EHR), we randomly chart reviewed 2,000 positive ANA individuals to determine if a systemic autoimmune disease was diagnosed by a rheumatologist. A priori, we considered demographics, billing codes for autoimmune disease-related symptoms, and laboratory values as variables for the risk model. We performed logistic regression and machine learning models using training and validation samples. Results: We assembled training (n = 1030) and validation (n = 449) sets. Positive ANA individuals who were younger, female, had a higher titer ANA, higher platelet count, disease-specific autoantibodies, and more billing codes related to symptoms of autoimmune diseases were all more likely to develop autoimmune diseases. The most important variables included having a disease-specific autoantibody, number of billing codes for autoimmune disease-related symptoms, and platelet count. In the logistic regression model, AUC was 0.83 (95% CI 0.79-0.86) in the training set and 0.75 (95% CI 0.68-0.81) in the validation set. Conclusion: We developed and validated a risk model that predicts risk for developing systemic autoimmune diseases and can be deployed easily within the EHR. The model can risk stratify positive ANA individuals to ensure high-risk individuals receive urgent rheumatology referrals while reassuring low-risk individuals and reducing unnecessary referrals.