A comparison of medium-term heat acclimation by post-exercise hot water immersion or exercise in the heat: adaptations, overreaching, and thyroid hormones.

This research compared thermal and perceptual adaptations, endurance capacity, and overreaching markers in men after 3, 6, and 12 days of post-exercise hot water immersion (HWI) or exercise heat acclimation (EHA) with a temperate exercise control (CON), and examined thyroid hormones as a mechanism for the reduction in resting and exercising core temperature (Tre) after HWI. HWI involved a treadmill run at 65% V̇o2peak at 19°C followed by a 40°C bath. EHA and CON involved a work-matched treadmill run at 65% V̇o2peak at 33°C or 19°C, respectively. Compared with CON, resting mean body temperature (Tb), resting and end-exercise Tre, Tre at sweating onset, thermal sensation, and perceived exertion were lower and whole-body sweat rate (WBSR) was higher after 12 days of HWI (all P ≤ 0.049, resting Tb: CON -0.11 ± 0.15°C, HWI -0.41 ± 0.15°C). Moreover, resting Tb and Tre at sweating onset were lower after HWI than EHA (P ≤ 0.015, resting Tb: EHA -0.14 ± 0.14°C). No differences were identified between EHA and CON (P ≥ 0.157) except WBSR that was greater after EHA (P = 0.013). No differences were observed between interventions for endurance capacity or overreaching markers (mood, sleep, Stroop, P ≥ 0.190). Thermal adaptations observed after HWI were not related to changes in thyroid hormone concentrations (P ≥ 0.086). In conclusion, 12 days of post-exercise hot water immersion conferred more complete heat acclimation than exercise heat acclimation without increasing overreaching risk, and changes in thyroid hormones are not related to thermal adaptations after post-exercise hot water immersion.

The Critical Intervention Screen: A Novel Tool to Determine the Use of Lights and Sirens during the Transport of Trauma Patients.

Objective: EMS use of lights and sirens has long been employed in EMS systems, despite an increased risk of motor vehicle collisions associated with their use. The specific aims of this study were to assess the current use of lights and sirens during the transport of trauma patients in a busy metropolitan area and to subsequently develop a novel tool, the Critical Intervention Screen, to aid EMS professionals tasked with making transport decisions in the presence of acute injury.Methods: This single-center, retrospective study included all patients transported to an academic Level One trauma center by ground ambulance from the scene of presumed or known injury. A subset of patients was identified as being most likely to benefit from shorter transport times if they received one of the following critical interventions within 20 minutes of emergency department arrival: intubation, thoracotomy, chest tube, blood products, central line, arterial line, REBOA, disposition to an operating room, or death. Stepwise logistic regression was employed for the development of the Critical Intervention Screen, with a subset of data retained for internal validation.Results: 1296 patients were available for analysis. Overall, 217 patients (16.7%) received a critical intervention, and 112 patients (8.6%) of those patients received a critical intervention within 20 minutes of emergency department arrival. At baseline, EMS use of lights and sirens was 91.1% sensitive and 80.3% specific for receiving a critical intervention. Stepwise logistic regression demonstrated that the need for assisted ventilation, GCS Motor < 6, and penetrating trauma to the trunk were the most predictive prehospital data for receiving at least one critical intervention. The Critical Intervention Screen, defined as having at least one of these risk factors in the prehospital setting, modestly increased sensitivity and specificity (96.4% and 87.9%, respectively) predicting the need for a critical intervention.Conclusion: These findings indicate that EMS are able to correctly identify high-acuity trauma patients, but at times employ L&S during the transport of patients with a low likelihood of receiving a time-sensitive intervention upon emergency department arrival. Therefore, the Critical Intervention Screen has the potential to reduce the use of lights and sirens and improve EMS safety.

Prediction of Opioid-Induced Respiratory Depression on Inpatient Wards Using Continuous Capnography and Oximetry: An International Prospective, Observational Trial.

BACKGROUND: Opioid-related adverse events are a serious problem in hospitalized patients. Little is known about patients who are likely to experience opioid-induced respiratory depression events on the general care floor and may benefit from improved monitoring and early intervention. The trial objective was to derive and validate a risk prediction tool for respiratory depression in patients receiving opioids, as detected by continuous pulse oximetry and capnography monitoring. METHODS: PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY (PRODIGY) was a prospective, observational trial of blinded continuous capnography and oximetry conducted at 16 sites in the United States, Europe, and Asia. Vital signs were intermittently monitored per standard of care. A total of 1335 patients receiving parenteral opioids and continuously monitored on the general care floor were included in the analysis. A respiratory depression episode was defined as respiratory rate ≤5 breaths/min (bpm), oxygen saturation ≤85%, or end-tidal carbon dioxide ≤15 or ≥60 mm Hg for ≥3 minutes; apnea episode lasting >30 seconds; or any respiratory opioid-related adverse event. A risk prediction tool was derived using a multivariable logistic regression model of 46 a priori defined risk factors with stepwise selection and was internally validated by bootstrapping. RESULTS: One or more respiratory depression episodes were detected in 614 (46%) of 1335 general care floor patients (43% male; mean age, 58 ± 14 years) continuously monitored for a median of 24 hours (interquartile range [IQR], 17-26). A multivariable respiratory depression prediction model with area under the curve of 0.740 was developed using 5 independent variables: age ≥60 (in decades), sex, opioid naivety, sleep disorders, and chronic heart failure. The PRODIGY risk prediction tool showed significant separation between patients with and without respiratory depression (P < .001) and an odds ratio of 6.07 (95% confidence interval [CI], 4.44-8.30; P < .001) between the high- and low-risk groups. Compared to patients without respiratory depression episodes, mean hospital length of stay was 3 days longer in patients with ≥1 respiratory depression episode (10.5 ± 10.8 vs 7.7 ± 7.8 days; P < .0001) identified using continuous oximetry and capnography monitoring. CONCLUSIONS: A PRODIGY risk prediction model, derived from continuous oximetry and capnography, accurately predicts respiratory depression episodes in patients receiving opioids on the general care floor. Implementation of the PRODIGY score to determine the need for continuous monitoring may be a first step to reduce the incidence and consequences of respiratory compromise in patients receiving opioids on the general care floor.

Postoperative hemorrhage secondary to acquired hemophilia A.

Acquired hemophilia A in postoperative patients can cause major bleeding and an accurate diagnosis is required for effective treatment. Standard treatment is costly, difficult to obtain, and takes 4 to 6 weeks to be effective. This article describes a patient successfully treated with recombinant factor VIIa, porcine factor VIII, plasmapheresis, rituximab, and high-dose corticosteroids.

Premeditated versus "passionate": patterns of homicide related to intimate partner violence.

BACKGROUND: Intimate partner violence (IPV) is prevalent but underrecognized; at least 25% of United States women experience IPV within their lifetime. We examined the most severe consequence of IPV by exploring the patterns of death from IPV in a statewide database of homicide victims. MATERIALS AND METHODS: This is a retrospective review of the Colorado Violent Death Reporting System from 2004 to 2015. Deaths were coded as IPV if the primary relationship between the suspect and victim fell into the following categories: spouse, ex-spouse, girlfriend/boyfriend, and ex-girlfriend/ex-boyfriend. RESULTS: We identified a total of 2279 homicide victims, with 295 cases of IPV homicide (12.9%). The majority was female victims of a male partner (n = 240, 81.4%). In nearly half of these (n = 108, 45%), the male suspect subsequently died by suicide as part of the same incident. These homicide-suicide incidents were more likely than homicide alone to involve a spousal relationship, more likely to involve firearms and less likely to involve intoxication or preceding arguments. They had a distinct demographic profile from other victims of IPV, mirroring suicide victims in terms of race and estimated income. CONCLUSIONS: These results indicate that there are two distinct groups of female IPV homicides, and recognizing this distinction may allow for the development of more effective trauma prevention strategies. Homicide-suicides showed a more premeditated pattern while homicide alone suggested a crime of passion, with a smaller proportion of firearm deaths and higher rates of positive toxicology findings and preceding conflict in the latter group.

Multicenter Study Validating Accuracy of a Continuous Respiratory Rate Measurement Derived From Pulse Oximetry: A Comparison With Capnography.

BACKGROUND: Intermittent measurement of respiratory rate via observation is routine in many patient care settings. This approach has several inherent limitations that diminish the clinical utility of these measurements because it is intermittent, susceptible to human error, and requires clinical resources. As an alternative, a software application that derives continuous respiratory rate measurement from a standard pulse oximeter has been developed. We sought to determine the performance characteristics of this new technology by comparison with clinician-reviewed capnography waveforms in both healthy subjects and hospitalized patients in a low-acuity care setting. METHODS: Two independent observational studies were conducted to validate the performance of the Medtronic Nellcor Respiration Rate Software application. One study enrolled 26 healthy volunteer subjects in a clinical laboratory, and a second multicenter study enrolled 53 hospitalized patients. During a 30-minute study period taking place while participants were breathing spontaneously, pulse oximeter and nasal/oral capnography waveforms were collected. Pulse oximeter waveforms were processed to determine respiratory rate via the Medtronic Nellcor Respiration Rate Software. Capnography waveforms reviewed by a clinician were used to determine the reference respiratory rate. RESULTS: A total of 23,243 paired observations between the pulse oximeter-derived respiratory rate and the capnography reference method were collected and examined. The mean reference-based respiratory rate was 15.3 ± 4.3 breaths per minute with a range of 4 to 34 breaths per minute. The Pearson correlation coefficient between the Medtronic Nellcor Respiration Rate Software values and the capnography reference respiratory rate is reported as a linear correlation, R, as 0.92 ± 0.02 (P < .001), whereas Lin's concordance correlation coefficient indicates an overall agreement of 0.85 ± 0.04 (95% confidence interval [CI] +0.76; +0.93) (healthy volunteers: 0.94 ± 0.02 [95% CI +0.91; +0.97]; hospitalized patients: 0.80 ± 0.06 [95% CI +0.68; +0.92]). The mean bias of the Medtronic Nellcor Respiration Rate Software was 0.18 breaths per minute with a precision (SD) of 1.65 breaths per minute (healthy volunteers: 0.37 ± 0.78 [95% limits of agreement: -1.16; +1.90] breaths per minute; hospitalized patients: 0.07 ± 1.99 [95% limits of agreement: -3.84; +3.97] breaths per minute). The root mean square deviation was 1.35 breaths per minute (healthy volunteers: 0.81; hospitalized patients: 1.60). CONCLUSIONS: These data demonstrate the performance of the Medtronic Nellcor Respiration Rate Software in healthy subjects and patients hospitalized in a low-acuity care setting when compared with clinician-reviewed capnography. The observed performance of this technology suggests that it may be a useful adjunct to continuous pulse oximetry monitoring by providing continuous respiratory rate measurements. The potential patient safety benefit of using combined continuous pulse oximetry and respiratory rate monitoring warrants assessment.

Aldehyde-stabilized cryopreservation.

We describe here a new cryobiological and neurobiological technique, aldehyde-stabilized cryopreservation (ASC), which demonstrates the relevance and utility of advanced cryopreservation science for the neurobiological research community. ASC is a new brain-banking technique designed to facilitate neuroanatomic research such as connectomics research, and has the unique ability to combine stable long term ice-free sample storage with excellent anatomical resolution. To demonstrate the feasibility of ASC, we perfuse-fixed rabbit and pig brains with a glutaraldehyde-based fixative, then slowly perfused increasing concentrations of ethylene glycol over several hours in a manner similar to techniques used for whole organ cryopreservation. Once 65% w/v ethylene glycol was reached, we vitrified brains at -135 °C for indefinite long-term storage. Vitrified brains were rewarmed and the cryoprotectant removed either by perfusion or gradual diffusion from brain slices. We evaluated ASC-processed brains by electron microscopy of multiple regions across the whole brain and by Focused Ion Beam Milling and Scanning Electron Microscopy (FIB-SEM) imaging of selected brain volumes. Preservation was uniformly excellent: processes were easily traceable and synapses were crisp in both species. Aldehyde-stabilized cryopreservation has many advantages over other brain-banking techniques: chemicals are delivered via perfusion, which enables easy scaling to brains of any size; vitrification ensures that the ultrastructure of the brain will not degrade even over very long storage times; and the cryoprotectant can be removed, yielding a perfusable aldehyde-preserved brain which is suitable for a wide variety of brain assays.

The Role of Dietary Intake in the Weight Loss Outcomes of Roux-en-Y Gastric Bypass and Sleeve Gastrectomy: A Systematic Review and Meta-analysis.

The relationship between postoperative dietary intake and weight loss after bariatric surgery remains unclear. We performed a systematic review and meta-analysis of studies published between January 2000 and May 2023, reporting weight loss outcomes, and dietary intake before and after Roux-en-Y gastric bypass and sleeve gastrectomy. A total of 42 studies were included. There was no detectable difference in dietary intake between the two procedures. Roux-en-Y gastric bypass induced an average decrease in energy intake of 886 kcal/day at 12-month post-surgery; however, there was no correlation between daily energy intake and weight loss. These findings show a substantial reduction of energy intake in the first year after bariatric surgery but do not support a link between lower energy intake and greater weight loss.

High-grade liver injuries with contrast extravasation managed initially with interventional radiology versus observation: A secondary analysis of a WTA multicenter study.

BACKGROUND: High-grade liver injuries with extravasation (HGLI â€‹+ â€‹Extrav) are associated with morbidity/mortality. For low-grade injuries, an observation (OBS) first-strategy is beneficial over initial angiography (IR), however, it is unclear if OBS is safe for HGLI â€‹+ â€‹Extrav. Therefore, we evaluated the management of HGLI â€‹+ â€‹Extrav patients, hypothesizing IR patients will have decreased rates of operation and mortality. METHODS: HGLI â€‹+ â€‹Extrav patients managed with initial OBS or IR were included. The primary outcome was need for operation. Secondary outcomes included liver-related complications (LRCs) and mortality. RESULTS: From 59 patients, 23 (39.0%) were managed with OBS and 36 (61.0%) with IR. 75% of IR patients underwent angioembolization, whereas 13% of OBS patients underwent any IR, all undergoing angioembolization. IR patients had an increased rate of operation (13.9% vs. 0%, p â€‹= â€‹0.049), but no difference in LRCs (44.4% vs. 43.5%) or mortality (5.6% vs. 8.7%) versus OBS patients (both p â€‹> â€‹0.05). CONCLUSION: Over 60% of patients were managed with IR initially. IR patients had an increased rate of operation yet similar rates of LRCs and mortality, suggesting initial OBS reasonable in appropriately selected HGLI â€‹+ â€‹Extrav patients.

Computer-Assisted Levothyroxine Dose Selection for the Treatment of Postoperative Hypothyroidism.

Background: Thyroid hormone replacement with levothyroxine (LT4) is a recommended treatment for patients undergoing thyroidectomy. The starting LT4 dose is frequently calculated based on the patient's weight. However, the weight-based LT4 dosing performs poorly in clinical practice, with only ∼30% of patients achieving target thyrotropin (TSH) levels at the first thyroid function testing after treatment initiation. A better way to calculate the LT4 dose for patients with postoperative hypothyroidism is needed. Methods: In this retrospective cohort study we used demographic, clinical, and laboratory data for 951 patients after thyroidectomy and several regression and classification machine learning methods to develop an LT4 dose calculator for treating postoperative hypothyroidism targeting the desired TSH level. We compared the accuracy with the current standard-of-care practice and other published algorithms and evaluated generalizability with fivefold cross-validation and out-of-sample testing. Results: The retrospective clinical chart review showed that only 285/951 (30%) patients met their postoperative TSH goal. Obese patients were overtreated with LT4. An ordinary least squares regression based on weight, height, age, sex, calcium supplementation, and height:sex interaction predicted prescribed LT4 dose in 43.5% of all patients and 45.3% of patients with normal postoperative TSH (0.45-4.5 mIU/L). The ordinal logistic regression, artificial neural networks regression/classification, and random forest methods achieved comparable performance. LT4 calculator recommended lower LT4 doses to obese patients. Conclusions: The standard-of-care LT4 dosing does not achieve the target TSH in most thyroidectomy patients. Computer-assisted LT4 dose calculation performs better by considering multiple relevant patient characteristics and providing personalized and equitable care to patients with postoperative hypothyroidism. Prospective validation of LT4 calculator performance in patients with various TSH goals is needed.

Prehospital ETCO2 is predictive of death in intubated and non-intubated patients.

BACKGROUND: Prehospital identification of shock in trauma patients lacks accurate markers. Low end tidal carbon dioxide (ETCO2) correlates with mortality in intubated patients. The predictive value of ETCO2 obtained by nasal capnography cannula (NCC) is unknown. We hypothesized that prehospital ETCO2 values obtained by NCC and in-line ventilator circuit (ILVC) would be predictive of mortality. METHODS: This was a prospective, observational, multicenter study. ETCO2 values were collected by a NCC or through ILVC. AUROCs were compared with prehospital systolic blood pressure (SBP) and shock index (SI). The Youden index defined optimal cutoffs. RESULTS: Of 550 enrolled patients, 487 (88.5%) had ETCO2 measured through an NCC. Median age was 37 (27-52) years; 76.5% were male; median ISS was 13 (5-22). Mortality was 10.4%. Minimum prehospital ETCO2 significantly predicted mortality with an AUROC of 0.76 (CI 0.69-0.84; Youden index â€‹= â€‹22 â€‹mmHg), outperforming SBP with an AUROC of 0.68; (CI 0.62-0.74, p â€‹= â€‹0.04) and shock index with an AUROC of 0.67 (CI 0.59-0.74, p â€‹= â€‹0.03). CONCLUSION: Prehospital ETCO2 measured by non-invasive NCC or ILVC may be predictive of mortality in injured patients.

Global Diabetes Prevalence in COVID-19 Patients and Contribution to COVID-19- Related Severity and Mortality: A Systematic Review and Meta-analysis.

BACKGROUND: COVID-19 and diabetes both contribute to large global disease burdens. PURPOSE: To quantify the prevalence of diabetes in various COVID-19 disease stages and calculate the population attributable fraction (PAF) of diabetes to COVID-19-related severity and mortality. DATA SOURCES: Systematic review identified 729 studies with 29,874,938 COVID-19 patients. STUDY SELECTION: Studies detailed the prevalence of diabetes in subjects with known COVID-19 diagnosis and severity. DATA EXTRACTION: Study information, COVID-19 disease stages, and diabetes prevalence were extracted. DATA SYNTHESIS: The pooled prevalence of diabetes in stratified COVID-19 groups was 14.7% (95% CI 12.5-16.9) among confirmed cases, 10.4% (7.6-13.6) among nonhospitalized cases, 21.4% (20.4-22.5) among hospitalized cases, 11.9% (10.2-13.7) among nonsevere cases, 28.9% (27.0-30.8) among severe cases, and 34.6% (32.8-36.5) among deceased individuals, respectively. Multivariate metaregression analysis explained 53-83% heterogeneity of the pooled prevalence. Based on a modified version of the comparative risk assessment model, we estimated that the overall PAF of diabetes was 9.5% (7.3-11.7) for the presence of severe disease in COVID-19-infected individuals and 16.8% (14.8-18.8) for COVID-19-related deaths. Subgroup analyses demonstrated that countries with high income levels, high health care access and quality index, and low diabetes disease burden had lower PAF of diabetes contributing to COVID-19 severity and death. LIMITATIONS: Most studies had a high risk of bias. CONCLUSIONS: The prevalence of diabetes increases with COVID-19 severity, and diabetes accounts for 9.5% of severe COVID-19 cases and 16.8% of deaths, with disparities according to country income, health care access and quality index, and diabetes disease burden.

To observe or not to observe: Evaluation of the modified brain injury guideline management of small volume intracranial hemorrhage.

INTRODUCTION: Patients with small volume intracranial hemorrhage (ICH) are categorized as modified Brain Injury Guidelines (mBIG) 1 and are managed with a 6-h emergency department (ED) observation period. The current study aimed to describe the mBIG 1 patient population and determine the utility of the ED observation period. METHODS: A retrospective analysis was performed on trauma patients with small volume ICH. Exclusion criteria were Glasgow Coma Scale (GCS) < 13 and penetrating injuries. RESULTS: 359 patients were identified over the 8-year study period. The most common ICH was SDH (52.7%) followed by SAH (50.1%). Two patients (0.56%) had neurologic deterioration, but neither had radiographic progression. Overall, 14.3% of the cohort had radiographic progression; none required neurosurgical intervention. Four patients (1.1%) had readmission related to TBI from the index admission. CONCLUSION: There were no patients with small volume ICH that required neurosurgical intervention despite a small subset of patients having radiographic or clinical deterioration. Patients who meet the mBIG 1 criteria may be managed safely without an ED observation period.

An observation-first strategy for liver injuries with "blush" on computed tomography is safe and effective.

INTRODUCTION: The management of liver injuries in hemodynamically stable patients is variable and includes primary treatment strategies of observation (OBS), angiography (interventional radiology [IR]) with angioembolization (AE), or operative intervention (OR). We aimed to evaluate the management of patients with liver injuries with active extravasation on computed tomography (CT) imaging, hypothesizing that AE will have more complications without improving outcomes compared with OBS. METHODS: This is a prospective, multicenter, observational study. Patients who underwent CT within 2 hours after arrival with extravasation (e.g., blush) on imaging were included. Exclusion criteria included cirrhosis, nontraumatic hemorrhage, transfers from outside facilities, and pregnancy. No hemodynamic exclusion criteria were used. The primary outcome was liver-specific complications. Secondary outcomes include length of stay and mortality. Angioembolization patients were compared with patients treated without AE. Propensity score matching was used to match based on penetrating mechanism, liver injury severity, arrival vital signs, and early transfusion. RESULTS: Twenty-three centers enrolled 192 patients. Forty percent of patients (n = 77) were initially OBS. Eleven OBS patients (14%) failed nonoperative management and went to IR or OR. Sixty-one patients (32%) were managed with IR, and 42 (69%) of these had AE as an initial intervention. Fifty-four patients (28%) went to OR+/- IR. After propensity score matching (n = 34 per group), there was no difference in baseline characteristics between AE and OBS. The AE group experienced more complications with a higher rate of IR-placed drains for abscess or biloma (22% vs. 0%, p = 0.01) and an increased overall length of stay ( p = 0.01). No difference was noted in transfusions or mortality. CONCLUSION: Observation is highly effective with few requiring additional interventions. Angioembolization was associated with higher rate of secondary drain placement for abscesses or biloma. Given this, a trial of OBS and avoidance of empiric AE may be warranted in hemodynamically stable, liver-injured patient with extravasation on CT. LEVEL OF EVIDENCE: Therapeutic/Care Management; Level II.

Disparate resource allocation during the COVID-19 pandemic among trauma centers: A Western Trauma Association national survey.

BACKGROUND: During the pandemic, hospitals implemented disaster plans to conserve resources while maintaining patient care. It was unclear how these plans impacted injury care and trauma surgeons. STUDY DESIGN: A 16 question survey assessing COVID-related hospital policy and resource allocation pre-COVID-19 peak (March), and a 19 question post-peak (June) survey was distributed to Trauma/Critical Care attending's via social media and the Western Trauma Association member email list. RESULTS: There were 120 pre- and 134 post-peak respondents. Most (95%) altered trauma PPE components, a nd 67% noted changes in their admission population pre-peak while 80% did so post-peak. Penetrating injury increased 56% at Level 1 centers and 27% at Level 2 centers. Altered ICU and transfusion criteria were noted with 25% relocating TBI patients, 17% revised rib fracture admission criteria, and 23% adjusted transfusion practices. Importantly, 12% changed their massive transfusion protocol, with 11% reducing the symptomatic transfusion threshold from 7 g/dL to 6 g/dL. Half (50%) disclosed impediments to patient care including PPE shortages and COVID test-related procedural delay (Fig. 2). While only 14% felt their institution was overwhelmed by COVID, the vast majority (81%) shared durable concerns about personal health and safety. CONCLUSIONS: Disparate approaches to COVID-19 preparedness and response characterize survey respondent facility actions. These disparities, especially between Level 1 and Level 2 centers, represent opportunities for the trauma community to coordinate best-practice planning and implementation in light of future consequence infection or pandemic care.

Social vulnerability is associated with increased morbidity following colorectal surgery.

INTRODUCTION: Neighborhood measures of social vulnerability encompassing multiple sociodemographic factors can be used to quantify disparities in outcomes. We hypothesize patients with high Social Vulnerability Index (SVI) are at increased risk of morbidity following colectomy. METHODS: We used local 2012-2017 National Surgical Quality Improvement Program (NSQIP) data to study colectomy patients, examining associations between SVI and postoperative outcomes. RESULTS: We included 976 patients from five hospitals. High SVI (>75th percentile) was associated with increased postoperative morbidity on unadjusted analysis (OR 1.84, 95% CI 1.35-2.52, p < 0.001); this association persisted after adjusting for demographics and comorbidities (OR 1.63, 95% CI 1.15-2.31, p = 0.005). The association with SVI was not significant after adjusting for perioperative risk modifiers such as emergent presentation (OR 1.37, 95% CI 0.95-1.98, p = 0.10). CONCLUSIONS: High social vulnerability is associated with increased postoperative complications. This effect appears mediated by perioperative risk factors, suggesting potential to improve outcomes by facilitating timely surgical intervention.

Development and validation of a prediction model for conversion of outpatient to inpatient surgery.

BACKGROUND: Unplanned hospital admission after intended outpatient surgery is an undesirable outcome. We aimed to develop a prediction model that estimates a patient's risk of conversion from outpatient surgery to inpatient hospitalization. METHODS: This was a retrospective analysis using the American College of Surgeons National Surgical Quality Improvement Program database, 2005 to 2018. Conversion from outpatient to inpatient surgery was defined as having outpatient surgery and >1 day hospital stay. The Surgical Risk Preoperative Assessment System was developed using multiple logistic regression on a training dataset (2005-2016) and compared to a model using the 26 relevant variables in the American College of Surgeons National Surgical Quality Improvement Program. The Surgical Risk Preoperative Assessment System was validated using a testing dataset (2017-2018). Performance statistics and Hosmer-Lemeshow plots were compared. Two high-risk definitions were compared: (1) the maximum Youden index, and (2) the cohort above the tenth decile of risk on the Hosmer-Lemeshow plot. The sensitivities, specificities, positive predictive values, negative predictive values, and accuracies were compared. RESULTS: In all, 2,822,379 patients were included; 3.6% of patients unexpectedly converted to inpatient. The 6-variable Surgical Risk Preoperative Assessment System model performed comparably to the 26-variable American College of Surgeons National Surgical Quality Improvement Program model (c-indices = 0.818 vs. 0.823; Brier scores = 0.0308 vs 0.0306, respectively). The Surgical Risk Preoperative Assessment System performed well on internal validation (c-index = 0.818, Brier score = 0.0341). The tenth decile of risk definition had higher specificity, positive predictive values, and accuracy than the maximum Youden index definition, while having lower sensitivity. CONCLUSION: The Surgical Risk Preoperative Assessment System accurately predicted a patient's risk of unplanned outpatient-to-inpatient conversion. Patients at higher risk should be considered for inpatient surgery, while lower risk patients could safely undergo operations at ambulatory surgery centers.

Development and Validation of a Multivariable Prediction Model for Postoperative Intensive Care Unit Stay in a Broad Surgical Population.

IMPORTANCE: Despite limited capacity and expensive cost, there are minimal objective data to guide postoperative allocation of intensive care unit (ICU) beds. The Surgical Risk Preoperative Assessment System (SURPAS) uses 8 preoperative variables to predict many common postoperative complications, but it has not yet been evaluated in predicting postoperative ICU admission. OBJECTIVE: To determine if the SURPAS model could accurately predict postoperative ICU admission in a broad surgical population. DESIGN, SETTING, AND PARTICIPANTS: This decision analytical model was a retrospective, observational analysis of prospectively collected patient data from the 2012 to 2018 American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) database, which were merged with individual patients' electronic health record data to capture postoperative ICU use. Multivariable logistic regression modeling was used to determine how the 8 preoperative variables of the SURPAS model predicted ICU use compared with a model inputting all 28 preoperatively available NSQIP variables. Data included in the analysis were collected for the ACS NSQIP at 5 hospitals (1 tertiary academic center, 4 academic affiliated hospitals) within the University of Colorado Health System between January 1, 2012, and December 31, 2018. Included patients were those undergoing surgery in 9 surgical specialties during the 2012 to 2018 period. Data were analyzed from May 29 to July 30, 2021. EXPOSURE: Surgery in 9 surgical specialties, including general, gynecology, orthopedic, otolaryngology, plastic, thoracic, urology, vascular, and neurosurgery. MAIN OUTCOMES AND MEASURES: Use of ICU care up to 30 days after surgery. RESULTS: A total of 34 568 patients were included in the analytical data set: 32 032 (92.7%) in the cohort without postoperative ICU use and 2545 (7.4%) in the cohort with postoperative ICU use (no ICU use: mean [SD] age, 54.9 [16.6] years; 18 188 women [56.8%]; ICU use: mean [SD] age, 60.3 [15.3] years; 1333 men [52.4%]). For the internal chronologic validation of the 7-variable SURPAS model, data from 2012 to 2016 were used as the training data set (n = 24 250, 70.2% of the total sample size of 34 568) and data from 2017 to 2018 were used as the test data set (n = 10 318, 29.8% of the total sample size of 34 568). The C statistic improved in the test data set compared with the training data set (0.933; 95% CI, 0.924-0.941 vs 0.922; 95% CI, 0.917-0.928), whereas the Brier score was slightly worse in the test data set compared with the training data set (0.045; 95% CI, 0.042-0.048 vs 0.045; 95% CI, 0.043-0.047). The SURPAS model compared favorably with the model inputting all 28 NSQIP variables, with both having good calibration between observed and expected outcomes in the Hosmer-Lemeshow graphs and similar Brier scores (model inputting all variables, 0.044; 95% CI, 0.043-0.048; SURPAS model, 0.045; 95% CI, 0.042-0.046) and C statistics (model inputting all variables, 0.929; 95% CI, 0.925-0.934; SURPAS model, 0.925; 95% CI, 0.921-0.930). CONCLUSIONS AND RELEVANCE: Results of this decision analytical model study revealed that the SURPAS prediction model accurately predicted postoperative ICU use across a diverse surgical population. These results suggest that the SURPAS prediction model can be used to help with preoperative planning and resource allocation of limited ICU beds.