ASA Physical Status Classification Improves Predictive Ability of a Validated Trauma Risk Score

Performance of successful ambulatory cervical spine surgery: safety, efficacy, and early experiences of first 100 cases in Poland

BACKGROUND

Ambulatory anterior cervical discectomy and fusion (ACDF) is a promising method, but not common in Poland.

OBJECTIVE

That is why the purpose of this study was to demonstrate the experience of performing ACDF in patients with degenerative spinal diseases.

METHODS

This study at the Spine Centre involved a single-center, multi-surgeon evaluation of 100 patients undergoing ACDF.

RESULTS

Outcomes assessed included pain severity, measured by the visual analogue scale, which improved from 4.28 ± 0.76 preoperatively to 1.11 ± 0.59 one month postoperatively. The Core Outcome Measures Index-neck (COMI-neck) scale also showed significant improvement: before surgery, 30% of patients scored their condition severity between 4-6, and 70% scored 7-10; 6 months postoperatively, the scores were 0-3 for 55% of patients, 4-6 for 45%, and 7-10 for none. Only 2% of patients experienced moderate, temporary complications, with no serious complications or postoperative hematomas observed.

CONCLUSION

The study supports the feasibility, safety, and efficacy of performing ACDF in an ambulatory setting, suggesting that with appropriate patient selection and surgical protocols, ambulatory ACDF can be more broadly implemented.

Under pressure: symptomatic pulmonary hypertension is a predictor of poor outcome following hip fracture

INTRODUCTION

Pulmonary hypertension (PHTN) is associated with increased morbidity and mortality in noncardiac surgery and elective surgery. This population of patients has a low physiological reserve and is prone to cardiac arrest as a result. This study aims to identify the impact that PHTN has on outcomes among geriatric hip fracture patients.

METHODS

A 3:1 propensity-score-matched retrospective case (PHTN)-control (no PHTN [N]) study of hip fracture patients from 2014 to 2022 was performed. Patients were matched utilizing propensity score matching of a validated geriatric trauma risk assessment tool (STTGMA). All patients were reviewed for hospital quality measures and outcomes. Comparative univariable and multivariable analyses were conducted between the two matched cohorts. A sub-analysis compared patients across PHTN severity levels (mild, moderate, severe) based on pulmonary artery systolic pressures (PASP) as measured by transthoracic echocardiogram.

RESULTS

PHTN patients (n = 67) experienced a higher rate of inpatient, 30-day, and 1-year mortality, major complications, and 90-day readmissions as compared to the N cohort (n = 201). PHTN patients with a PASP > 60 experienced a significantly higher rate of major complications, need for ICU, longer admission length, and worse 1-year functional outcomes. Pulmonary hypertension was found to be independently associated with a 3.5 × higher rate of 30-day mortality (p = 0.016), 2.7 × higher rate of 1-year mortality (p = 0.008), 2.5 × higher rate of a major inpatient complication (p = 0.028), and 1.2 × higher rate of 90-day readmission (p = 0.044).

CONCLUSION

Patients who had a prior diagnosis of pulmonary hypertension before sustaining their hip fracture experienced significantly worse inpatient and post-discharge outcomes. Those with a PASP > 60 mmHg had worse outcomes within the PHTN cohort. Providers must recognize these at-risk patients at the time of arrival to adjust care planning accordingly.

LEVEL OF EVIDENCE

III.

A Prospective Multicenter Comparison of Trauma and Injury Severity Score, American Society of Anesthesiologists Physical Status, and National Surgical Quality Improvement Program Calculator's Ability to Predict Operative Trauma Outcomes

BACKGROUND

Trauma outcome prediction models have traditionally relied upon patient injury and physiologic data (eg, Trauma and Injury Severity Score [TRISS]) without accounting for comorbidities. We sought to prospectively evaluate the role of the American Society of Anesthesiologists physical status (ASA-PS) score and the National Surgical Quality Improvement Program Surgical Risk-Calculator (NSQIP-SRC), which are measurements of comorbidities, in the prediction of trauma outcomes, hypothesizing that they will improve the predictive ability for mortality, hospital length of stay (LOS), and complications compared to TRISS alone in trauma patients undergoing surgery within 24 hours.

METHODS

A prospective, observational multicenter study (9/2018-2/2020) of trauma patients ≥18 years undergoing operation within 24 hours of admission was performed. Multiple logistic regression was used to create models predicting mortality utilizing the variables within TRISS, ASA-PS, and NSQIP-SRC, respectively. Linear regression was used to create models predicting LOS and negative binomial regression to create models predicting complications.

RESULTS

From 4 level I trauma centers, 1213 patients were included. The Brier Score for each model predicting mortality was found to improve accuracy in the following order: 0.0370 for ASA-PS, 0.0355 for NSQIP-SRC, 0.0301 for TRISS, 0.0291 for TRISS+ASA-PS, and 0.0234 for TRISS+NSQIP-SRC. However, when comparing TRISS alone to TRISS+ASA-PS ( P = .082) and TRISS+NSQIP-SRC ( P = .394), there was no significant improvement in mortality prediction. NSQIP-SRC more accurately predicted both LOS and complications compared to TRISS and ASA-PS.

CONCLUSIONS

TRISS predicts mortality better than ASA-PS and NSQIP-SRC in trauma patients undergoing surgery within 24 hours. The TRISS mortality predictive ability is not improved when combined with ASA-PS or NSQIP-SRC. However, NSQIP-SRC was the most accurate predictor of LOS and complications.

"Off-Hour" Surgical Start Times Do Not Influence Surgical Precision and Outcomes in Middle-aged Patients and Patients 65 Years and Older With Hip Fractures

BACKGROUND

Previous studies show the "off-hour" effect impacts outcomes after surgery in non-orthopedic settings. This study assessed if the off-hour effect impacts surgical precision and outcomes in middle-aged patients and patients 65 years and older with hip fractures.

MATERIALS AND METHODS

All operative patients in an academic medical center's institutional review board-approved hip fracture registry were reviewed for demographics, hospital quality measures, operative details, radiographic parameters, and outcomes. Patients were grouped into standard (7 am to 4:59 pm) and off-hour (5 pm to 6:59 am) cohorts depending on surgical start time and comparative analyses were conducted. Two subanalyses were conducted: one comparing the quality of reduction for patients with intertrochanteric hip fractures and another comparing the rates of inpatient transfusion and postoperative dislocation for patients treated with arthroplasty.

RESULTS

A total of 2334 patients underwent operative treatment. The off-hour cohort had hospital quality measures and outcomes similar to the standard cohort, including length of stay, rates of inpatient complication, mortality, and readmission. Sub-analysis of 814 intertrochanteric hip fractures demonstrated similar tip-apex distance, residual calcar step-off, and post-fixation neck-shaft angle, while subanalysis of 713 patients undergoing arthroplasty showed similar rates of transfusion and dislocation between cohorts.

CONCLUSION

The time of day patients undergo hip fracture repair does not affect surgical outcomes or hospital quality measures. These results highlight the need for standardized hip protocols and treatment pathways to provide equitable care at all hours of the day. [Orthopedics. 2024;47(3):185-191.].

Can we predict 1-year functional outcomes and mortality following hip fracture in middle-aged and geriatric patients at time of admission?

This study's purpose is to determine if patients treated for hip fracture at highest risk for poor functional outcomes, shorter time to death, and death within 1-year can be predicted at the time of admission. We hypothesized that the Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) tool can be used to predict risk of these variables. Between February 2019-July 2020, 544 patients ≥ 55-years-old were treated for hip fracture [AO/OTA 31A/B, 32A/C]. Each patient's demographics, functional status, and injury details were used to calculate their respective risk (STTGMA) score at time of admission. Patients were divided into risk quartiles by STTGMA score. Patients were contacted by phone to complete EuroQol-5 Dimension (EQ5D-3L) questionnaires on functional status. Comparative analyses were conducted on outcomes and EQ5D-3L questionnaire results. 439 patients (80.7%) had at least 1-year follow-up. 82 patients (18.7%) died within 1-year after hospitalization. Mean STTGMA score was 1.67% ± 4.49%. The highest-risk cohort experienced a 42x (p < 0.01) and 2.5x (p = 0.01) increased rate of 1-year mortality compared to the minimal- and low-risk groups respectively. The highest-risk cohort had the shortest time to death (p = 0.015). The highest-risk cohort had the lowest EQ5D index (p < 0.01) and VAS scores (p < 0.01) along with the highest rate of 30 day readmission (p < 0.01) and the longest length of stay (p < 0.01). The STTGMA tool provides important prognostic information for middle-aged and geriatric hip fracture patients that can help modulate care levels. This information is useful when counseling patients, their families, and caregivers on expected outcomes.

The Impact of Screening for Perioperative ICU Admission in Geriatric Hip Fracture Patients: A Retrospective Analysis

BACKGROUND

Hip fracture patients are a subset of trauma patients with high peri-operative mortality. To mitigate the mortality risk, the use of predictive scoring systems (e.g., RSI or Nomograms) for risk stratification and monitoring of high-risk patients in the intensive care unit (ICU) has been proposed. Screening patients for ICU admission with relatively low-cost tools may achieve high-quality, low-cost care. The aim of this study was to assess the effectiveness and feasibility of screening postoperative hip fracture patients for ICU admission.

METHODS

This is a retrospective single-site study comparing two groups of patients, before and after implementation of a hip fracture postoperative screening intervention in a level 1 trauma center in the United States. All hip fracture patients > 55 years of age admitted to the hospital between January 2021 and May 2023 were included. Trauma team members assessed and screened patients postoperatively in the post-anesthesia care unit (PACU), ordering standardized tests, including laboratory tests, a chest x-ray, and electrocardiogram (EKG). Assessment of the effect of the intervention included a comparison of a number of major adverse events (MAEs), mortality, planned and unplanned ICU admissions, ICU length of stay (LOS), and hospital LOS between pre- and post-intervention groups. Propensity score (PS) estimates were used to compare outcomes between the matched participants in the sample. A predictive model for ICU admission for the overall sample was estimated, and discriminative ability was assessed with an area under the curve (AUC) receiver operator characteristics (ROC) analysis. Lastly, feasibility was assessed by compliance with screening intervention and charges per patient related to the intervention.

RESULTS

The sample consisted of 290 patients in the pre-intervention and 180 patients in the post-intervention groups, respectively, with a mean age of 81.4 ± (9.9) years. There was a significant increase (p<0.01) in planned ICU admissions (OR=2.387, 95% CI (1.430, 3.983)) after screening protocol implementation. There was no significant difference between the pre-intervention group and post-intervention group in the number of MAEs (p=0.392), mortality (p=0.591), ICU LOS (p=0.617), and hospital LOS (p=0.151). When the PS-matched sample (n=424) was analyzed, there was a significant decrease (p=0.45) in unplanned ICU admissions (OR=6.40, 95% CI (0.81, 50.95)) after protocol implementation. Anticoagulants, emergency department (ED) respiratory rate (RR), injury severity score (ISS), number of comorbidities, substance use disorder (SAD), peripheral artery disease (PAD), and chronic obstructive pulmonary disease (COPD) were significant predictors of ICU admission (p=0.002, 0.022, 0.030, 0.034, 0.039, 0.039, and 0.042), respectively, and, demonstrated the discriminative ability between high and low risk for ICU admission (AUC=0.597, 0.587, 0.581, 0.578, 0.513, and 0.587, respectively). The screening intervention was achievable with 99% compliance (Kappa estimate 0.94) among trauma team members with an average charge of $282 per patient.

CONCLUSION

The addition of a postoperative screening intervention for hip fracture patients > 55 years of age is achievable and decreases unplanned ICU admissions in matched samples. Presenting clinical indicators and comorbidities are associated with ICU admission and provide sufficient discriminatory ability as criteria for ICU admission.

Diagnostic Accuracy of a Trauma Risk Assessment Tool Among Geriatric Patients With Crash Injuries

ABSTRACT

The Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) is a risk stratification tool. We evaluated the STTGMA's accuracy in predicting 30-day mortality and the odds of unfavorable clinical trajectories among crash-related trauma patients. This retrospective cohort study (n = 912) pooled adults aged 55 years and older from a single institutional trauma database. The data were split into training and test data sets (70:30 ratio) for the receiver operating curve analysis and internal validation, respectively. The outcome variables were 30-day mortality and measures of clinical trajectory. The predictor variable was the high-energy STTGMA score (STTGMAHE). We adjusted for the American Society of Anesthesiologists Physical Status. Using the training and test data sets, STTGMAHE exhibited 82% (95% CI: 65.5-98.3) and 96% (90.7-100.0) accuracies in predicting 30-day mortality, respectively. The STTGMA risk categories significantly stratified the proportions of orthopedic trauma patients who required intensive care unit (ICU) admissions, major and minor complications, and the length of stay (LOS). The odds of ICU admissions, major and minor complications, and the median difference in the LOS increased across the risk categories in a dose-response pattern. STTGMAHE exhibited an excellent level of accuracy in identifying middle-aged and geriatric trauma patients at risk of 30-day mortality and unfavorable clinical trajectories.

The Cost We Bear: Financial Implications for Hip Fracture Care Amidst the COVID-19 Pandemic

INTRODUCTION

The purpose of this study was to assess the impact of COVID-19 on the cost of hip fracture care in the geriatric/middle-aged cohort, hypothesizing the cost of care increased during the pandemic, especially in COVID+ patients.

METHODS

Between October 2014 and January 2022, 2,526 hip fracture patients older than 55 years were analyzed for demographics, injury details, COVID status on admission, hospital quality measures, and inpatient healthcare costs from the inpatient admission. Comparative analyses were conducted between: (1) All comers and high-risk patients in the prepandemic (October 2014 to January 2020) and pandemic (February 2020 to January 2022) cohorts and (2) COVID+ and COVID- patients during the pandemic. Subanalysis assessed the difference in cost breakdown for patients in the overall cohorts, the high-risk quartiles, and between the prevaccine and postvaccine pandemic cohorts.

RESULTS

Although the total costs of admission for all patients, and specifically high-risk patients, were not notably higher during the pandemic, further breakdown showed higher costs for the emergency department, laboratory/pathology, radiology, and allied health services during the pandemic, which was offset by lower procedural costs. High-risk COVID+ patients had higher total costs than high-risk COVID- patients ( P < 0.001), most notably in room-and-board ( P = 0.032) and allied health ( P = 0.023) costs. Once the pandemic started, subgroup analysis demonstrated no change in the total cost in the prevaccine and postvaccine cohort.

CONCLUSION

The overall inpatient cost of hip fracture care did not increase during the pandemic. Although individual subdivisions of cost signified increased resource utilization during the pandemic, this was offset by lower procedural costs. COVID+ patients, however, had notably higher total costs compared with COVID- patients driven primarily by increased room-and-board costs. The overall cost of care for high-risk patients did not decrease after the widespread administration of the COVID-19 vaccine.

LEVEL OF EVIDENCE

III.

Cut-Through versus Cut-Out: No Easy Way to Predict How Single Lag Screw Design Cephalomedullary Nails Used for Intertrochanteric Hip Fractures Will Fail?

Purpose

This study aims to compare patients in whom fixation failure occurred via cut-out (CO) or cut-through (CT) in order to determine patient factors and radiographic parameters that may be predictive of each mechanism.

Materials and Methods

This retrospective cohort study includes 18 patients with intertrochanteric (IT) hip fractures (AO/OTA classification 31A1.3) who underwent treatment using a single lag screw design intramedullary nail in whom fixation failure occurred within one year. All patients were reviewed for demographics and radiographic parameters including tip-to-apex distance (TAD), posteromedial calcar continuity, neck-shaft angle, lateral wall thickness, and others. Patients were grouped into cohorts based on the mechanism of failure, either lag screw CO or CT, and a comparison was performed.

Results

No differences in demographics, injury details, fracture classifications, or radiographic parameters were observed between CO/CT cohorts. Of note, a similar rate of post-reduction TAD>25 mm (P=0.936) was observed between groups. A higher rate of DEXA (dual energy X-ray absorptiometry) confirmed osteoporosis (25.0% vs. 60.0%) was observed in the CT group, but without significance.

Conclusion

The mechanism of CT failure during intramedullary nail fixation of an IT fracture did not show an association with clinical data including patient demographics, reduction accuracy, or radiographic parameters. As reported in previous biomechanical studies, the main predictive factor for patients in whom early failure might occur via the CT effect mechanism may be related to bone quality; however, conduct of larger studies will be required in order to determine whether there is a difference in bone quality.

Poorly controlled diabetes: Glycosylated hemoglobin (HA1c) levels >8% are the tipping point for significantly worse outcomes following hip fracture in the geriatric population

INTRODUCTION

The presence of diabetes has been associated with increased mortality risk after hip fracture, however, little has been published about the lab values of these diabetic patients and the role high labs play in morbidity and mortality. The purpose of this study is to quantify the severity of diabetes that is associated with worse outcomes in hip fracture patients.

METHODS

A consecutive series of 2430 patients >55 years old who sustained a hip fracture between October 2014-November 2021 were reviewed for demographics, hospital quality measures, and outcomes. Each patient with a diagnosis of diabetes mellitus (DM) was reviewed for hemoglobin-A1c (HA1c) and glucose values at admission. Univariable comparisons and multivariable regression analyses were conducted to assess the impact of diabetes and elevated lab values (HA1c) on outcomes such as hospital quality measures, inpatient complications, readmission rates, and mortality rates.

RESULTS

565 patients (23%) carried a diagnosis of diabetes mellitus at the time of their injury. Considerable demographic and comorbidity differences between diabetic and non-diabetic cohorts indicated that the diabetic cohort was less healthy. The diabetic cohort had longer hospitalizations, higher rates of minor complications, readmissions within 90-days, and mortality within 30-days/1-year. Stratification by HA1c levels found patients with a HA1c>8% had a significantly higher rate of major complications, and mortality at all time points (inpatient/30-day/1-year). Multivariable regression found HA1c>8% to be independently associated with a higher rate of inpatient/30-day/1-year mortality in comparison to a diagnosis of diabetes alone which was not independently significant.

CONCLUSION

While all patients with DM experienced worse outcomes than those without, those with poorly controlled diabetes (HA1c>8%) at the time of hip fracture injury experienced poorer outcomes compared to those with well-controlled diabetes. Treating physicians must recognize these patients with poorly controlled DM at the time of arrival to adjust care planning and patient expectations accordingly.

Crosswalk between Charlson Comorbidity Index and the American Society of Anesthesiologists Physical Status Score for Geriatric Trauma Assessment

The American Society of Anesthesiologists Physical Status (ASA-PS) grade better risk stratifies geriatric trauma patients, but it is only reported in patients scheduled for surgery. The Charlson Comorbidity Index (CCI), however, is available for all patients. This study aims to create a crosswalk from the CCI to ASA-PS. Geriatric trauma cases, aged 55 years and older with both ASA-PS and CCI values (N = 4223), were used for the analysis. We assessed the relationship between CCI and ASA-PS, adjusting for age, sex, marital status, and body mass index. We reported the predicted probabilities and the receiver operating characteristics. A CCI of zero was highly predictive of ASA-PS grade 1 or 2, and a CCI of 1 or higher was highly predictive of ASA-PS grade 3 or 4. Additionally, while a CCI of 3 predicted ASA-PS grade 4, a CCI of 4 and higher exhibited greater accuracy in predicting ASA-PS grade 4. We created a formula that may accurately situate a geriatric trauma patient in the appropriate ASA-PS grade after adjusting for age, sex, marital status, and body mass index. In conclusion, ASA-PS grades can be predicted from CCI, and this may aid in generating more predictive trauma models.

Transfusion Thresholds Can Be Safely Lowered in the Hip Fracture Patient: A Consecutive Series of 1,496 Patients

INTRODUCTION

The purpose of this study is to identify optimal threshold hemoglobin (Hgb) and hematocrit (Hct) laboratory values to transfuse hip fracture patients.

METHODS

A consecutive series of hip fracture patients were reviewed for demographic, clinical, and cost data. Patients receiving an allogeneic transfusion of packed red blood cells (pRBCs) were grouped based on last Hct or Hgb (H&H) value before first transfusion. Multivariate logistic regressions of H&H quantile were performed to predict "good outcomes," a composite binary variable defined as admissions satisfying (1) no major complications, (2) length of stay below top tertile, (3) cost below median, (4) no mortality within 30 days, and (5) no readmission within 30 days. Odds ratios (OR) for "good outcomes" were calculated for each H&H quantile.

RESULTS

One thousand four hundred ninety-six hip fracture patients were identified, of which 598 (40.0%) were transfused with pRBCs. Patients first transfused at Hgb values from 7.55 to 7.85 g/dL ( P = 0.043, OR = 2.70) or Hct values from 22.7 to 23.8% ( P = 0.048, OR = 2.63) were most likely to achieve "good outcomes."

DISCUSSION

The decision to transfuse patients should be motivated by Hgb and Hct laboratory test results, given that transfusion timing relative to surgery has been shown to not affect outcomes among patients matched by trauma risk score. Surgeons should aim to transfuse hip fracture patients at Hgb levels between 7.55 g/dL and 7.85 g/dL or Hct levels between 22.7% and 23.8%. These transfusion thresholds have the potential to lower healthcare costs without compromising quality, ultimately resulting in less costly, efficacious care for the patient.

LEVEL OF EVIDENCE

Level III.

Impact of Poorly Controlled Diabetes and Glycosylated Hemoglobin Values in Geriatric Hip Fracture Mortality Risk Assessment

Introduction The presence of poorly-controlled diabetes in the setting of geriatric hip fractures has been shown to increase all-cause mortality and worsen outcomes. This study aimed to assess whether the addition of a patient's glycated hemoglobin (A1c) value to a validated geriatric inpatient risk tool improves the predictive capacity of the risk tool. Methods A cohort of 2430 patients >55 years old treated for low-energy mechanism hip fractures between October 2014 to November 2021 were reviewed for demographics (including diabetes diagnoses and their respective hemoglobin A1c values at the time of admission), injury details, hospital quality measures, and mortality. As past work demonstrated a hemoglobin A1c value above 8% to be the tipping point for worse outcomes, the baseline Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) tool for inpatient mortality in hip fractures (STTGMAHIP_FX_SCORE - Score for Trauma Triage in the Geriatric and Middle-Aged Hip Fracture Score) was modified to include a patient's hemoglobin A1c using an 8% cutoff (STTGMAHIP_8%A1c - Score for Trauma Triage in the Geriatric and Middle-Aged Hip 8% Hemoglobin A1c Cutoff Score). The new model's predictive ability (as measured by the area under the receiver operating curves (AUROCs)) for inpatient mortality was compared to the baseline tool using DeLong's test. Risk quartiles were generated for the new tool, and comparative analyses were conducted on hospital quality measures and outcomes.  Results Five hundred and sixty-five patients (23%) were noted to have diabetes mellitus, and 76 patients had an A1c above 8%. Patients with a hemoglobin A1c above 8% had a higher rate of inpatient complications and mortality through one year. The STTGMAHIP_8%A1c score significantly improved the predictive capacity for inpatient mortality compared to STTGMAHIP_FX_SCORE (0.786 vs. 0.672, p=0.0456). Upon analysis of the risk quartiles, the highest risk cohort was found to have a longer length of stay (p<0.001), with higher rates of inpatient (p<0.001) and 30-day mortality (p<0.001) and need for admission to the intensive care unit (p<0.001) as compared to the minimal risk cohort. Patients in the lowest risk quartile were most likely to be discharged home (p<0.001). Conclusion Patients who present with a hemoglobin A1c above 8% experienced significantly worse outcomes than those below 8%. The inclusion of a patient's hemoglobin A1c as a cutoff score improves the STTGMAHIP_FX_SCORE tool to predict mortality and risk stratify patient outcomes. While diabetes presents another medical challenge to manage, providers may utilize this new variable to better highlight at-risk diabetic patients.

Adaptive Risk Modeling: Improving Risk Assessment of Geriatric Hip Fracture Patients Throughout their Hospitalization

INTRODUCTION

The purpose of this study was twofold: 1. To assess how adaptive modeling, accounting for development of inpatient complications, affects the predictive capacity of the risk tool to predict inpatient mortality for a cohort of geriatric hip fracture patients. 2. To compare how risk triaging of secondary outcomes is affected by adaptive modeling. We hypothesize that adaptive modeling will improve the predictive capacity of the model and improve the ability to risk triage secondary outcomes.

METHODS

Between October 2014-August 2021, 2421 patients >55 years old treated for hip fracture obtained through low-energy mechanisms were analyzed for demographics, injury details and hospital quality measures. The baseline Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) tool for hip fractures (STTGMA_HIP) was calculated in the emergency department setting. A new mortality risk score (STTGMA_{HIP_ADPTV}) was created including inpatient complications. Each models' predictive ability was compared using DeLong's test. Patients were grouped into quartiles based on their respective STTGMA_{HIP_ADPTV} and comparative analyses were conducted.

RESULTS

AUROC comparison demonstrated STTGMA_{HIP_ADPTV} significantly improved the predictive capacity for inpatient mortality compared to STTGMA_HIP (p < 0.01). STTGMA_{HIP_ADPTV} correctly triaged 80% and 64% of high-risk patients with inpatient and 30-day mortality compared to 64% and 57% for STTGMA_HIP. STTGMA_{HIP_ADPTV} quartile stratification demonstrated that the highest risk cohort had the worst mortality outcomes and hospital quality measures. Patients whose risk classification changed from minimal risk using STTGMA_HIP to high risk using STTGMA_{HIP_ADPTV} experienced the highest rate of mortality, readmission, ICU admission, with longer lengths of stay and higher hospital costs.

DISCUSSION

Adaptive modeling accounting for inpatient complications improves the predictive capacity and risk triaging of the STTGMA_HIP tool. Real-time modulation of a patient's mortality risk profile can inform their requisite level of medical management to improve the quality and value of care as patients progress through their index hospitalization. STTGMA_{HIP_ADPTV} can better identify patients at risk for developing complications whose mortality and readmission risk profile increase significantly, allowing their new risk classification to inform higher levels of care. While this may increase length of stay and total costs, it may improve outcomes in both the short and long-term.

LEVEL OF EVIDENCE

III.

No Differences Between White and Non-White Patients in Terms of Care Quality Metrics, Complications, and Death After Hip Fracture Surgery When Standardized Care Pathways Are Used

BACKGROUND

Many initiatives by medical and public health communities at the national, state, and institutional level have been centered around understanding and analyzing critical determinants of population health with the goal of equitable and nondisparate care. In orthopaedic traumatology, several studies have demonstrated that race and socioeconomic status are associated with differences in care delivery and outcomes of patients with hip fractures. However, studies assessing the effectiveness of methods to address disparities in care delivery, quality metrics, and complications after hip fracture surgery are lacking.

QUESTIONS/PURPOSES

(1) Are hospital quality measures (such as delay to surgery, major inpatient complications, intensive care unit admission, and discharge disposition) and outcomes (such as mortality during inpatient stay, within 30 days or within 1 year) similar between White and non-White patients at a single institution in the setting of a standardized hip fracture pathway? (2) What factors correlate with aforementioned hospital quality measures and outcomes under the standardized care pathway?

METHODS

In this retrospective, comparative study, we evaluated the records of 1824 patients 55 years of age or older with hip fractures from a low-energy mechanism who were treated at one of four hospitals in our urban academic healthcare system, which includes an orthopaedic tertiary care hospital, from the initiation of a standardized care pathway in October 2014 to March 2020. The standardized 4-day hip fracture pathway is comprised of medicine comanagement of all patients and delineated tasks for doctors, nursing, social work, care managers, and physical and occupational therapy from admission to expected discharge on postoperative day 4. Of the 1824 patients, 98% (1787 of 1824) of patients who had their race recorded in the electronic medical record chart (either by communicating it to a medical provider or by selecting their race from options including White, Black, Hispanic, and Asian in a patient portal of the electronic medical record) were potentially eligible. A total of 14% (249 of 1787) of patients were excluded because they did not have an in-state address. Of the included patients, 5% (70 of 1538) were lost to follow-up at 30 days and 22% (336 of 1538) were lost to follow-up at 1 year. Two groups were established by including all patients selecting White as primary race into the White cohort and all other patients in the non-White cohort. There were 1111 White patients who were 72% (801) female with mean age 82 ± 10 years and 427 non-White patients who were 64% (271) female with mean age 80 ± 11 years. Univariate chi-square and Mann-Whitney U tests of demographics were used to compare White and non-White patients and find factors to control for potentially relevant confounding variables. Multivariable regression analyses were used to control for important baseline between-group differences to (1) determine the correlation of White and non-White race on mortality, inpatient complications, intensive care unit (ICU) admissions, and discharge disposition and (2) assess the correlation of gender, socioeconomic status, insurance payor, and the Score for Trauma Triage in the Geriatric and Middle Aged (STTGMA) trauma risk score with these quality measures and outcomes.

RESULTS

After controlling for gender, insurer, socioeconomic status and STTGMA trauma risk score, we found that non-White patients had similar or improved care in terms of mortality and rates of delayed surgery, ICU admission, major complications, and discharge location in the setting of the standardized care pathway. Non-White race was not associated with inpatient (odds ratio 1.1 [95% CI 0.40 to 2.73]; p > 0.99), 30-day (OR 1.0 [95% CI 0.48 to 1.83]; p > 0.99) or 1-year mortality (OR 0.9 [95% CI 0.57 to 1.33]; p > 0.99). Non-White race was not associated with delay to surgery beyond 2 days (OR = 1.1 [95% CI 0.79 to 1.38]; p > 0.99). Non-White race was associated with less frequent ICU admissions (OR 0.6 [95% CI 0.42 to 0.85]; p = 0.03) and fewer major complications (OR 0.5 [95% CI 0.35 to 0.83]; p = 0.047). Non-White race was not associated with discharge to skilled nursing facility (OR 1.0 [95% CI 0.78 to 1.30]; p > 0.99), acute rehabilitation facility (OR 1.0 [95% CI 0.66 to 1.41]; p > 0.99), or home (OR 0.9 [95% CI 0.68 to 1.29]; p > 0.99). Controlled factors other than White versus non-White race were associated with mortality, discharge location, ICU admission, and major complication rate. Notably, the STTGMA trauma risk score was correlated with all endpoints.

CONCLUSION

In the context of a hip fracture care pathway that reduces variability from time of presentation through discharge, no differences in mortality, time to surgery, complications, and discharge disposition rates were observed beween White and non-White patients after controlling for baseline differences including trauma risk score. The pathway detailed in this study is one iteration that the authors encourage surgeons to customize and trial at their institutions, with the goal of providing equitable care to patients with hip fractures and reducing healthcare disparities. Future investigations should aim to elucidate the impact of standardized trauma care pathways through the use of the STTGMA trauma risk score as a controlled confounder or randomized trials in comparing standardized to individualized, surgeon-specific care.

LEVEL OF EVIDENCE

Level III, therapeutic study.

The Role of Smoking and Body Mass Index in Mortality Risk Assessment for Geriatric Hip Fracture Patients

Background

Smoking, obesity, and being below a healthy body weight are known to increase all-cause mortality rates and are considered modifiable risk factors. The purpose of this study is to assess whether adding these risk factors to a validated geriatric inpatient mortality risk tool will improve the predictive capacity for hip fracture patients. We hypothesize that the predictive capacity of the Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) tool will improve.

Methodology

Between October 2014 and August 2021, 2,421 patients >55-years-old treated for hip fractures caused by low-energy mechanisms were analyzed for demographics, injury details, hospital quality measures, and mortality. Smoking status was recorded as a current every-day smoker, former smoker, or never smoker. Smokers (current and former) were compared to non-smokers (never smokers). Body mass index (BMI) was defined as underweight (<18.5 kg/m²), healthy weight (18.5-24.9 kg/m²), overweight (25.0-24.9 kg/m²), or obese (>30 kg/m²). The baseline STTGMA tool for hip fractures (STTGMAHIP_FX_SCORE) was modified to include patients’ BMI and smoking status (STTGMA_MODIFIABLE), and new mortality risk scores were calculated. Each model’s predictive ability was compared using DeLong’s test by analyzing the area under the receiver operating curves (AUROCs). Comparative analyses were conducted on each risk quartile.

Results

A comparison of smokers versus non-smokers demonstrated that smokers experienced higher rates of inpatient (p = 0.025) and 30-day (p = 0.048) mortality, myocardial infarction (p < 0.01), acute respiratory failure (p < 0.01), and a longer length of stay (p = 0.014). Comparison among BMI cohorts demonstrated that underweight patients experienced higher rates of pneumonia (p = 0.033), decubitus ulcers (p = 0.046), and the need for an intensive care unit (ICU) (p < 0.01). AUROC comparison demonstrated that STTGMA_MODIFIABLE significantly improved the predictive capacity for inpatient mortality compared to STTGMAHIP_FX_SCORE (0.792 vs. 0.672, p = 0.0445). Quartile stratification demonstrated the highest risk cohort had a longer length of stay (p < 0.01), higher rates of inpatient (p < 0.01) and 30-day mortality (p < 0.01), and need for an ICU (p < 0.01) compared to the minimal risk cohort. Patients in the lowest risk quartile were most likely to be discharged home (p < 0.01).

Conclusions

Smoking, obesity, and being below a healthy body weight increase the risk of perioperative complications and poor outcomes. Including smoking and BMI improves the STTGMAHIP_FX_SCORE tool to predict mortality and risk stratify patient outcomes. Because smoking, obesity, and being below a healthy body weight are modifiable patient factors, providers can counsel patients and implement lifestyle changes to potentially decrease their risk of longer-term poor outcomes, especially in the setting of another fracture. For patients who are former smokers, providers can use this information to encourage continued restraint and healthy choices.

Seasonality Affects Elderly Hip Fracture Mortality Risk During the COVID-19 Pandemic

Background

The incidence of geriatric hip fractures, respiratory infections (e.g., coronavirus disease 2019 (COVID-19), influenza), and mortality is higher during the fall and winter. The purpose of this study is to assess whether the addition of seasonality to a validated geriatric inpatient mortality risk tool will improve the predictive capacity and risk stratification for geriatric hip fracture patients. We hypothesize that seasonality will improve the predictive capacity.

Methodology

Between October 2014 and August 2021, 2,421 patients >55-year-old treated for hip fracture were analyzed for demographics, date of presentation, COVID-19 status (for patients after February 2020), and mortality. Patients were grouped by season based on their admission dates into the following four cohorts: fall (September-November), winter (December-February), spring (March-May), and summer (June-August). Patients presenting during the fall/winter and spring/summer were compared. The baseline Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) tool for hip fractures (STTGMAHIP_FX_SCORE) and the seasonality iteration (STTGMA_SEASON) were also compared. Sub-analysis was conducted on 687 patients between February 2020 and August 2021 amid the COVID-19 pandemic. The baseline score (STTGMAHIP_FX_SCORE) and the COVID-19 iteration (STTGMACOVID_ORIGINAL_2020) were modified to include seasonality (STTGMA_COVID/SEASON). Patients were stratified by risk score and compared. The predictive ability of the models was compared using DeLong’s test.

Results

For the overall cohort, patients who presented during the fall/winter had a higher rate of inpatient mortality (2.87% vs. 1.25%, p < 0.01). STTGMA_SEASON improved the predictive capacity for inpatient mortality compared to STTGMAHIP_FX_SCORE but not significantly (0.773 vs. 0.672, p = 0.105) On sub-analysis, regression weighting showed a coefficient of 0.643, with fall and winter having a greater absolute effect size (fall = 2.572, winter = 1.929, spring = 1.286, summer = 0.643). STTGMA_COVID/SEASON improved the predictive capacity for inpatient mortality compared to STTGMAHIP_FX_SCORE (0.882 vs. 0.581, p < 0.01) and STTGMACOVID_ORIGINAL_2020 (0.882 vs. 0.805, p = 0.04). The highest risk quartile contained 89.5% of patients who expired during their index inpatient hospitalization (p < 0.01) and 68.2% of patients who died within 30 days of discharge (p < 0.01).

Conclusions

Seasonality may play a role in both the incidence and impact of COVID-19 and additional respiratory infections. Including seasonality improves the predictive capacity and risk stratification of the STTGMA tool during the COVID-19 pandemic. This allows for effective triage and closer surveillance of high-risk geriatric hip fracture patients by better accounting for the increased respiratory infection incidence and the associated mortality risk seen during fall and winter.

Predicting mortality in elderly trauma patients: a review of the current literature

PURPOSE OF REVIEW

Advances in medical care allow patients to live longer, translating into a larger geriatric patient population. Adverse outcomes increase with older age, regardless of injury severity. Age, comorbidities, and physiologic deterioration have been associated with the increased mortality seen in geriatric trauma patients. As such, outcome prediction models are critical to guide clinical decision making and goals of care discussions for this population. The purpose of this review was to evaluate the various outcome prediction models for geriatric trauma patients.

RECENT FINDINGS

There are several prediction models used for predicting mortality in elderly trauma patients. The Geriatric Trauma Outcome Score (GTOS) is a validated and accurate predictor of mortality in geriatric trauma patients and performs equally if not better to traditional scores such as the Trauma and Injury Severity Score. However, studies recommend medical comorbidities be included in outcome prediction models for geriatric patients to further improve performance.

SUMMARY

The ideal outcome prediction model for geriatric trauma patients has not been identified. The GTOS demonstrates accurate predictive ability in elderly trauma patients. The addition of medical comorbidities as a variable in outcome prediction tools may result in superior performance; however, additional research is warranted.

Racial Differences in Orthopedic Trauma Surgery

Racial discrepancies among patients in the United States undergoing orthopedic trauma surgery have not been investigated. Issues relating to socioeconomic status and access to care have played a role in the health outcomes of racial groups. In orthopedic surgery, recent joint arthroplasty literature has shown significant racial differences in the use of elective joint arthroplasty. Furthermore, studies also suggest increased rates of early complication in racial minority groups. In general, little information exists on the postoperative outcomes of racial minority groups in orthopedic surgery. We retrospectively queried the National Surgical Quality Improvement Program database to identify patients undergoing orthopedic trauma surgery between 2008 and 2016. Patients of all ages who underwent orthopedic trauma surgery were identified using Current Procedural Terminology codes. Patients classified as either Black or White were included in the study. Demographic data, comorbidities, and basic surgical data were compared between the groups. Adverse outcomes in the initial 30 days postoperative were also examined. Higher frequencies of deep wound infection (0.5% vs 0.3%, P=.002) were noted among Black patients, with decreased mortality (0.3% vs 0.6%, P=.004) and postoperative transfusion (2.7% vs 3.8%, P<.001) rates, compared with White patients. Clear differences exist in the demographic, surgical, and outcome data between Black and White patients undergoing orthopedic trauma surgery. More epidemiological studies are required to further investigate racial differences in orthopedic trauma surgery. [Orthopedics. 2022;45(2):71-76.].

Trauma Risk Score Matching for Observational Studies in Orthopedic Trauma

OBJECTIVES

To determine if matching by trauma risk score is non-inferior to matching by chronic comorbidities and/or a combination of demographic and patient characteristics in observational studies of acute trauma in a hip fracture model.

DESIGN

Retrospective cohort study SETTING: Level-1 Trauma Center PATIENTS: 1,590 hip fracture [AO/OTA 31A and 31B] patients age 55 and over treated between October 2014 and February 2020 at 4 hospitals within a single academic medical center.

INTERVENTION

Repeatedly matching randomized subsets of patients by (1) Score for Trauma Triage in Geriatric and Middle-Aged (STTGMA), (2) Charlson Comorbidity Index (CCI), or (3) a combination of sex, age, CCI and body mass index (BMI).

MAIN OUTCOME MEASUREMENTS

"Matching failures" where rate of significant differences in variables of matched cohorts exceeds the 5% expected by chance.

RESULTS

STTGMA and combination matching resulted in no "matching failures". Matching by CCI alone resulted in "matching failures" of BMI, ASA class, STTGMA, major complications, sepsis, pneumonia, acute respiratory failure, and 90-day readmission.

CONCLUSIONS

STTGMA matching in observational cohort studies is less likely to yield significant differences of demographics and outcomes than CCI matching. STTGMA matching is noninferior to matching a combination of demographic variables optimized for each treatment cohort. STTGMA matching is apt to reflect equipoise of health at admission and outcome likelihood in observational cohort studies of orthopedic trauma, while maintaining consistent weighting of demographic and injury characteristic variables that may expand the generalizability of these studies.

LEVEL OF EVIDENCE

Level III.

Trauma risk score matching for observational studies in orthopedic trauma dataset and code

The dataset presented was collected via retrospective review from an orthopedic trauma database approved by the institutional review board at the author's institution from patients treated at any of the four hospitals serviced by the academic orthopedic surgery department. Femoral neck and intertrochanteric hip fracture patients from low energy mechanisms admitted between October 2014 and February 2020, were selected if they were age 55 or older and had recorded sex, body mass index (BMI), Charlson Comorbidity Index (CCI), American Society of Anaesthesiologists (ASA) physical status classification, Glasgow Coma Score, Abbreviated Injury Severity score for the chest, head and neck, and extremities, and ambulation status prior to injury.

The resultant 1,590 subject dataset may be analysed via the supplied R statistical code to determine the frequency of equipoise in baseline and outcome variables from propensity matching via three matching schemes. The code implements three matching schemes including matching by (1) The Score for Trauma Triage in Geriatric and Middle-Aged (STTGMA) (2) CCI alone, or (3) a combination of sex, age, CCI and BMI. The code selects a subset of ten percent of hip fracture patients by a pseudorandom number generator (PRNG). The code matches the remaining patients 1:1 to the selected patients by propensity score generated by logistic regression of STTGMA, CCI, or a combination of sex, age, CCI and BMI using greedy nearest neighbor matching without replacement by the MatchIt package for R software. The code then compares matched cohorts by Chi-square, Fisher, or Mann-Whitney U test with significance level of 0.05 representing a 5% chance of significant differences due to random sampling of subjects.

The supplied code repeats the random selection, matching and testing process 100,000 times for each matching method. The resultant code output is the frequency of significantly different demographic or outcome parameters among matched cohorts by matching method.

This data and statistical code have reuse potential to explore alternative matching schemes. The supplied baseline variables should be robust enough to derive alternative risk scores for each patient which may be included as a matching variable for comparison. The authors also look forward to unexpected ways that this data may be used by readers.

Trauma Risk Score Also Predicts Blood Transfusion Requirements in Hip Fracture Patients

Introduction

The purpose of this study is to determine if the risk of receiving a blood transfusion during hip fracture hospitalization can be predicted by a validated risk profiling score (Score for Trauma Triage in Geriatric and Middle Aged (STTGMA)).

Materials and Methods

A consecutive series of 1449 patients 55 years and older admitted for a hip fracture at one academic medical center were identified from a trauma database. The STTGMA risk score was calculated for each patient. Patients were stratified into risk groups based on their STTGMA score quantile: minimal risk (0–50%), low risk (50–80%), moderate risk (80–95%), and high risk (95–100%). Incidence and volume of blood transfusions were compared between risk groups.

Results

There were 562 (38.8%) patients who received a transfusion during their admission. 58.3% of patients in the high risk group received a transfusion during admission compared to 31.2% of minimal risk group patients, 42.6% of low risk group patients, and 50.0% of moderate risk group patients (p < 0.001). STTGMA was predictive of first transfusion incidence in both the preoperative and postoperative periods. There was no difference in mean total transfusion volume between the four risk groups.

Conclusion

The STTGMA model is capable of risk stratifying hip fracture patients more likely to receive blood transfusions during hospitalization. Surgeons can use this tool to anticipate transfusion requirements.

Transfusion timing relative to surgery does not impact outcomes in hip fracture patients

PURPOSE

The purpose of this study is to determine the effects of blood transfusion timing in hip fracture patients.

METHODS

A consecutive series of hip fracture patients 55 years and older who required a blood transfusion during hospitalization were reviewed for demographic, injury, clinical outcome, and cost information. A validated risk predictive score (STTGMA) was calculated for each patient. Patients were stratified to preoperative, intraoperative, or postoperative first transfusion cohorts. The intraoperative and postoperative cohorts were matched by STTGMA, sex, and procedure to the preoperative cohort. Baseline patient characteristics and outcomes were compared before and after matching.

RESULTS

Prior to matching, the preoperative cohort was more often male (p < 0.001) with increased Charlson comorbidity index (p = 0.012), ASA class (p < 0.002), STTGMA (p < 0.001), total transfused volume (p = 0.002), incidence of inpatient mortality (p = 0.045), myocardial infarction (p = 0.005) and cardiac arrest (p = 0.014). After matching, the preoperative cohort had increased total transfused volume (p = 0.015) and decreased pneumonia incidence (p = 0.040).

CONCLUSION

Matching STTGMA score, sex, and procedure results in non-inferior outcomes among hip fracture patients receiving preoperative first blood transfusions compared to intraoperative and postoperative transfusions.