Preoperative Length Of Stay Research Articles

Preoperative Risk Factors Impacting Length of Stay After Transcarotid Artery Revascularization

Transcarotid artery revascularization (TCAR), using interoperative flow reversal is a unique, hybrid operation utilized in treating critical carotid artery stenosis. Over the past decade, TCAR has been increasingly used to treat asymptomatic carotid artery disease and has a similar risk profile to traditional carotid endarterectomy. Postoperative length of stay (LOS) has a significant impact on cost-effectiveness and quality outcomes in this expanded setting. The objective of this study is to develop a multivariate regression model to identify key preoperative variables and their impact factor on LOS after TCAR for asymptomatic carotid artery stenosis. We hypothesized that high-risk preoperative patient factors historically identified in carotid endarterectomy would similarly impact LOS after TCAR. A multi-institution, retrospective study of all adult patients undergoing TCAR with flow-reversal for intraoperative neuroprotection was performed using the Society for Vascular Surgery Vascular Quality Initiative (VQI) from January 2016 to August 2021. Patients with prolonged preoperative hospitalization (preoperative LOS ≥1day) were excluded to enhance the capture of carotid artery stenosis as the index admission. Univariate analysis was done on preoperative factors against LOS using nonparametric statistical tests. A multivariate model was then constructed using a negative binomial regression. The study population was split into 80% "training" data for model formulation and 20% "test" data for model validation. Thirteen thousand four hundred eighty-three patients undergoing TCAR for asymptomatic carotid stenosis met the study's inclusion criteria with a median postoperative LOS of 1.82days. Factors in VQI found to have a significant effect on LOS and retained in the multivariate model were lesion type (restenosis versus atherosclerotic), age, gender, chronic obstructive pulmonary disease, preoperative beta blocker, calcific lesion burden, hypertension status, and race (P<0.05). The model accurately predicted LOS after TCAR within 1day for 86.04% and within 2days for 94.51% of patients in the test population. This large-scale analysis from 2016 to 2021 spans a considerable expansion in the practice of TCAR for asymptomatic carotid disease. All preoperative variables shown to significantly increase the postoperative LOS were derived from the VQI data set. As LOS is a measure of health-care efficiency and cost-effectiveness, this model can be used to identify patients at risk for increased postoperative LOS. It has the potential to be incorporated into a patient/physician decision support tool to optimize resource planning and patient selection for elective TCAR.

Novel Preoperative Risk Stratification Using Digital Phenotyping Applying a Scalable Machine-Learning Approach.

Classification of perioperative risk is important for patient care, resource allocation, and guiding shared decision-making. Using discriminative features from the electronic health record (EHR), machine-learning algorithms can create digital phenotypes among heterogenous populations, representing distinct patient subpopulations grouped by shared characteristics, from which we can personalize care, anticipate clinical care trajectories, and explore therapies. We hypothesized that digital phenotypes in preoperative settings are associated with postoperative adverse events including in-hospital and 30-day mortality, 30-day surgical redo, intensive care unit (ICU) admission, and hospital length of stay (LOS). We identified all laminectomies, colectomies, and thoracic surgeries performed over a 9-year period from a large hospital system. Seventy-seven readily extractable preoperative features were first selected from clinical consensus, including demographics, medical history, and lab results. Three surgery-specific datasets were built and split into derivation and validation cohorts using chronological occurrence. Consensus k -means clustering was performed independently on each derivation cohort, from which phenotypes' characteristics were explored. Cluster assignments were used to train a random forest model to assign patient phenotypes in validation cohorts. We reconducted descriptive analyses on validation cohorts to confirm the similarity of patient characteristics with derivation cohorts, and quantified the association of each phenotype with postoperative adverse events by using the area under receiver operating characteristic curve (AUROC). We compared our approach to American Society of Anesthesiologists (ASA) alone and investigated a combination of our phenotypes with the ASA score. A total of 7251 patients met inclusion criteria, of which 2770 were held out in a validation dataset based on chronological occurrence. Using segmentation metrics and clinical consensus, 3 distinct phenotypes were created for each surgery. The main features used for segmentation included urgency of the procedure, preoperative LOS, age, and comorbidities. The most relevant characteristics varied for each of the 3 surgeries. Low-risk phenotype alpha was the most common (2039 of 2770, 74%), while high-risk phenotype gamma was the rarest (302 of 2770, 11%). Adverse outcomes progressively increased from phenotypes alpha to gamma, including 30-day mortality (0.3%, 2.1%, and 6.0%, respectively), in-hospital mortality (0.2%, 2.3%, and 7.3%), and prolonged hospital LOS (3.4%, 22.1%, and 25.8%). When combined with the ASA score, digital phenotypes achieved higher AUROC than the ASA score alone (hospital mortality: 0.91 vs 0.84; prolonged hospitalization: 0.80 vs 0.71). For 3 frequently performed surgeries, we identified 3 digital phenotypes. The typical profiles of each phenotype were described and could be used to anticipate adverse postoperative events.

Does the Timed-Up-and-Go Test Predict Length of Stay After Total Hip Arthroplasty? A Retrospective Study.

The prevalence of ambulatory total hip arthroplasty (THA) is rising, but it is not appropriate for all patients. Preoperative patient selection considers medical and social factors but overlooks patients' prior level of physical function. The aim of this study was to evaluate if preoperative physical function, measured by the Timed-Up-and-Go (TUG) test, is associated with length of stay (LOS) in patients who underwent primary THA. A retrospective study was performed using 396 patients who underwent primary THA within a 2-month period at a single institution. Regression analysis evaluated the relationship between preoperative TUG scores and hospital LOS. Receiver-operating characteristic (ROC) curves were generated to identify a cutoff TUG score associated with LOS longer than 24 hours. Univariate regression analysis of those discharged in less than 24 hours and those discharged in more than 24 hours found lower TUG scores (10.7 vs 13.7, respectively) were associated with patient discharge within 24 hours. Multivariate regression analysis showed a higher TUG score (adjusted odds ratio [aOR]: 0.91, 95% confidence interval [CI]: 0.84-0.99) was associated with decreased odds of discharge within 24 hours. Receiver-operating characteristic curve analysis was performed on the entire study cohort and the ambulatory surgery group and identified TUG scores of 10.3 and 10.5 seconds, respectively, associated with LOS of less than 24 hours (OR full cohort: 3.02, 95% CI: 1.94-4.71; OR ambulatory surgery: 2.97, 95% CI: 1.90-4.60). Sensitivity and specificity were not sufficient to support the use of these cutoff scores alone in predicting LOS. Although we were unable to establish a cutoff TUG score in patients who underwent primary THA that could determine LOS of more than 24 hours, the preoperative TUG score may be useful as a tool to aid in identifying patients who may require a longer hospital LOS. Further study is needed.

Abstract 12166: Social Determinants of Health and Acute Interstage Outcomes: An NPC-QIC Analysis

Introduction: The interstage period after Stage 1 palliation (S1P) carries high morbidity and mortality. The impact of social determinants of health (SDOH) on acute interstage outcomes has not been well described. Question: How do SDOH affect interstage outcomes? Methods: Infants discharged after S1P in the National Pediatric Cardiology Quality Improvement Collaborative Phase 2 registry were analyzed. ZIP code-level Childhood Opportunity Index (COI), a composite metric incorporating 29 indicators, was used to classify patients into 5 COI levels. Birth and S1P characteristics were compared. The association between COI level and binary acute interstage outcomes was assessed using log-rank test and logistic regression with and without adjustment for race/ethnicity, interstage risk factors, and interstage duration. Results: There were 1837 patients from 68 centers. There were differences across COI levels in birthweight, proximity to a surgical center, area of residence, age and weight at S1P, S1P length of stay (LOS), and feeding mode at discharge ( Table ). Over 98% of patients in all COI levels had home monitoring. Death or transplant occurred in 101 (5%) patients with unplanned readmission in 987 (53%), ICU admission in 448 (24%), unplanned catheterizations in 345 (19%), and reoperation in 83 (5%). COI level was not associated with differences in interstage outcomes on logistic regression or log-rank test ( Figure) . Conclusions: COI level is associated with differences in pre-operative status, feeding mode, and S1P LOS, but not acute interstage outcomes. The role of home monitoring programs in protecting against interstage disparities merits further investigation.

The predictive value of the preoperative albumin-to-fibrinogen ratio for postoperative hospital length of stay in liver cancer patients.

Hepatocellular carcinoma (HCC) is a significant global health burden, with postoperative hospital length of stay (LOS) impacting patient outcomes and healthcare costs. Existing nutritional, inflammatory, and coagulation indices can predict LOS, with particular interest in albumin, fibrinogen, and D-dimer. This study investigates the predictive value of preoperative albumin-to-fibrinogen ratio (AFR) and albumin-to-D-dimer ratio (ADR) for postoperative LOS in HCC patients. This retrospective study involved 462 adult HCC patients who underwent partial hepatic lesion excision between February 2016 and August 2022. We analyzed demographic and clinical data, including preoperative blood samples, surgical approach, and LOS. The primary outcome measure was LOS, calculated from the date of surgery to the date of hospital discharge. Preoperative AFR and ADR were calculated. The ROC curves determined optimal cutoff points. The Cox proportional hazards model, Kaplan-Meier method, and the log-rank test were used for statistical analysis. The study established an optimal AFR cutoff value of 15.474, with a higher AUC value than ADR, indicating superior predictive potential for postoperative LOS. Participants with high-AFR (AFR > 15.474) had a shorter median LOS (13 vs. 15 days, p < 0.001) compared to those with low-AFR (AFR ≤15.474). Multivariate analysis revealed high-AFR (HR: 1.99; p < 0.001) as a positive influence on LOS reduction, whereas Child-Pugh rated as B (HR: 0.49; p < 0.001), laparotomy (HR: 0.37; p < 0.001) and total bilirubin >20.5 μmol/L (HR: 0.58; p < 0.001) negatively impacted LOS reduction. Subgroup analysis confirmed AFR's predictive ability for patients experiencing reduced or prolonged LOS due to Child-Pugh score, surgical methods, and total bilirubin concentrations. Even within normal albumin and fibrinogen levels, patients with high-AFR exhibited a shorter LOS (all p < 0.001). Our findings underscore the value of the AFR as a reliable predictor of LOS in HCC patients. An AFR greater than 15.474 consistently correlated with a shorter LOS, suggesting its potential clinical utility in guiding perioperative management and resource allocation in HCC patients.

The relationship between preoperative anemia and length of hospital stay among patients undergoing radical surgery for esophageal carcinoma: a single-centre retrospective study

BackgroundAlthough it is unclear if preoperative anemia affects patients undergoing radical resection of esophageal cancer, it does increase the length of stay (LOS) for surgical patients. Accordingly, the purpose of this study was to investigate if, after adjusting for other covariates, anemia was independently associated with LOS in people undergoing radical resection of esophageal cancer.MethodsThe retrospective cohort study included 680 patients undergoing radical esophageal cancer surgery between January 2010 and December 2020. Preoperative anemia was the targeted independent variable, while LOS was the target independent variable. Demographics, comorbidities, laboratory tests, surgery and anesthesia, postoperative outcomes, and complications were collected. Multivariate linear analyses were performed for variables that might influence preoperative anemia and LOS selection. Subgroup analysis using hierarchical variables was then used to test the potential relationship.ResultsThe 647 individuals that were randomly chosen had an average age of 61.06 ± 8.16 years, and 77.43% of them were male. The prevalence of anemia was 36.6%. All patients recruited had an average length of stay (LOS) of 26.31 ± 13.19 days, 25.40 ± 11.44 days for patients who had no preoperative anemia, and 27.89 ± 15.66 days for patients who had preoperative anemia, p < 0.05. After adjusting for covariates, the results of fully adjusted linear regression revealed that preoperative anemia was significantly associated with LOS (β = 2.04, 95%CI (0.13, 3.96) ), p < 0.05. The results of the subgroup analysis were basically accurate and steady. Regardless of gender, same outcomes were seen when preoperative anemia was defined as a Hb level < 13 g/dL (β = 2.29, 95%CI (0.33, 4.25) ), p < 0.05. In addition, the LOS was shortened with the increase of preoperative hemoglobin (Hb) (β= -0.81, 95%CI (-1.46, -0.1) ), p < 0.05.ConclusionPreoperative anemia is typical in Chinese patients undergoing radical esophageal cancer resection and is independently associated with prolonged LOS.

Optimal Time to Surgery for Small Bowel Obstruction: A Risk Adjusted Analysis Utilizing the Nationwide Inpatient Sample.

The management of a small bowel obstruction (SBO) remains a challenge for general surgeons. The majority of SBOs can be treated conservatively; however, when surgery is required, the timing of operative intervention remains uncertain. Utilizing a large national database, we sought to evaluate the optimal timeframe for surgery following hospital admission with a diagnosis of SBO. This was a retrospective review utilizing the Nationwide Inpatient Sample (2006-2015). Outcomes following surgery for SBO were identified using ICD-9-CM coding. Two comorbidity indices were utilized to determine severity of illness. Patients were stratified into four groups based on time in days from admission to surgery. Propensity score models were created to predict the number of days until surgery following admission. Multivariate regression analysis was performed to determine risk adjusted postoperative outcomes. We identified 92807 cases of non-elective surgery for SBO. The overall mortality rate was 4.7%. Surgery on days 3-5 was associated with the lowest rate of mortality. A longer preoperative length of stay (LOS) (3-5days) was associated with a significantly greater number of wound (OR = 1.24) and procedural (OR = 1.17) complications compared to day 0. However, delayed surgical intervention (≥6days) was associated with decreased cardiac (OR = .69) and pulmonary complications (OR = .58). After adjustment, a preoperative LOS of 3-5days was associated with a decreased risk of mortality. In addition, increasing preoperative LOS was associated with decreased cardiopulmonary complications. However, an increased risk of procedural and wound complications during this time period suggest surgery may be more technically challenging.

Multiple regression model to analyze the total LOS for patients undergoing laparoscopic appendectomy

BackgroundThe rapid growth in the complexity of services and stringent quality requirements present a challenge to all healthcare facilities, especially from an economic perspective. The goal is to implement different strategies that allows to enhance and obtain health processes closer to standards. The Length Of Stay (LOS) is a very useful parameter for the management of services within the hospital and is an index evaluated for the management of costs. In fact, a patient's LOS can be affected by a number of factors, including their particular condition, medical history, or medical needs. To reduce and better manage the LOS it is necessary to be able to predict this value.MethodsIn this study, a predictive model was built for the total LOS of patients undergoing laparoscopic appendectomy, one of the most common emergency procedures. Demographic and clinical data of the 357 patients admitted at “San Giovanni di Dio e Ruggi d’Aragona” University Hospital of Salerno (Italy) had used as independent variable of the multiple linear regression model.ResultsThe obtained model had an R2 value of 0.570 and, among the independent variables, the significant variables that most influence the total LOS were Age, Pre-operative LOS, Presence of Complication and Complicated diagnosis.ConclusionThis work designed an effective and automated strategy for improving the prediction of LOS, that can be useful for enhancing the preoperative pathways. In this way it is possible to characterize the demand and to be able to estimate a priori the occupation of the beds and other related hospital resources.

Is It Possible to Predict the Length of Stay of Patients Undergoing Hip-Replacement Surgery?

The proximal fracture of the femur and hip is the most common reason for hospitalization in orthopedic departments. In Italy, 115,989 hip-replacement surgeries were performed in 2019, showing the economic relevance of studying this type of procedure. This study analyzed the data relating to patients who underwent hip-replacement surgery in the years 2010–2020 at the “San Giovanni di Dio e Ruggi d’Aragona” University Hospital of Salerno. The multiple linear regression (MLR) model and regression and classification algorithms were implemented in order to predict the total length of stay (LOS). Lastly, using a statistical analysis, the impact of COVID-19 was evaluated. The results obtained from the regression analysis showed that the best model was MLR, with an R2 value of 0.616, compared with XGBoost, Gradient-Boosted Tree, and Random Forest, with R2 values of 0.552, 0.543, and 0.448, respectively. The t-test showed that the variables that most influenced the LOS, with the exception of pre-operative LOS, were gender, age, anemia, fracture/dislocation, and urinary disorders. Among the classification algorithms, the best result was obtained with Random Forest, with a sensitivity of the longest LOS of over 89%. In terms of the overall accuracy, Random Forest and Gradient-Boosted Tree achieved a value of 71.76% and an error of 28.24%, followed by Decision Tree, with an accuracy of 71.13% and an error of 28.87%, and, finally, Support Vector Machine, with an accuracy of 65.06% and an error of 34.94%. A significant difference in cardiovascular disease, fracture/dislocation, and post-operative LOS variables was shown by the chi-squared test and Mann–Whitney test in the comparison between 2019 (before COVID-19) and 2020 (in full pandemic emergency conditions).

Regression Models to Study the Total LOS Related to Valvuloplasty.

Background: Valvular heart diseases are diseases that affect the valves by altering the normal circulation of blood within the heart. In recent years, the use of valvuloplasty has become recurrent due to the increase in calcific valve disease, which usually occurs in the elderly, and mitral valve regurgitation. For this reason, it is critical to be able to best manage the patient undergoing this surgery. To accomplish this, the length of stay (LOS) is used as a quality indicator. Methods: A multiple linear regression model and four other regression algorithms were used to study the total LOS function of a set of independent variables related to the clinical and demographic characteristics of patients. The study was conducted at the University Hospital “San Giovanni di Dio e Ruggi d’Aragona” of Salerno (Italy) in the years 2010–2020. Results: Overall, the MLR model proved to be the best, with an R2 value of 0.720. Among the independent variables, age, pre-operative LOS, congestive heart failure, and peripheral vascular disease were those that mainly influenced the output value. Conclusions: LOS proves, once again, to be a strategic indicator for hospital resource management, and simple linear regression models have shown excellent results to analyze it.

Data analytics and artificial intelligence in predicting length of stay, readmission, and mortality: a population-based study of surgical management of colorectal cancer

Data analytics and artificial intelligence (AI) have been used to predict patient outcomes after colorectal cancer surgery. A prospectively maintained colorectal cancer database was used, covering 4336 patients who underwent colorectal cancer surgery between 2003 and 2019. The 47 patient parameters included demographics, peri- and post-operative outcomes, surgical approaches, complications, and mortality. Data analytics were used to compare the importance of each variable and AI prediction models were built for length of stay (LOS), readmission, and mortality. Accuracies of at least 80% have been achieved. The significant predictors of LOS were age, ASA grade, operative time, presence or absence of a stoma, robotic or laparoscopic approach to surgery, and complications. The model with support vector regression (SVR) algorithms predicted the LOS with an accuracy of 83% and mean absolute error (MAE) of 9.69 days. The significant predictors of readmission were age, laparoscopic procedure, stoma performed, preoperative nodal (N) stage, operation time, operation mode, previous surgery type, LOS, and the specific procedure. A BI-LSTM model predicted readmission with 87.5% accuracy, 84% sensitivity, and 90% specificity. The significant predictors of mortality were age, ASA grade, BMI, the formation of a stoma, preoperative TNM staging, neoadjuvant chemotherapy, curative resection, and LOS. Classification predictive modelling predicted three different colorectal cancer mortality measures (overall mortality, and 31- and 91-days mortality) with 80–96% accuracy, 84–93% sensitivity, and 75–100% specificity. A model using all variables performed only slightly better than one that used just the most significant ones.

The Relationship Between Preoperative Physical Activity With American Society of Anesthesiologists Score and Postoperative Length of Stay in Patients Undergoing Radical Prostatectomy.

The relationship between preoperative physical activity (PA) and hospital length of stay (LOS) following radical prostatectomy (RP) is poorly understood. In addition, the relationship between PA and the American Society of Anesthesiologists Physical Status score (ASA PS), an established prognosticator of surgical risk, has not been studied. The authors assessed the relationship between leisure-time PA (LTPA), ASA PS, and LOS in individuals undergoing RP. This retrospective cohort study was conducted using data from an institutional database. Ordinal logistic regression was used to assess the relationship between preoperative LTPA and physical status as indicated by the ASA PS. Binary logistic regression was used to assess the relationship between preoperative LTPA and LOS. A sample of 1064 participants were included in the analyses. The participants in the highest preoperative LTPA quartile had 45% reduced odds (P = .015) of a worse ASA PS classification compared with participants in the lowest quartile. The participants engaging in vigorous LTPA preoperatively had 35% lower odds (P = .014) of a >2-day LOS following RP compared with participants who were not engaging in preoperative vigorous LTPA. Our findings suggest that total and vigorous preoperative LTPA is associated with improved preoperative American Society of Anesthesiologists scores and LOS following RP, respectively.

Impact of the COVID-19 pandemic on provision and outcomes of emergency abdominal surgery in Irish public hospitals.

BackgroundThe SARS-CoV-2 pandemic caused severe disruption to scheduled surgery in Ireland but its impact on emergency abdominal surgery (EAS) is unknown.AimsThe primary objective was to identify changes in volume, length of stay (LOS), and survival outcomes following EAS during the pandemic. A secondary objective was to evaluate differences in EAS patient flow including admission source, ITU utilisation, discharge destination, and readmission rates.MethodsUsing a national administrative dataset, demographic, comorbidity, and patient flow data on 5611 patients admitted for EAS between 2018 and 2020 were extracted. Pre-pandemic and pandemic timeframes were compared using graphic and regression analyses, and bivariate logistic regression, adjusting for demographics and case-mix.ResultsThere was a 19.9% decrease in EAS during the 2020 COVID-19 pandemic with no difference in comorbidity, nor in the commonest procedures. Most patients (92.4%) were admitted from home. In-hospital post-operative mortality was unchanged (7.6%). Patients over 80 comprised 16.3% of EAS pre-COVID, but 17.9% during COVID. Average total LOS reduced significantly by 4.9 days and 3.5 days during COVID-19 waves 1 (29 Feb 2020–30 June 2020) and 2 (1 July 2020–30 Nov 2020), respectively. During wave 1, pre-operative LOS reduced (1 day) and ICU LOS was significantly shorter (0.8 days), but similar change was not observed during wave 2.ConclusionsSignificant improvements in patient flow following admission for EAS during the pandemic were observed. These changes were not associated with greater mortality nor increased readmission rates and offer important insights into optimal delivery of EAS services.

SP3.2.10 Establishing an Emergency Surgical Ambulatory Care (ESAC) pathway for acute laparoscopic cholecystectomies: a single centre experience from a District General Hospital

Abstract Aims Early laparoscopic cholecystectomy is the gold standard for acute cholecystitis and gallstone pancreatitis. In order to deliver this service, a local Emergency Surgical Ambulatory Care (ESAC) pathway with a dedicated ESAC theatre list was established. The aim of this audit was to determine whether ESAC was associated with (1) improved length of stay and (2) cost efficiencies. Methods Consecutive patients who underwent an emergency laparoscopic cholecystectomy between October 2018 to October 2019 were identified. Data related to patient demographics, operating time, complications length of stay (LOS), reason for inpatient stay and re-admissions were collected. A dedicated ESAC service was introduced in July 2020. Outcomes were re-audited (July – December 2020). Results Prior to the introduction of ESAC, 142 patients (42% male, mean age 51 years (range 14 -82 years)) underwent an acute cholecystectomy, of which 13% were discharged on the same day. Median pre-operative LOS was 2 days (range 0-12 days) and median post-operative LOS was 1 day (range 1-16 days). Following the introduction of ESAC, 78 patients (32% male, mean age 49 years (range 22 – 89 years)) underwent an acute cholecystectomy, of which 76% were discharged on the same day and 90% within 1 day. Median pre-operative LOS was 0 days (range 0 to 7 days) and median post-operative LOS was 0 days (range 0-16 days). Conclusions Our results show that the introduction of a dedicated ESAC pathway improved both pre- and post-operative LOS. This subsequently saves approximately £80,000 per annum in hospital bed days.

Non-English Primary Language Is Associated with Short-Term Outcomes After Supratentorial Tumor Resection

Despite research indicating that patients with non-English primary language (NEPL) have increased hospital length of stay (LOS) for craniotomies, there is a paucity of neurosurgical research examining the impact of language on short-term outcomes. This study sought to evaluate short-term outcomes for patients with English primary language (EPL) and NEPL admitted for resection of a supratentorial tumor. Using the Agency for Healthcare Research and Quality Healthcare Cost and Utilization Project New Jersey State Inpatient Database, this study included patients 18-90 years old who underwent resection of a supratentorial primary brain tumor, meningioma, or brain metastasis from 2009 to 2017. The primary outcomes were total, preoperative, and postoperative LOS. Secondary outcomes were complications, mortality, and discharge disposition. Univariable and multivariable analyses compared Spanish primary language (SPL), non-English non-Spanish (NENS) primary language, and EPL groups. A total of 7324 patients were included: 2962 with primary brain tumor, 2091 with meningioma, and 2271 with brain metastasis. Patients with SPL (n= 297) were younger and more likely to have noncommercial insurance, lower income, and fewer comorbidities. Patients with NENS (n= 257) had similar age and comorbidities to the EPL group but had a greater proportion of noncommercially insured and low-income patients (P < 0.001). Multivariable analysis showed that patients with NENS had increased postoperative LOS (adjusted incidence rate ratio, 1.10; P= 0.008) and higher odds of a complication (adjusted odds ratio, 1.36; P= 0.015), and patients with SPL had higher odds of being discharged home (adjusted odds ratio, 1.55; P= 0.017). Patients with NEPL have different short-term outcomes after supratentorial tumor resection that varies based on primary language. More research is needed to understand the mechanisms driving these findings and to clarify unique experiences for different populations with NEPL.

Lean Six Sigma Approach for Reducing Length of Hospital Stay for Patients with Femur Fracture in a University Hospital.

Surgical intervention within 48 h of hospital admission is the gold standard procedure for the management of elderly patients with femur fractures, since the increase in preoperative waiting time is correlated with the onset of complications and longer overall length of stay (LOS) in the hospital. However, national evidence demonstrates that there is still the need to provide timely intervention for this type of patient, especially in some regions of central southern Italy. Here we discuss the introduction of a diagnostic–therapeutic assistance pathway (DTAP) to reduce the preoperative LOS for patients undergoing femur fracture surgery in a university hospital. A Lean Six Sigma methodology, based on the DMAIC cycle (Define, Measure, Analyze, Improve, Control), is implemented to evaluate the effectiveness of the DTAP. Data were retrospectively collected and analyzed from two groups of patients before and after the implementation of DTAP over a period of 10 years. The statistics of the process measured before the DTAP showed an average preoperative LOS of 5.6 days (standard deviation of 3.2), thus confirming the need for corrective actions to reduce the LOS in compliance with the national guidelines. The influence of demographic and anamnestic variables on the LOS was evaluated, and the impact of the DTAP was measured and discussed, demonstrating the effectiveness of the improvement actions implemented over the years and leading to a significant reduction in the preoperative LOS, which decreased to an average of 3.5 days (standard deviation of 3.60). The obtained reduction of 39% in the average LOS proved to be in good agreement with previously developed DTAPs for femur fracture available in the literature.

Improving recovery after microvascular decompression surgery for hemifacial spasm: experience from 530 cases with enhanced recovery after surgery (ERAS) protocol

Objective To assess the efficacy of microvascular decompression (MVD) for hemifacial spasm with an enhanced recovery after surgery (ERAS) protocol. Methods 984 hemifacial spasm patients who underwent MVD from Jan 2017 to Dec 2017 were analyzed. They were divided into the conventional treatment group (control; n = 453) and the later ERAS group (n = 531). The multimodal ERAS protocol consists of 23 perioperative elements. Time to feeding, mobilization, and urinary catheter removal, wound pain, postoperative nausea and vomiting (PONV), and total, preoperative, and perioperative hospital length of stay (LOS), along with outcomes and complications, were analyzed. Results The patients in both groups had similar clinical characteristics. Patients in the ERAS group had significantly higher rates of early feeding (469 [88.5%], ERAS, vs. 183 [40.6%], control; p < 0.05), early mobilization (497 [93.7%], ERAS, vs. 215 [47.7%], control; p < 0.05), and early removal of urinary catheter (458 [86.4%], ERAS, vs. 175 [38.8%], control; p < 0.05). The ERAS group also had a significantly lower incidence of wound pain (135 [25.5%], ERAS, vs. 348 [77.2%], control) and PONV (173 [32.6%], ERAS, vs. 251 (55.7%), control) (p < 0.05) and significantly shorter preoperative (0.9 ± 0.3 d, ERAS, vs. 2.3 ± 0.6 d, control), postoperative (4.1 ± 0.4 d, ERAS, vs. 5.8 ± 0.7 d, control), and total LOS (5.2 ± 0.3 d, ERAS, vs. 8.8 ± 0.6 d, control) (p < 0.05). There was no significant difference in outcomes or surgical complication rates between two groups. Conclusions Implementation of the ERAS protocol for patients undergoing MVD procedures for the treatment of HFS improved the quality of perioperative care without an increase in adverse events.

A Geriatric Hip Fracture Care Pathway: An Operational Approach to Quality Improvement

Introduction: Geriatric hip fractures are a devastating injury that decrease patient independence, increase morbidity and mortality, and have a significant economic impact. Although early operative intervention decreases mortality, hospitals often do not meet these benchmarks. The purpose of this study was to use a methodological approach to optimize the care and outcomes of patients sustaining geriatric hip fractures at a single level I trauma center by minimizing time to surgery and length of stay (LOS). Methods: A process map that outlined the paths that a hip fracture patient could take through our system from the time of injury to discharge was created. Classical operations management tactics known as Lean Synchronization and Six Sigma were used to identify bottlenecks in the system that led to delays in time to surgery or discharge. The pathway was systematically revised to address additional inefficiencies. Results: The initial process map revealed that time to surgery was increased by extensive preoperative testing and LOS was increased by admission to a non-orthopaedics service. By creating a standardized protocol for risk stratification and admitting all hip fracture patients to the orthopaedics service, improvements were seen within 6 months, including reductions in time to surgery (32.4 vs 17.5 hours), LOS (7.1 vs 5.6 days), 30-day readmissions (14.29% to 8.33%), and in-hospital mortality (2.79% vs 0%). Additional areas for improvement were later identified to reduce delirium rates and cost of care. Discussion: We conclude that the use of an operational management approach to address the inefficiencies in a clinical care pathway produced substantial and sustainable improvements in relevant outcome measures in patients sustaining geriatric hip fractures. By systematically identifying the bottlenecks in the system, we generated an ideal state pathway, which has allowed us to deliver higher quality care to our patients while simultaneously decreasing cost of care.

Impact of COVID-19 Pandemic in a Pediatric and Congenital Cardiovascular Surgery Program in Brazil.

Introduction:The coronavirus disease 2019 (COVID-19) has negatively impacted healthcare services worldwide. We hypothesized that the pandemic would affect our case mix and mortality. Our objective was to study this impact.Methods:We retrospectively studied all patients who underwent congenital heart surgeries from March 21st to August 21st in 2019 and 2020 using the institutional electronic database. We compared demographic data, preoperative and postoperative length of stay (LOS), risk stratification using Risk Adjustment for Congenital Heart Surgery (RACHS) classification and outcomes in both periods.Results:We observed a 66.7% decrease in our surgical volume (285 × 95 patients). Patients operated in the pre-pandemic period were older (911.3 [174.8 - 5953.8] days-old) compared to the pandemic period (275 days-old; P<0.05). When the case mix was compared between periods, the percentage of neonatal surgery was increased in the pandemic era (8% × 21.1%; P<0.05), and the number of RACHS 1-2 surgeries decreased significantly (60.7 × 27.4%; P<0.05). Preoperative LOS was increased in the pandemic period (1.2 × 7 days; P=0.001). There was no significant increment in mortality (P=0.1). Two patients tested positive for COVID-19 in the postoperative period and both died.Conclusion:Our program observed a sudden decrease in surgical volume and a consequent increase in surgical complexity. There was a non-significant increment in mortality.

Association of Preoperative Geriatric Assessment With Length of Stay After Combined Cardiac Surgery

For older patients undergoing cardiac surgery, geriatric factors are known to increase postoperative complications and prolong length of stay (LOS). Comprehensive geriatric assessment (CGA) is an evidence-based method for geriatric evaluation to develop an individualized-care plan to optimize physical, functional, and social issues. This study analyzed the association between preoperative CGA and hospital LOS after combined cardiac surgery. This retrospective monocentric study included all patients aged 75 years and greater who underwent combined cardiac surgery between 2014 and 2017. Hospital LOS, intensive care unit LOS, and postoperative complications were compared between patients with or without preoperative CGA before and after propensity-score matching. Mean age of the 407 patients was 79.6 years; 114 underwent a preoperative CGA (28%). For 305 patients (74.9%), coronary artery bypass was associated with aortic valve replacement. After propensity-score matching, a significant difference was found between the 2 groups (preoperative CGA versus none) for in-hospital LOS (12 versus 13 days; P= .04) and intensive care unit LOS (3 versus 4 days; P= .01). In multivariable analysis, a significant association remained between hospital LOS and CGA (P= .02), renal function (P= .02), mitral replacement (P= .001), and complications (P= .001). Our results favor the use of systematic preoperative CGA. These encouraging results need to be validated by prospective studies that assess the impact of individualized-care plan established after CGA on postoperative outcomes. With an aging population, efforts are required to determine how to implement preoperative individualized-care plans to improve postoperative outcomes for vulnerable patients undergoing cardiac surgery.