Development and validation of an instrument to predict prolonged length of stay in the postanesthesia care unit following ambulatory surgery.

PURPOSE: We sought to develop and validate an Anticipated Surveillance Requirement Prediction Instrument (ASRI) for prediction of prolonged postanesthesia care unit length of stay (PACU-LOS, more than four hours) after ambulatory surgery. METHODS: We analyzed hospital registry data from patients who received anesthesia care in ambulatory surgery centres (ASCs) of university-affiliated hospital networks in New York, USA (development and internal validation cohort [n = 183,711]) and Massachusetts, USA (validation cohort [n = 148,105]). We used stepwise backwards elimination to create ASRI. RESULTS: The model showed discriminatory ability in the development, internal, and external validation cohorts with areas under the receiver operating characteristic curve of 0.82 (95% confidence interval [CI], 0.82 to 0.83), 0.82 (95% CI, 0.81 to 0.83), and 0.80 (95% CI, 0.79 to 0.80), respectively. In cases started in the afternoon, ASRI scores ≥ 43 had a total predicted risk for PACU stay past 8 p.m. of 32% (95% CI, 31.1 to 33.3) vs 8% (95% CI, 7.9 to 8.5) compared with low score values (P-for-interaction < 0.001), which translated to a higher direct PACU cost of care of USD 207 (95% CI, 194 to 2,019; model estimate, 1.68; 95% CI, 1.64 to 1.73; P < 0.001) The effects of using the ASRI score on PACU use efficiency were greater in a free-standing ASC with no limitations on PACU bed availability. CONCLUSION: We developed and validated a preoperative prediction tool for prolonged PACU-LOS after ambulatory surgery that can be used to guide scheduling in ambulatory surgery to optimize PACU use during normal work hours, particularly in settings without limitation of PACU bed availability.

RéSUMé: OBJECTIF: Nous avons cherché à mettre au point et à valider un Instrument de prédiction anticipée des besoins de surveillance pour anticiper toute prolongation de la durée de séjour en salle de réveil (plus de quatre heures) après chirurgie ambulatoire. MéTHODE: Nous avons analysé les données enregistrées dans le registre de l'hôpital des patient·es qui ont reçu des soins d'anesthésie dans des centres de chirurgie ambulatoire (CCA) des réseaux hospitaliers affiliés à une université à New York, aux États-Unis (cohorte de développement et de validation interne [n = 183 711]) et au Massachusetts, États-Unis (cohorte de validation [n = 148 105]). Nous avons utilisé un procédé d'élimination progressive régressive pour créer notre instrument de prédiction. RéSULTATS: Le modèle a montré une capacité discriminatoire dans les cohortes de développement, de validation interne et de validation externe, avec des surfaces sous la courbe de fonction d'efficacité de l'opérateur (ROC) de 0,82 (intervalle de confiance [IC] à 95 %, 0,82 à 0,83), 0,82 (IC 95 %, 0,81 à 0,83), et 0,80 (IC 95 %, 0,79 à 0,80), respectivement. Dans les cas commencés en après-midi, les scores sur notre instrument de prédiction ≥ 43 montraient un risque total prédit de séjour en salle de réveil après 20 h de 32 % (IC 95 %, 31,1 à 33,3) vs 8 % (IC 95 %, 7,9 à 8,5) comparativement aux valeurs de score faibles (P-pour-interaction < 0,001), ce qui s'est traduit par une augmentation de 207 USD du coût direct des soins en salle de réveil (IC 95 %, 194 à 2019; estimation du modèle, 1,68; IC 95 %, 1,64 à 1,73; P < 0,001). Les effets de l'utilisation du score de notre instrument de prédiction sur l'efficacité d'utilisation de la salle de réveil étaient plus importants dans un CCA autonome sans limitation dans la disponibilité des lits en salle de réveil. CONCLUSION: Nous avons mis au point et validé un outil de prédiction préopératoire de la prolongation de la durée de séjour en salle de réveil après une chirurgie ambulatoire qui peut être utilisé pour guider la planification en chirurgie ambulatoire afin d'optimiser l'utilisation de la salle de réveil pendant les heures normales de travail, en particulier dans les milieux sans limitation de disponibilité des lits en salle de réveil.

Development and validation of a machine learning ASA-score to identify candidates for comprehensive preoperative screening and risk stratification.

OBJECTIVE: The ASA physical status (ASA-PS) is determined by an anesthesia provider or surgeon to communicate co-morbidities relevant to perioperative risk. Assigning an ASA-PS is a clinical decision and there is substantial provider-dependent variability. We developed and externally validated a machine learning-derived algorithm to determine ASA-PS (ML-PS) based on data available in the medical record. DESIGN: Retrospective multicenter hospital registry study. SETTING: University-affiliated hospital networks. PATIENTS: Patients who received anesthesia at Beth Israel Deaconess Medical Center (Boston, MA, training [n = 361,602] and internal validation cohorts [n = 90,400]) and Montefiore Medical Center (Bronx, NY, external validation cohort [n = 254,412]). MEASUREMENTS: The ML-PS was created using a supervised random forest model with 35 preoperatively available variables. Its predictive ability for 30-day mortality, postoperative ICU admission, and adverse discharge were determined by logistic regression. MAIN RESULTS: The anesthesiologist ASA-PS and ML-PS were in agreement in 57.2% of the cases (moderate inter-rater agreement). Compared with anesthesiologist rating, ML-PS assigned more patients into extreme ASA-PS (I and IV), (p < 0.01), and less patients in ASA II and III (p < 0.01). ML-PS and anesthesiologist ASA-PS had excellent predictive values for 30-day mortality, and good predictive values for postoperative ICU admission and adverse discharge. Among the 3594 patients who died within 30 days after surgery, net reclassification improvement analysis revealed that using the ML-PS, 1281 (35.6%) patients were reclassified into the higher clinical risk category compared with anesthesiologist rating. However, in a subgroup of multiple co-morbidity patients, anesthesiologist ASA-PS had a better predictive accuracy than ML-PS. CONCLUSIONS: We created and validated a machine learning physical status based on preoperatively available data. The ability to identify patients at high risk early in the preoperative process independent of the provider's decision is a part of the process we use to standardize the stratified preoperative evaluation of patients scheduled for ambulatory surgery.

Comparison of the effects of sugammadex versus neostigmine for reversal of neuromuscular block on hospital costs of care.

BACKGROUND: Sugammadex reversal of neuromuscular block facilitates recovery of neuromuscular function after surgery, but the drug is expensive. We evaluated the effects of sugammadex on hospital costs of care. METHODS: We analysed 79 474 adult surgical patients who received neuromuscular blocking agents and reversal from two academic healthcare networks between 2016 and 2021 to calculate differences in direct costs. We matched our data with data from the Healthcare Cost and Utilization Project-National Inpatient Sample (HCUP-NIS) to calculate differences in total costs in US dollars. Perioperative risk profiles were defined based on ASA physical status and admission status (ambulatory surgery vs hospitalisation). RESULTS: Based on our registry data analysis, administration of sugammadex vs neostigmine was associated with lower direct costs (-1.3% lower costs; 95% confidence interval [CI], -0.5 to -2.2%; P=0.002). In the HCUP-NIS matched cohort, sugammadex use was associated with US$232 lower total costs (95% CI, -US$376 to -US$88; P=0.002). Subgroup analysis revealed that sugammadex was associated with US$1042 lower total costs (95% CI, -US$1198 to -US$884; P<0.001) in patients with lower risk. In contrast, sugammadex was associated with US$620 higher total costs (95% CI, US$377 to US$865; P<0.001) in patients with a higher risk (American Society of Anesthesiologists physical status ≥3 and preoperative hospitalisation). CONCLUSIONS: The effects of using sugammadex on costs of care depend on patient risk, defined based on comorbidities and admission status. We observed lower costs of care in patients with lower risk and higher costs of care in hospitalised surgical patients with severe comorbidities.

Incidence and predictors of case cancellation within 24 h in patients scheduled for elective surgical procedures.

OBJECTIVE: Avoidable case cancellations within 24 h reduce operating room (OR) efficiency, add unnecessary costs, and may have physical and emotional consequences for patients and their families. We developed and validated a prediction tool that can be used to guide same day case cancellation reduction initiatives. DESIGN: Retrospective hospital registry study. SETTING: University-affiliated hospitals network (NY, USA). PATIENTS: 246,612 (1/2016-6/2021) and 58,662 (7/2021-6/2022) scheduled elective procedures were included in the development and validation cohort. MEASUREMENTS: Case cancellation within 24 h was defined as cancelling a surgical procedure within 24 h of the scheduled date and time. Our candidate predictors were defined a priori and included patient-, procedural-, and appointment-related factors. We created a prediction tool using backward stepwise logistic regression to predict case cancellation within 24 h. The model was subsequently recalibrated and validated in a cohort of patients who were recently scheduled for surgery. MAIN RESULTS: 8.6% and 8.7% scheduled procedures were cancelled within 24 h of the intended procedure in the development and validation cohort, respectively. The final weighted score contains 29 predictors. A cutoff value of 15 score points predicted a 10.3% case cancellation rate with a negative predictive value of 0.96, and a positive predictive value of 0.21. The prediction model showed good discrimination in the development and validation cohort with an area under the receiver operating characteristic curve (AUC) of 0.79 (95% confidence interval 0.79-0. 80) and an AUC of 0.73 (95% confidence interval 0.72-0.73), respectively. CONCLUSIONS: We present a validated preoperative prediction tool for case cancellation within 24 h of surgery. We utilize the instrument in our institution to identify patients with high risk of case cancellation. We describe a process for recalibration such that other institutions can also use the score to guide same day case cancellation reduction initiatives.

Improving Adjuvant Liver-Directed Treatment Recommendations for Unresectable Hepatocellular Carcinoma: An Artificial Intelligence-Based Decision-Making Tool.

PURPOSE: Liver-directed therapy after transarterial chemoembolization (TACE) can lead to improvement in survival for selected patients with unresectable hepatocellular carcinoma (HCC). However, there is uncertainty in the appropriate application and modality of therapy in current clinical practice guidelines. The aim of this study was to develop a proof-of-concept, machine learning (ML) model for treatment recommendation in patients previously treated with TACE and select patients who might benefit from additional treatment with combination stereotactic body radiotherapy (SBRT) or radiofrequency ablation (RFA). METHODS: This retrospective observational study was based on data from an urban, academic hospital system selecting for patients diagnosed with stage I-III HCC from January 1, 2008, to December 31, 2018, treated with TACE, followed by adjuvant RFA, SBRT, or no additional liver-directed modality. A feedforward, ML ensemble model provided a treatment recommendation on the basis of pairwise assessments evaluating each potential treatment option and estimated benefit in survival. RESULTS: Two hundred thirty-seven patients met inclusion criteria, of whom 54 (23%) and 49 (21%) received combination of TACE and SBRT or TACE and RFA, respectively. The ML model suggested a different consolidative modality in 32.7% of cases among patients who had previously received combination treatment. Patients treated in concordance with model recommendations had significant improvement in progression-free survival (hazard ratio 0.5; P = .007). The most important features for model prediction were cause of cirrhosis, stage of disease, and albumin-bilirubin grade (a measure of liver function). CONCLUSION: In this proof-of-concept study, an ensemble ML model was able to provide treatment recommendations for HCC who had undergone prior TACE. Additional treatment in line with model recommendations was associated with significant improvement in progression-free survival, suggesting a potential benefit for ML-guided medical decision making.

Pediatric surgical site infection (SSI) following ambulatory surgery: Incidence, risk factors and patient outcomes.

BACKGROUND: Inpatient surgical site infections (SSIs) cause morbidity in children. The SSI rate among pediatric ambulatory surgery patients is less clear. To fill this gap, we conducted a multiple-institution, retrospective epidemiologic study to identify incidence, risk factors, and outcomes. METHODS: We identified patients aged <22 years with ambulatory visits between October 2010 and September 2015 via electronic queries at 3 medical centers. We performed sample chart reviews to confirm ambulatory surgery and adjudicate SSIs. Weighted Poisson incidence rates were calculated. Separately, we used case-control methodology using multivariate backward logistical regression to assess risk-factor association with SSI. RESULTS: In total, 65,056 patients were identified by queries, and we performed complete chart reviews for 13,795 patients; we identified 45 SSIs following ambulatory surgery. The weighted SSI incidence following pediatric ambulatory surgery was 2.00 SSI per 1,000 ambulatory surgeries (95% confidence interval [CI], 1.37-3.00). Integumentary surgeries had the highest weighted SSI incidence, 3.24 per 1,000 ambulatory surgeries (95% CI, 0.32-12). The following variables carried significantly increased odds of infection: clean contaminated or contaminated wound class compared to clean (odds ratio [OR], 9.8; 95% CI, 2.0-48), other insurance type compared to private (OR, 4.0; 95% CI, 1.6-9.8), and surgery on weekend day compared to weekday (OR, 30; 95% CI, 2.9-315). Of the 45 instances of SSI following pediatric ambulatory surgery, 40% of patients were admitted to the hospital and 36% required a new operative procedure or bedside incision and drainage. CONCLUSIONS: Our findings suggest that morbidity is associated with SSI following ambulatory surgery in children, and we also identified possible targets for intervention.

Central Venous Catheter Salvage in Ambulatory Central Line-Associated Bloodstream Infections.

BACKGROUND: Guidelines for treatment of central line-associated bloodstream infection (CLABSI) recommend removing central venous catheters (CVCs) in many cases. Clinicians must balance these recommendations with the difficulty of obtaining alternate access and subjecting patients to additional procedures. In this study, we evaluated CVC salvage in pediatric patients with ambulatory CLABSI and associated risk factors for treatment failure. METHODS: This study was a secondary analysis of 466 ambulatory CLABSIs in patients <22 years old who presented to 5 pediatric medical centers from 2010 to 2015. We defined attempted CVC salvage as a CVC left in place ≥3 days after a positive blood culture result. Salvage failure was removal of the CVC ≥3 days after CLABSI. Successful salvage was treatment of CLABSI without removal of the CVC. Bivariate and multivariable logistic regression analyses were used to test associations between risk factors and attempted and successful salvage. RESULTS: A total of 460 ambulatory CLABSIs were included in our analysis. CVC salvage was attempted in 379 (82.3%) cases. Underlying diagnosis, CVC type, number of lumens, and absence of candidemia were associated with attempted salvage. Salvage was successful in 287 (75.7%) attempted cases. Underlying diagnosis, CVC type, number of lumens, and absence of candidemia were associated with successful salvage. In patients with malignancy, neutropenia within 30 days before CLABSI was significantly associated with both attempted salvage and successful salvage. CONCLUSIONS: CVC salvage was often attempted and was frequently successful in ambulatory pediatric patients presenting with CLABSI.

Costs of ambulatory pediatric healthcare-associated infections: Central-line-associated bloodstream infection (CLABSIs), catheter-associated urinary tract infection (CAUTIs), and surgical site infections (SSIs).

OBJECTIVE: Ambulatory healthcare-associated infections (HAIs) occur frequently in children and are associated with morbidity. Less is known about ambulatory HAI costs. This study estimated additional costs associated with pediatric ambulatory central-line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTI), and surgical site infections (SSIs) following ambulatory surgery. DESIGN: Retrospective case-control study. SETTING: Four academic medical centers. PATIENTS: Children aged 0-22 years seen between 2010 and 2015 and at risk for HAI as identified by electronic queries. METHODS: Chart review adjudicated HAIs. Charges were obtained for patients with HAIs and matched controls 30 days before HAI, on the day of, and 30 days after HAI. Charges were converted to costs and 2015 USD. Mixed-effects linear regression was used to estimate the difference-in-differences of HAI case versus control costs in 2 models: unrecorded charge values considered missing and a sensitivity analysis with unrecorded charge considered $0. RESULTS: Our search identified 177 patients with ambulatory CLABSIs, 53 with ambulatory CAUTIs, and 26 with SSIs following ambulatory surgery who were matched with 382, 110, and 75 controls, respectively. Additional cost associated with an ambulatory CLABSI was $5,684 (95% confidence interval [CI], $1,005-$10,362) and $6,502 (95% CI, $2,261-$10,744) in the 2 models; cost associated with a CAUTI was $6,660 (95% CI, $1,055, $12,145) and $2,661 (95% CI, -$431 to $5,753); cost associated with an SSI following ambulatory surgery at 1 institution only was $6,370 (95% CI, $4,022-$8,719). CONCLUSIONS: Ambulatory HAI in pediatric patients are associated with significant additional costs. Further work is needed to reduce ambulatory HAIs.

Coordination and management of multicenter clinical studies in trauma: Experience from the PRospective Observational Multicenter Major Trauma Transfusion (PROMMTT) Study.

AIM: Early death due to hemorrhage is a major consequence of traumatic injury. Transfusion practices differ among hospitals and it is unknown which transfusion practices improve survival. This report describes the experience of the PRospective Observational Multicenter Major Trauma Transfusion (PROMMTT) Study Data Coordination Center in designing and coordinating a study to examine transfusion practices at ten Level 1 trauma centers in the US. METHODS: PROMMTT was a multisite prospective observational study of severely injured transfused trauma patients. The clinical sites collected real-time information on the timing and amounts of blood product infusions as well as colloids and crystalloids, vital signs, initial diagnostic and clinical laboratory tests, life saving interventions and other clinical care data. RESULTS: Between July 2009 and October 2010, PROMMTT screened 12,561 trauma admissions and enrolled 1245 patients who received one or more blood transfusions within 6h of Emergency Department (ED) admission. A total of 297 massive transfusions were observed over the course of the study at a combined rate of 5.0 massive transfusion patients/week. CONCLUSION: PROMMTT is the first multisite study to collect real-time prospective data on trauma patients requiring transfusion. Support from the Department of Defense and collaborative expertise from the ten participating centers helped to demonstrate the feasibility of prospective trauma transfusion studies. The observational data collected from this study will be an invaluable resource for research in trauma surgery and it will guide the design and conduct of future randomized trials.