Non-home Discharge Destination Research Articles

Predictors of Nonhome Discharge After Cervical Disc Replacement.

Retrospective review of a national database. The aim of this study was to identify the factors that increase the risk of nonhome discharge after CDR. As spine surgeons continue to balance increasing surgical volume, identifying variables associated with patient discharge destination can help expedite postoperative placement and reduce unnecessary length of stay. However, no prior study has identified the variables predictive of nonhome patient discharge after cervical disc replacement (CDR). The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was queried for patients who underwent primary 1-level or 2-level CDR between 2011 and 2020. Multivariable Poisson regression with robust error variance was employed to identify the predictors for nonhome discharge destination following surgery. A total of 7276 patients were included in this study, of which 94 (1.3%) patients were discharged to a nonhome destination. Multivariable regression revealed older age (OR: 1.076, P<0.001), Hispanic ethnicity (OR: 4.222, P=0.001), BMI (OR: 1.062, P=0.001), ASA class ≥3 (OR: 2.562, P=0.002), length of hospital stay (OR: 1.289, P<0.001), and prolonged operation time (OR: 1.007, P<0.001) as predictors of nonhome discharge after CDR. Outpatient surgery setting was found to be protective against nonhome discharge after CDR (OR: 0.243, P<0.001). Age, Hispanic ethnicity, BMI, ASA class, prolonged hospital stay, and prolonged operation time are independent predictors of nonhome discharge after CDR. Outpatient surgery setting is protective against nonhome discharge. These findings can be utilized to preoperatively risk stratify expected discharge destination, anticipate patient discharge needs postoperatively, and expedite discharge in these patients to reduce health care costs associated with prolonged length of hospital stay. IV.

Application of machine learning constructs to predict post-operative complications and adverse events following shoulder hemiarthroplasty

Background: Artificial intelligence (AI) constructs and machine learning (ML) algorithms have demonstrated utility in predicting various clinical, surgical, and financial outcomes. In this study, we applied AI to shoulder hemiarthroplasty (HA) to predict various post-operative complications. Methods: The sample was queried from the American college of surgeons-national surgical quality improvement program (ACS-NSQIP) database for all shoulder HA cases from 2008-2018. Six ML algorithms-random forest classifier, gradient boosting classifier, decision tree classifier, SVM classifier-tuned model, Gaussian Naïve Bayes classifier, multi-layer perception-analyzed the sample dataset. Postoperative complications included extended length of stay, non-home discharge destination, transfusion, and any adverse event. Each ML model was compared to logistic regression (LR), and model strength was evaluated. Results: We identified a total of 1585 shoulder HA cases. Mean age, BMI, operative time, and length of stay were 66±12 years, 31±8 kg/m2, 114±61 minutes, and 2.93±6.61 days. Preop hematocrit, longer operative time, and older age were most predictive of extended length of stay. Preop hematocrit, operative time, and ASA class had the highest importance in any adverse events (AAE) prediction. ML models outperformed traditional comorbidity indices, LR, for predicting extended length of stay (79% vs. 66%), non-home discharge destination (79% vs. 65%), any adverse event (78% vs. 66%), and transfusion requirement (82% vs. 63%). Conclusions: ML algorithms predicted post-surgical outcomes of interest following shoulder HA at a higher rate to conventional LR and can assist orthopedic surgeons in decision making.

Elective Single-Level Primary Anterior Cervical Decompression and Fusion for Degenerative Spondylotic Cervical Myelopathy is Associated With Decreased Resource Utilization Versus Posterior Cervical Decompression and Fusion.

Retrospective cohort study. To compare elective single-level anterior cervical discectomy and fusion (ACDF) versus posterior cervical decompression and fusion (PCDF) for degenerative cervical myelopathy (DCM) in terms of (1) cost, (2) length of hospital stay, and (3) discharge destination in Medicare patients. A sub-analysis of potential cost drivers was also performed. In the era of value-based medicine, there is substantial interest in reducing the cost of care. Both ACDF and PCDF are used to treat DCM but carry different morbidity and risk profiles that can impact hospital resource utilization. However, this has not been assessed on a national level. Patients undergoing single-level elective ACDF and PCDF surgery were identified using the 2019 Medicare Provider Analysis and Review (MedPAR) Limited Data Set (LDS) and Centers for Medicare and Medicaid Services (CMS) 2019 Impact File. Multivariate models of hospital cost of care, length of stay, and discharge destination were performed, controlling for confounders. A univariate sub-analysis of 9 revenue centers was performed. In all, 3942 patients met the inclusion criteria. The mean cost of elective single-level cervical fusion for myelopathy was $18,084±10,783, and the mean length of stay was 2.45±2.95d. On multivariate analysis, ACDF was independently associated with decreased cost of $5,814 (P<0.001), shorter length of stay by 1.1 days (P<0.001), and decreased risk of nonhome discharge destination by 58% (adjusted odds ratio: 0.422, P<0.001).On sub-analysis of 9 revenue centers, medical/surgical supply ($10,497, 44%), operating room charges ($5401, 23%), and accommodations ($3999, 17%) were the largest drivers of charge differences. Single-level elective primary ACDF for DCM was independently associated with decreased cost, decreased hospital length of stay, and a lower rate of nonhome discharge compared with PCDF. Medical and surgical supply, operating room, and accommodation differences between ACDF and PCDF are potential areas for intervention. Increased granularity in reimbursement structures is warranted to prevent the creation of disincentives to the treatment of patients with DCM with pathology that is better addressed with PCDF. Level-III Retrospective Cohort Study.

Clinical tool for prognostication of discharge outcomes following craniotomy for meningioma

BackgroundPatients' comorbidities might affect the immediate postoperative morbidity and discharge disposition after surgical resection of intracranial meningioma. ObjectiveTo study the impact of comorbidities on outcomes and provide a web-based application to predict time to favorable discharge. MethodsA retrospective review of the prospectively collected national inpatient sample (NIS) database was conducted for the years 2009–2013. Time to favorable discharge was defined as hospital length of stay (LOS). A favorable discharge was defined as a discharge to home and a non-home discharge destination was defined as an unfavorable discharge. Cox proportional hazards model was built. Full model for time to discharge and separate reduced models were built. ResultsOf 10,757 patients who underwent surgery for meningioma, 6554 (60%) had a favorable discharge. The median hospital LOS was 3 days (interquartile range [IQR] 2–5). In the full model, several clinical and socioeconomic factors were associated with a higher likelihood of unfavorable discharge. In the reduced model, 13 modifiable comorbidities were negatively associated with a favorable discharge except for drug abuse and obesity, which are not associated with discharge. Both models accurately predicted time to favorable discharge (c-index:0.68–0.71). ConclusionWe developed a web application using robust prognostic model that accurately predicts time to favorable discharge after surgery for meningioma. Using this tool will allow physicians to calculate individual patient discharge probabilities based on their individual comorbidities and provide an opportunity to timely risk stratify and address some of the modifiable factors prior to surgery.

Bariatric surgery prior to elective shoulder arthroplasty: a Nationwide Inpatient Sample analysis

BackgroundObesity has been linked to adverse outcomes after various orthopedic procedures, and bariatric surgery is an effective surgical treatment for morbid obesity. This study assesses whether prior bariatric surgery is associated with differences in hospital length of stay (LOS), discharge destination, and inpatient complication rate for elective shoulder arthroplasty. MethodsThe Nationwide Inpatient Sample database was queried from years 2003 to 2014 for all elective anatomic and reverse total shoulder arthroplasty cases. Two groups were defined: morbidly obese without prior bariatric surgery (MO cohort) and prior bariatric surgery without morbid obesity (BS cohort). Outcome measures were LOS (extended if greater than the 75th percentile), discharge destination (home or non-home), and any inpatient complication. Patients under age of 18 years and those with missing information were excluded. National estimates were calculated using weights provided by the Nationwide Inpatient Sample database. Chi-squared tests were performed for demographics and comorbidities. Binomial multivariate logistic regression was performed using significant demographics and comorbidities. ResultsA weighted-total of 19,877 patients were included in the study, of which 2783 were in the BS cohort and 17,094 were in the MO cohort. The BS group was younger (62.9 years vs. 66.0 years), had more females (73% vs. 69%), and was more likely to be anemic (15% vs. 10%). The MO group was more likely to have diabetes (40% vs. 22%), hypertension (83% vs. 65%), and peripheral vascular disease (3% vs. 1%). Multivariate analysis showed that the BS cohort had decreased odds of extended LOS (odds ratio [OR], 0.68), non-home discharge destination (OR, 0.67), and developing any inpatient complication (OR, 0.42). ConclusionIn the setting of anatomic and reverse total shoulder arthroplasties, patients with prior bariatric surgery and without morbid obesity had more favorable hospital LOS, discharge destination, and inpatient complication rate than morbidly obese patients with no prior bariatric surgery. Further studies are warranted to better elucidate the relationship between bariatric surgery and shoulder arthroplasty.

Short-term and long-term increased mortality in elderly patients with burn injury: a national longitudinal cohort study

BackgroundThe population of elderly patients with burn injuries is growing. Insight into long-term mortality rates of elderly after burn injury and predictors affecting outcome is limited. This study aimed to provide this information.MethodsA multicentre observational retrospective cohort study was conducted in all three Dutch burn centres. Patients aged ≥65 years, admitted with burn injuries between 2009 and 2018, were included. Data were retrieved from electronic patient records and the Dutch Burn Repository R3. Mortality rates and standardized mortality ratios (SMRs) were calculated. Multivariable logistic regression was used to assess predictors for in-hospital mortality and mortality after discharge at 1 year and five-year. Survival analysis was used to assess predictors of five-year mortality.ResultsIn total, 682/771 admitted patients were discharged. One-year and five-year mortality rates were 8.1 and 23.4%. The SMRs were 1.9(95%CI 1.5–2.5) and 1.4(95%CI 1.2–1.6), respectively. The SMRs were highest in patients aged 75–80 years at 1 year (SMRs 2.7, 95%CI 1.82–3.87) and five-year in patients aged 65–74 years (SMRs 10.1, 95%CI 7.7–13.0). Independent predictors for mortality at 1 year after discharge were higher age (OR 1.1, 95%CI 1.0–1.1), severe comorbidity, (ASA-score ≥ 3) (OR 4.8, 95%CI 2.3–9.7), and a non-home discharge location (OR 2.0, 95%CI 1.1–3.8). The relative risk of dying up to five-year was increased by age (HR 1.1, 95%CI 1.0–1.1), severe comorbidity (HR 2.3, 95%CI 1.6–3.5), and non-home discharge location (HR 2.1, 95%CI 1.4–3.2).ConclusionLong-term mortality until five-year after burn injury was higher than the age and sex-matched general Dutch population, and predicted by higher age, severe comorbidity, and a non-home discharge destination. Next to pre-injury characteristics, potential long-lasting systemic consequences on biological mechanisms following burn injuries probably play a role in increased mortality. Decreased health status makes patients more prone to burn injuries, leading to early death.

135. Elective primary anterior cervical decompression and fusion for degenerative spondylotic cervical myelopathy is associated with decreased resource utilization vs posterior cervical decompression and fusion

135. Elective primary anterior cervical decompression and fusion for degenerative spondylotic cervical myelopathy is associated with decreased resource utilization vs posterior cervical decompression and fusion

1069 ESSENTIAL FRAILTY TOOLSET AS A PREDICTOR OF PROLONGED LENGTH OF STAY AND DISCHARGE DESTINATION AFTER TRANSCATHETER AORTIC VALVE IMPLANTATION

Abstract Introduction Frailty is associated with poor outcomes following transcatheter aortic valve implantation (TAVI). Rockwood is the widely used score for this population. In a recent trial, a more objective score, the Essential Frailty Toolset (EFT) outperformed Rockwood’s in predicting mortality and disability 1-year post-TAVI. Whether it predicts in-hospital length of stay (LOS) and discharge destination post-TAVI remains unclear. Method A cohort of patients undergoing TAVI for aortic stenosis was recruited, demographic characteristics collected, and frailty assessed with EFT and Rockwood scores. Primary outcomes were LOS post-TAVI, categorised as ‘not prolonged’ (≤2 days) or ‘prolonged’ (&amp;gt;2 days) and discharge destination, characterised as ‘home’ or ‘non-home’. Results 86 patients were recruited, with median age 82 years (IQR 78–86). 54% were male. EFT identified 35% and Rockwood 11% as frail. 19% were cognitively impaired. 5 chair rises were completed by 70%, with 30% managing under 15 seconds. Median haemoglobin was 121 g/L (IQR 109.5–136). Median albumin was 36 g/L (IQR 33–39). 84% of procedures were transfemoral. 20% had moderate–severe left ventricular systolic dysfunction. Median LOS post-TAVI was 2 days (IQR 2–5). 94% were discharged home, 6% to referring local hospital or rehabilitation centre. 46% were NYHA class III-IV. A model for prolonged LOS including comorbidities, showed frailty determined by EFT (OR 4.80, CI 95% 1.52–15.2, p = 0.008) but not Rockwood (OR 5.00, CI 95% 0.865–29.0, p = 0.072) was the only significant independent predictor for prolonged LOS. A model adjusting for comorbidities also showed EFT to be an independent predictor for non-home discharge destination of borderline significance (OR 2.57 CI 95% 0.994–6.66, p = 0.051) but Rockwood was not (OR 1.38 CI95% 0.485–3.91, p = 0.548). Conclusion In a real-world elderly population, EFT score was a stronger, more independent predictor of prolonged LOS and non-home discharge post-TAVI, than Rockwood’s. EFT would be an effective pre-operative assessment tool for LOS and discharge destination for TAVI.

Impact of race on nonroutine discharge, length of stay, and postoperative complications after surgery for spinal metastases.

Previous studies have suggested the possibility of racial disparities in surgical outcomes for patients undergoing spine surgery, although this has not been thoroughly investigated in those with spinal metastases. Given the increasing prevalence of spinal metastases requiring intervention, knowledge about potential discrepancies in outcomes would benefit overall patient care. The objective in the present study was to investigate whether race was an independent predictor of postoperative complications, nonroutine discharge, and prolonged length of stay (LOS) after surgery for spinal metastasis. The authors retrospectively examined patients at a single comprehensive cancer center who had undergone surgery for spinal metastasis between April 2013 and April 2020. Demographic information, primary pathology, preoperative clinical characteristics, and operative outcomes were collected. Factors achieving p values < 0.15 on univariate regression were entered into a stepwise multivariable logistic regression to generate predictive models. Nonroutine discharge was defined as a nonhome discharge destination and prolonged LOS was defined as LOS greater than the 75th percentile for the entire cohort. Three hundred twenty-eight patients who had undergone 348 operations were included: 240 (69.0%) White and 108 (31.0%) Black. On univariable analysis, cohorts significantly differed in age (p = 0.02), marital status (p < 0.001), insurance status (p = 0.03), income quartile (p = 0.02), primary tumor type (p = 0.04), and preoperative Karnofsky Performance Scale (KPS) score (p < 0.001). On multivariable analysis, race was an independent predictor for nonroutine discharge: Black patients had significantly higher odds of nonroutine discharge than White patients (adjusted odds ratio [AOR] 2.24, 95% confidence interval [CI] 1.28-3.92, p = 0.005). Older age (AOR 1.06 per year, 95% CI 1.03-1.09, p < 0.001), preoperative KPS score ≤ 70 (AOR 3.30, 95% CI 1.93-5.65, p < 0.001), preoperative Frankel grade A-C (AOR 3.48, 95% CI 1.17-10.3, p = 0.02), insurance status (p = 0.005), being unmarried (AOR 0.58, 95% CI 0.35-0.97, p = 0.04), number of levels (AOR 1.17 per level, 95% CI 1.05-1.31, p = 0.004), and thoracic involvement (AOR 1.71, 95% CI 1.02-2.88, p = 0.04) were also predictive of nonroutine discharge. However, race was not independently predictive of postoperative complications or prolonged LOS. Higher Charlson Comorbidity Index (AOR 1.22 per point, 95% CI 1.04-1.43, p = 0.01), low preoperative KPS score (AOR 1.84, 95% CI 1.16-2.92, p = 0.01), and number of levels (AOR 1.15 per level, 95% CI 1.05-1.27, p = 0.004) were predictive of complications, while insurance status (p = 0.05), income quartile (p = 0.01), low preoperative KPS score (AOR 1.64, 95% CI 1.03-2.72, p = 0.05), and number of levels (AOR 1.16 per level, 95% CI 1.05-1.30, p = 0.004) were predictive of prolonged LOS. Race, insurance status, age, baseline functional status, and marital status were all independently associated with nonroutine discharge. This suggests that a combination of socioeconomic factors and functional status, rather than medical comorbidities, may best predict postdischarge disposition in patients treated for spinal metastases. Further investigation in a prospective cohort is merited.

Major Surgery and Long Term Cognitive Outcomes: The Effect of Postoperative Delirium on Dementia in the Year Following Discharge

Delirium is among the most common complications following major surgery. Delirium following medical illness is associated with the development of chronic cognitive decline. The objective of this study was to determine the association of postoperative delirium with dementia in the year following surgery. This was a retrospective cohort study in a large health network (January 2013 to December 2019). All patients over age 50 undergoing surgery requiring an inpatient stay were included. Our main exposure was an episode of delirium. The primary outcome was a new dementia diagnosis in the 1 y following discharge. Secondary outcomes included hospital length of stay, non-home discharge destination, mortality and rehospitalizations in 1 y. There were 39,665 patients included, with a median age of 66. There were 4156 of 39,665 emergencies (10.5%). Specialties were general surgery (12,285/39,665, 31%) and orthopedics (11,503/39,665, 29%). There were 3327 (8.4%) patients with delirium. Delirious patients were older and were more likely to have comorbid conditions and undergone complex procedures. There were 1353 of 39,665 (3.5%) patients who developed dementia in the year following their surgery; 4930 of 39,665 (12.4%) who died; and 8200 of 39,665 (20.7%) who were readmitted. Delirium was associated with a new dementia diagnosis after adjusting for baseline characteristics (Odds ratio [OR] 13.9; 95% CI, 12.2-15.7). Similarly, delirium was also associated with 1 y mortality (OR 3.1; 95% CI 2.9-3.4) and readmission (OR 1.9, 95% CI 1.7-2.0). Postoperative delirium is the strongest factor associated with development of dementia in the year following a major operation. Strategies to prevent, identify, and treat delirium in the postoperative setting may improve long-term cognitive recovery.

268. Frailty is a better predictor than age of mortality and perioperative complications after surgery for Degenerative Cervical Myelopathy: An analysis of 41,369 patients from the NSQIP database 2010-2018

<h3>BACKGROUND CONTEXT</h3> The effect of frailty on the perioperative outcomes for patients undergoing surgery for degenerative cervical myelopathy (DCM) patients is poorly understood. <h3>PURPOSE</h3> The objective of the current study was to model the effect of various models of frailty on the perioperative outcomes for surgical DCM patients. <h3>STUDY DESIGN/SETTING</h3> Retrospective cohort study. <h3>PATIENT SAMPLE</h3> Patients under going surgery for DCM registered in the National Safety and Quality Improvment Database (NSQIP). <h3>OUTCOME MEASURES</h3> Mortality, adverse events, readmission, reoperation, length of hospital stay and discharge to nonhome destination. <h3>METHODS</h3> The modified frailty index 11- and 5-point (MFI-11, MFI-5), modified Charlson comorbidity index (mCCI) and ASA grade were calculated for patients with a diagnosis of DCM from the NSQIP database 2010-2018. The MFI-11 and MFI-5 scores were stratified into "Not Frail," "Prefrail," "Frail" and "Severely Frail." Univariate analysis was performed to assess the risk of mortality and adverse events by index. Multivariable modelling of age and frailty with a base model (type of surgical approach, number of operated levels and gender) was performed, with receiver operating characteristic area under the curve analysis (AUC) to define discriminative ability of each measure. <h3>RESULTS</h3> A total of 41,369 patients were included. Increasing frailty correlated significantly with increased risk of mortality, adverse events, longer hospital stay and risk of nonhome discharge destination. Comparing age and the other indices, the MFI-5 had the largest effect size for all variables (odds ratio 8.37 [Frail] - 27.70 [Severely Frail]). MFI-5 and mCCI have the best discriminative ability at predicting adverse events with multivariable modelling, but the base model with MFI-5 and age had the best predictive value (AUC=0.84). The effect size of frailty was greater than age alone for all outcomes, and MFI-5 had a categorical assessment correlation with MFI-11 of 0.988 (p<0.001). <h3>CONCLUSIONS</h3> Frailty has a larger effect size and better discriminative value compared to age alone to predict adverse events after surgery for DCM. A multivariable regression model using MFI-5 produced the most robust predictive tool, which substantiates the use of the MFI-5 in preference to the MFI-11 in clinical practice. <h3>FDA DEVICE/DRUG STATUS</h3> This abstract does not discuss or include any applicable devices or drugs.

Obesity and perioperative outcomes in older surgical patients undergoing elective spine and major arthroplasty surgery

Study objectiveTo determine whether obesity status is associated with perioperative complications, discharge outcomes and hospital length of stay in older surgical patients. DesignSecondary analysis of five independent study cohorts (N = 1262). SettingAn academic medical center between 2001 and 2017 in the United States. PatientsPatients aged 65 years or older who were scheduled to undergo elective spine, knee, or hip surgery with an expected hospital stay of at least 2 days. MeasurementsBody mass index (BMI) was stratified as nonobese (BMI ≤ 30 kg/m2), obesity class 1 (30 kg/m2 ≤ BMI < 35 kg/m2) or obesity class 2–3 (BMI ≥ 35 kg/m2). Primary outcomes included predefined intraoperative and postoperative complications, hospital length of stay (LOS), and discharge location. Univariate and multivariate logistic regression was performed. Main resultsObesity status was not associated with intraoperative adverse events. However, obesity class 2–3 significantly increased the risk for postoperative complications (IRR 1.43, 95% CI 1.03–1.95, P = 0.03), hospital LOS (IRR 1.13, 95% CI 1.02–1.25, P = 0.02) and non-home discharge destination (OR 1.95, 95% CI 1.35–2.81, P < 0.001) after accounting for patient related factors and surgery type. ConclusionsObesity class 2–3 status has prognostic value in predicting an increased incidence of postoperative complications, increased hospital LOS, and non-home discharge location. These results have important clinical implications for preoperative informed consent and provide areas to target for care improvement for the older obese individual.

Discharge Destination After Shoulder Arthroplasty: An Analysis of Discharge Outcomes, Placement Risk Factors, and Recent Trends.

Rates of shoulder arthroplasty continue to increase. Factors influencing disposition and the effect discharge destination may have on perioperative outcomes are currently unknown. This study (1) investigates patients undergoing total shoulder arthroplasty subsequently discharged to home, skilled nursing facilities, and or independent rehabilitation facilities; (2) identifies differences in perioperative outcomes; and (3) investigates the risk of adverse events and readmission after nonhome disposition. The American College of Surgeons National Surgical Quality Improvement Program database was queried for patients undergoing total shoulder arthroplasty from 2013 to 2018. Bivariate and multivariate analyses were conducted to determine the relationship between patient characteristics and risks of discharge to a non-home destination, discharge to an independent rehabilitation facility as opposed to a skilled nursing facility, severe postdischarge adverse events, and unplanned readmission. Factors associated with discharge to a non-home facility included those older than 85 years of age (odds ratio [OR], 14.38), dialysis requirement (OR, 4.16), transfer from a non-home facility (OR, 3.69), dependent functional status (OR, 3.17), female sex (OR, 2.78), history of congestive heart failure (2.05), American Society of Anesthesiologists class >2 (OR, 1.97), longer length of stay (OR, 1.47), and body mass index >35 (OR, 1.29) (P < 0.05). Patients discharged to a non-home facility had an approximately quadrupled rate of both major adverse events (8.6% vs 2.4%, P < 0.001) and minor adverse events (6.1% vs 1.4%, P < 0.001). Discharge to a non-home facility had a higher likelihood of a severe adverse event (OR, 1.82, P = 0.029) or unplanned readmission (OR, 1.60, P = 0.001). Non-home discharge destination demonstrated a notable negative impact on postoperative outcomes independent of medical complexity. Preoperative management of modifiable risk factors may decrease length of inpatient stay, rates of disposition to non-home facilities, and total cost of care. The benefit of more intense postoperative management at a non-home discharge destination must be carefully weighed against the independent risk of postoperative adverse events and readmissions.

Frailty Is a Better Predictor than Age of Mortality and Perioperative Complications after Surgery for Degenerative Cervical Myelopathy: An Analysis of 41,369 Patients from the NSQIP Database 2010-2018.

Background: The ability of frailty compared to age alone to predict adverse events in the surgical management of Degenerative Cervical Myelopathy (DCM) has not been defined in the literature. Methods: 41,369 patients with a diagnosis of DCM undergoing surgery were collected from the National Surgical Quality Improvement Program (NSQIP) Database 2010–2018. Univariate analysis for each measure of frailty (modified frailty index 11- and 5-point; MFI-11, MFI-5), modified Charlson Co-morbidity index and ASA grade) were calculated for the following outcomes: mortality, major complication, unplanned reoperation, unplanned readmission, length of hospital stay, and discharge to a non-home destination. Multivariable modeling of age and frailty with a base model was performed to define the discriminative ability of each measure. Results: Age and frailty have a significant effect on all outcomes, but the MFI-5 has the largest effect size. Increasing frailty correlated significantly with the risk of perioperative adverse events, longer hospital stay, and risk of a non-home discharge destination. Multivariable modeling incorporating MFI-5 with age and the base model had a robust predictive value (0.85). MFI-5 had a high categorical assessment correlation with a MFI-11 of 0.988 (p < 0.001). Conclusions and Relevance: Measures of frailty have a greater effect size and a higher discriminative value to predict adverse events than age alone. MFI-5 categorical assessment is essentially equivalent to the MFI-11 score for DCM patients. A multivariable model using MFI-5 provides an accurate predictive tool that has important clinical applications.

Stroke prognostication for discharge planning with machine learning: A derivation study

Post-stroke discharge planning may be aided by accurate early prognostication. Machine learning may be able to assist with such prognostication. The study’s primary aim was to evaluate the performance of machine learning models using admission data to predict the likely length of stay (LOS) for patients admitted with stroke. Secondary aims included the prediction of discharge modified Rankin Scale (mRS), in-hospital mortality, and discharge destination. In this study a retrospective dataset was used to develop and test a variety of machine learning models. The patients included in the study were all stroke admissions (both ischaemic stroke and intracerebral haemorrhage) at a single tertiary hospital between December 2016 and September 2019. The machine learning models developed and tested (75%/25% train/test split) included logistic regression, random forests, decision trees and artificial neural networks. The study included 2840 patients. In LOS prediction the highest area under the receiver operator curve (AUC) was achieved on the unseen test dataset by an artificial neural network at 0.67. Higher AUC were achieved using logistic regression models in the prediction of discharge functional independence (mRS ≤2) (AUC 0.90) and in the prediction of in-hospital mortality (AUC 0.90). Logistic regression was also the best performing model for predicting home vs non-home discharge destination (AUC 0.81). This study indicates that machine learning may aid in the prognostication of factors relevant to post-stroke discharge planning. Further prospective and external validation is required, as well as assessment of the impact of subsequent implementation.

Discharge destination following rectal cancer resection: an analysis of preoperative and intraoperative factors.

Rectal cancer resections can be associated with long and complicated postoperative recoveries. Many patients undergoing these operations are discharged to rehabilitation or skilled nursing facilities. The purpose of this study was to identify preoperative and intraoperative factors associated with increased risk for non-home discharge after rectal cancer resection. Rectal cancer resections were identified in the National Surgical Quality Improvement Program Targeted Proctectomy Dataset (years 2016 through 2017) by ICD code. Patients with unknown discharge destination or who experienced in-hospital mortality were excluded. Univariate and multivariate logistic regression analyses were performed to identify preoperative and intraoperative variables associated with non-home discharge destination. Multiple imputation was used to account for missing values. Among the 3637 patients comprising the study sample, 292 (8.0%) patients were discharged to rehabilitation, skilled care, or acute care facilities. Preoperative factors associated with non-home discharge on multivariate analysis included older age, non-independent functional status, insulin-dependent diabetes, and hypoalbuminemia (all p < 0.05). Having received neoadjuvant chemotherapy was associated with home discharge (OR 0.625, 95% CI 0.427-0.914, p = 0.015). Intraoperative factors associated with non-home discharge on multivariate analysis were concurrent cystectomy (p = 0.004) and myocutaneous flap reconstruction (p < 0.001). Patients discharged to non-home facilities had longer initial lengths of stay (14.1 versus 7.0days, p < 0.001) and higher reoperation rates (12.7 versus 5.0%, p < 0.001), but similar readmission rates (14.7 versus 15.0%, p = 1.0). Several preoperative and intraoperative factors are associated with increased risk for non-home discharge after rectal cancer resection. These data can aid in perioperative planning and discharge optimization.

Analysis of Discharge Destination After Open Versus Minimally Invasive Surgery for Lung Cancer

Patients express strong opinion regarding discharge destination, preferring discharge home vs elsewhere. As focus on patient satisfaction increases, we sought to understand differences in postoperative discharge destination after minimally invasive vs open anatomic lung resection for lung cancer to guide patient education and management and better understand the postoperative patient experience. Procedures were identified by Current Procedural Terminology and International Classification of Diseases codes using the 2012-2017 American College of Surgeons National Surgical Quality Improvement Program dataset. Propensity score analysis was used to assess the relationship between the surgical approach and nonhome discharge destination (primary outcome) and postoperative complications; related, unplanned readmission; and mortality (secondary outcomes). A total of 17,303 patients underwent anatomic lung resection for lung cancer, including 10,121 (58.5%) minimally invasive and 7182 (41.5%) open resections. Patients undergoing open resection had 60% greater odds of nonhome discharge (P < .001), 58% greater odds of postoperative mortality (P= .003), 36% greater odds of postoperative complication (P < .001), and 17% greater odds of readmission (P= .04) compared with patients undergoing minimally invasive resection. The minimally invasive approach to lung resection for lung cancer offers patients a more desirable patient-centered postoperative experience, as well as more favorable clinical outcomes, and should be favored when feasible.

Prediction of Discharge Destination Following Major Hepatectomy

BackgroundAnatomic hepatectomies can be associated with complicated post-operative recoveries, often with discharge to post-acute care facilities. This study identifies preoperative and intraoperative factors associated with increased risk for non-home discharge destination after major hepatectomy. MethodsPatients undergoing major hepatectomy were identified in the NSQIP Targeted Hepatectomy Dataset (2014–2016). Multivariable logistic regression was performed. Patients from 2014 to 2015 were used for training cohort with nomogram generation and 2016 for validation cohort. ResultsOverall, 226 of 3750 patients (6.0%) were discharged to rehab, skilled care, or acute care facilities. Preoperative factors associated with non-home discharge on multivariable analysis were outside patient transfers, older age, presence of ascites, ASA physical status 3 or higher, and low preoperative hematocrit (all p < 0.05). Intraoperative factors significantly predictive were concurrent lysis of adhesions, Pringle maneuver, and biliary reconstruction (all p < 0.05). Predictors from testing cohort were validated in validation cohort. Nomograms based on preoperative variables alone and both preoperative and intraoperative variables were generated. ConclusionWe identify several preoperative and intraoperative factors that are associated with increased risk for non-home discharge after major hepatectomy. Preoperative anemia represents a potentially modifiable risk factor. Nomograms for preoperative planning as well as immediately following surgery were generated.

Non-home discharge disposition after posterior spinal fusion in neuromuscular scoliosis-an analysis of the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) Pediatric database.

Despite an increasing trend of corrective surgery in patients with neuromuscular scoliosis, evidence regarding risk factors associated with non-home discharge destination following surgery remains limited. The 2012-2016 American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) Pediatric database was queried using Current Procedural Terminology codes for patients undergoing posterior spinal fusion (22802, 22804 and 22808) for neuromuscular scoliosis. Non-home discharge was defined as discharge to a skilled nursing facility, rehabilitation facility and/or separate acute care unit. Patients who expired during inpatient stay were excluded from the study sample. Only patients aged 2-18 years with a primary diagnosis of neuromuscular scoliosis were included in the final cohort. Out of a total of 1,269 patients, 76 (6.0%) had a non-home discharge disposition. Following adjustment for baseline clinical characteristics, patients lying in the age bracket of 15-17 years {odds ratio (OR) 2.27 [95% confidence interval (CI): 1.01-5.08]; P=0.047} or >17 years [OR 2.29 (95% CI: 1.10-4.79); P=0.027], male gender [OR 1.75 (95% CI: 1.06-2.89); P=0.029], having structural pulmonary abnormality at time of surgery [OR 2.01 (95% CI: 1.17-3.43); P=0.011], a length of stay >4 days [OR 2.29 (95% CI: 1.15-4.55); P=0.018] and having a past history of childhood cancer [OR 4.50 (95% CI: 1.15-17.61); P=0.031] were significant independent predictors associated with a non-home discharge. Providers can utilize these data to pre-operatively identify patients who might require continued high-level/inpatient care in a facility, and subsequently expedite discharge and reduce costs associated with a prolonged inpatient stay.

30-day adverse events, length of stay and re-admissions following surgical management of pelvic/acetabular fractures

IntroductionPelvic/acetabular fractures are associated with significant morbidity, mortality and cost to the society. We sought to utilize a national surgical database to assess the incidence and factors associated with prolonged length of stay (LOS), non-home discharge destination, 30-day adverse events and readmissions following surgical fixation of pelvic/acetabular fractures. Materials & methodsThe 2011–2016 ACS-NSQIP database files were queried using CPT codes (27215, 27217, 27218, 27226, 27227, 27228) for patients undergoing open reduction/internal fixation (ORIF) for pelvic/acetabular fractures. Patients undergoing additional procedures for associated fractures (vertebral fractures, distal radius/ulna fractures or femoral neck/hip fractures) were excluded from the analysis to ensure that a relevant population of patients with isolated pelvic/acetabular injuries were included in the analysis. A total of 572 patients were included in the final cohort. Severe adverse events (SAE) were defined as: death, ventilator use >48 h, unplanned intubation, stroke, deep venous thrombosis, pulmonary embolism, cardiac arrest, myocardial infarction, acute renal failure, sepsis, septic shock, re-operation, deep SSI and organ/space SSI. Minor adverse events (MAE) included – wound dehiscence, superficial SSI, urinary tract infection (UTI) and progressive renal insufficiency. An extended LOS was defined as >75th centile (>9days). ResultsFactors associated with AAE were partially dependent functional health status pre-operatively (p = 0.020), transfusion ≥1 unit of packed RBCs (p = 0.001), and ASA > II (p < 0.001). Experiencing a SAE was associated with congestive heart failure (CHF) pre-operatively [p = 0.005), total operative time >140 min (p = 0.034) and Hct <36 pre-operatively (p = 0.003). MAE was associated with transfusion≥1 unit of packed RBCs (p = 0.022) and ASA > II (p = 0.007). Patients with an ASA > II (p = 0.001), total operative time>140 min (p < 0.001) and Hct <36 (p = 0.006) were more likely to have a LOS >9 days. Male gender (p = 0.026), prior history of CHF (p = 0.024), LOS >9 days (p = 0.030) and >10% bodyweight loss in last 6 months before the procedure (p = 0.002) were predictors of 30-day mortality. ConclusionPatients with ASA grade > II, greater co-morbidity burden and prolonged operative times were likely to experience adverse events and have a longer length of stay. Surgeons can utilize this data to risk stratify patients so that appropriate pre-operative and post-operative medical optimization can take place.