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Hip Trauma

Time-to-Surgery for Definitive Fixation of Hip Fractures: A Look at Outcomes Based Upon Delay

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Author Affiliation | Disclosures

Authors’ Disclosure Statement: The authors report no actual or potential conflict of interest in relation to this article.

Dr. Alvi is an Adult Joint Reconstruction Orthopedic Surgeon, Barrington Orthopedic Specialists, Schaumburg, Illinois. Dr. Thompson is Assistant Professor, Department of Orthopaedic Surgery, and Associate Director, Center for Cerebral Palsy, David Geffen School of Medicine, The University of California, Los Angeles, Los Angeles, California. Dr. Krishnan is a General Surgery Resident, Lenox Hill Hospital/Northwell Health, New York, New York. Dr. Kwasny is Professor of Preventive Medicine, Department of Preventive Medicine, Biostatistics Collaboration Center, Northwestern University, Chicago, Illinois. Dr. Beal is Associate Professor and Program Director; and Dr. Manning is Associate Professor and Vice Chairman Department of Orthopaedic Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois.

Address correspondence to: Hasham M. Alvi, MD, Barrington Orthopedic Specialists, 929 W. Higgins Road, Schaumburg, IL 60195 (tel, 847-285-4200; email, Halvi@barrringtonortho.com).

Am J Orthop. 2018;47(9). Copyright Frontline Medical Communications Inc. 2018. All rights reserved.

Abstract

The morbidity and mortality after hip fracture in the elderly are influenced by non-modifiable comorbidities. Time-to-surgery is a modifiable factor that may play a role in postoperative morbidity. This study investigates the outcomes and complications in the elderly hip fracture surgery as a function of time-to-surgery.

Using the American College of Surgeons-National Surgical Quality Improvement Program data from 2011 to 2012, a study population was generated using the Current Procedural Terminology codes for percutaneous or open treatment of femoral neck fractures (27235, 27236) and fixation with a screw and side plate or intramedullary fixation (27244, 27245) for peritrochanteric fractures. Three time-to-surgery groups (<24 hours to surgical intervention, 24-48 hours, and >48 hours) were created and matched for surgery type, sex, age, and American Society of Anesthesiologists class. Time-to-surgery was then studied for its effect on the post-surgical outcomes using the adjusted regression modeling.

A study population of 6036 hip fractures was created, and 2012 patients were assigned to each matched time-to-surgery group. The unadjusted models showed that the earlier surgical intervention groups (<24 hours and 24-48 hours) exhibited a lower overall complication rate (P = .034) compared with the group waiting for surgery >48 hours. The unadjusted mortality rates increased with delay to surgical intervention (P = .039). Time-to-surgery caused no effect on the return to the operating room rate (P = .554) nor readmission rate (P = .285). Compared with other time-to-surgeries, the time-to-surgery of >48 hours was associated with prolonged total hospital length of stay (10.9 days) (P < .001) and a longer surgery-to-discharge time (hazard ratio, 95% confidence interval: 0.74, 0.69-0.79) (P < .001). Adjusted analyses showed no time-to-surgery related difference in complications (P = .143) but presented an increase in the total length of stay (P < .001) and surgery-to-discharge time (P < .001).

Timeliness of surgical intervention in a comorbidity-adjusted population of elderly hip fracture patients causes no effect on the overall complications, readmissions, nor 30-day mortality. However, time-to-surgery of >48 hours is associated with costly increase in the total length of stay, including an increased post-surgery-to-discharge time.




Take-Home Points

  • Time-to-surgery for definitive fixation of hip fractures is a modifiable risk factor.
  • This study fails to demonstrate a benefit in delaying surgery for medical optimization as there were no time-to-surgery related differences in complications (P = 1.43).
  • Delay in definitive surgery results in an increase in the total length of stay (P < .001) and surgery-to-discharge time (P < .001) without an improvement in overall complications, readmission or 30-day mortality rates.
  • Despite numerous investigations, there are no consensus guidelines to decrease complications and mortality rates following hip fracture surgery.
  • ACS-NSQIP database is a reliable and validated database.

Despite the best efforts to optimize surgical care and postoperative rehabilitation following hip fracture, elderly patients feature alarmingly high in-hospital and 1-year mortality rates of 4.35% to 9.2%1-4 and 36%,5 respectively. Those who survive are unlikely to return to independent living, with only 17% of the patients following hip fracture being able to walk independently 6 months postoperatively, and 12% being able to climb stairs6. Possibly, these poor outcomes reflect a preoperative medical comorbidity burden rather than a measure of medical or surgical quality. Given the absence of consensus regarding optimal time-to-surgery, treating physicians often opt to delay surgical intervention for the purposes of medically optimizing highly comorbid patients without significant data to suggest clinical benefit of such practice.

Numerous investigators have attempted to identify the modifiable risk factors for complication after surgical care of elderly hip fracture patients. However, consensus guidelines of care are missing. This condition is largely due to the difficulties in effectively modifying preoperative demographic and medical comorbidities on a semi-urgent basis. However, timeliness to surgery is one area for study that the care team can affect. Although time-to-surgery is dependent on multiple factors, including time of presentation, day of week of admission, difficulties with scheduling, and administrative delays, the care team plays a role in hastening or retarding time-to-surgery. Several studies have considered various time cut-offs (24, 48, 72, and 120 hours) to define early intervention, but none have defined a specific role for early or delayed surgery. Several investigators have discovered a positive association between delayed time-to-surgery and mortality;4,8-14 however, the most rigorously conducted studies that stringently control for preoperative comorbidities and demographics conclude that variance in time-to-surgery causes no effect on the in-hospital or 1-year mortality risk.1-3,15-18  

Other investigators have shown that with early surgical intervention for hip fracture, patients experience shorter hospital stays,1,3,16,17,19-22 less days in pain,19 decreased risk of decubitus ulcers,15,17,19,22 and an increased likelihood of independence following fracture,22-25 regardless of preoperative medical status. Despite this evidence of improved outcomes with early surgery, 40% to 54% of hip fracture patients in the United States experience surgical delays of more than 24 to 48 hours. Additionally, with the recent (2013) national estimates of cost per day spent in the hospital falling between $1791 to $2289,26 minimizing the days spent in the hospital would likely lead to significant cost-savings, presuming no adverse effect on health-related outcomes. To this end, we hypothesize that the value (outcomes per associated cost)7 of hip fracture surgical care can be positively influenced by minimizing surgical wait-times. We assessed the effect of early surgical intervention, within 24 or 48 hours of presentation, on 30-day mortality, postoperative morbidity, hospital length of stay, and readmission rates in a comorbidity-adjusted population from a nationally representative cohort.

Materials and Methods

This study used the data from the American College of Surgeon-National Surgical Quality Improvement Program (ACS-NSQIP) database. With over 258 participating hospitals, this database has been widely used to identify national trends in various surgical specialties.27-34 The database includes information from participants in 43 states with hospitals ranging from rural community hospitals to large academic centers. Each site employs surgical clinical reviewers who are rigorously trained to collect data through chart review and discussion with the treating surgeon and/or patient,35 allowing for the use of robust and quality data with proven inter-rater reliability.36,37

Using the 2011 to 2012 NSQIP database, we used primary Current Procedural Terminology codes to identify all patients who underwent percutaneous (27235) or open (27236) fixation of femoral neck fractures; and fixation with a screw and side plate (27244) or intramedullary fixation (27245) for peritrochanteric fractures. The sample was divided into 3 time-to-surgery groups (<24 hours from presentation to surgery, 24-48 hours, and >48 hours) which were matched for fracture type (femoral neck or peritrochanteric), sex, age (under 75 years or ≥75 years), and American Society of Anesthesiologists (ASA) class used as a surrogate for severity of medical infirmary. The subjects were randomly matched 1:1:1 to create 3 statistically equivalent time-to-surgery groups using Proc SurveySelect (SAS version 9.2, SAS Institute).

Generalized linear models using logit link function for binary variables and identity link function for normally distributed characteristics were used to compare the 3 time-to-surgery groups. Descriptive statistics are presented as counts and percentages or least-square means with standard deviations. Preoperative lab values that were not normally distributed were log transformed and presented in their original scales with median values and 25th to 75th percentiles. Outcomes were similarly modeled.  

Total hospital stay was modeled with a negative binomial distribution. Proportional hazards models were used to model the time from operating room (OR) to discharge, censoring patients who died before discharge, with results presented as hazard ratios (HR) and 95% confidence intervals (CI) (Figure). The assumption of the proportional hazards was tested using a Wald test. Using this model, a HR of <1 denotes a longer postoperative hospital stay, as a longer hospital stay decreases the “risk” for discharge.

All models were adjusted for confounders, including race, body mass index (BMI), hypertension, chronic obstructive pulmonary disease, cancer, bleeding disorders, transfusion within 72 hours before surgery, preoperative levels of creatinine, platelet count, white blood cells (WBCs), hematocrit anesthesia type, and wound infection. These covariates were selected based upon their observed relationship to the studied outcomes and time-to-surgery groups, and were evaluated across the models for all outcomes for consistency and clarity. All statistical analyses were run at a type I error rate of 5% and performed in SAS version 9.2 software.

Results

A study population of 6036 hip fractures was identified and divided into 3 groups of 2012 subjects each based upon time-to-surgery. The groups were successfully matched for surgery type, age (≥75 years old), gender, and ASA class. In each group, 594 of the 2012 (29.5%) patients were male, 1525 (75.8%) were ≥75 years of age, 9 (.5%) were ASA Class I, 269 (13.4%) were ASA Class II, 1424 (70.8%) were ASA class III, and 309 (15.4%) were ASA class IV.

Significant differences in preoperative comorbidity burden and preoperative lab values were identified between the 3 cohorts. Increased time-to-surgery was associated with differences in race (P < .001), elevated BMI (P = .010), higher rates of congestive heart failure (P < .001), hypertension medication (P = .020), bleeding disorders (P < .001), blood transfusion within 72 hours of surgery (P < .001), and systemic sepsis (P = .001). Delay to surgery was also associated with lower preoperative sodium (P = .005), blood urea nitrogen (P = .013), serum WBC (P < .001), hematocrit (P < .001), and platelets (P < .001) (Table 1).

The unadjusted analyses revealed no association between time-to-surgery and return to OR (P = .554) nor readmission (P = .285). However, increasing time-to-surgery was associated with an increase in overall complications (P = .034), total length of hospital stay (P < .001), and 30-day mortality (P = .039) (Table 2).

The adjusted analysis controlling for preoperative demographic and comorbidity variables revealed trends toward the increased overall complications and 30-day mortality with increased time-to-surgery; these trends showed no statistical significance (P = .143 and P = .08). No statistical relationship was observed between return to OR nor readmission and time-to-surgery. Increasing time-to-surgery remained significantly associated with the increased total length of hospital stay (P < .001). The adjusted analysis also revealed that the delay of >48 hours in time-to-surgery resulted in a longer surgery-to-discharge time (P < .001) (Table 3). No evidence of violation of the proportional hazards assumption was observed in the unadjusted nor adjusted clustered proportional hazards models (Wald test, P = .27 and P = .25, respectively).

Discussion

Previous research has demonstrated an association between age,3,4,25 comorbidity burden,1,3,25 gender,3,4 and ASA class4,18,21 with outcomes following hip fractures and serves as the basis of our matched analysis statistical methodology in assessing the effect of time-to-surgery on the outcome following hip fracture surgery. Prior investigators have also established the positive correlation between increased preoperative comorbidity burden and delay in time-to-surgery.10,15 This finding was confirmed in our unadjusted comparison of 3 time-to-surgery groups. However, prior investigations have not established a clear association between time-to-surgical intervention and postoperative morbidity and mortality.1,15,16,18,20,38 This study utilized a nationally representative dataset known for its data integrity and from which 6036 patients with surgically treated hip fractures, matched for surgery type, age, gender, and ASA class (a surrogate for severity of medical infirmary), were studied using adjusted regression modeling to afford an isolated statistical assessment of the effect of time-to-surgery on outcomes following hip fracture surgery.

Despite a large sample size and rigorous statistical methodology, for many outcome measures, our results show no support for the early or late operative intervention following hip fracture. We found no difference in 30-day mortality, readmission rate, nor total complication rate between the 3 time-to-surgery cohorts. This result indicates that the care of elderly patients following hip fracture is inherently complicated and that perioperative complication risk is probably only modestly modifiable by best medical practices, including optimizing time from clinical presentation to surgery.

As expected, patients who experienced longer delays from presentation to surgery were on average, more comorbid and more likely to yield abnormal preoperative lab values. However, in the adjusted analysis, delay in time-to-surgery, presumably for medical management, was not found to be associated with improved outcomes. In the same adjusted analysis, we uniquely identified that in the patients whose surgeries were delayed for more than 48 hours, the time from surgery-to-discharge was significantly increased. As a result, these patients spent extra days in the hospital both preoperatively and postoperatively, but without any corollary improvement in the outcomes.

Recent estimates of the cost of hospital admission is approximated nationally at $2000/day.26 Although our data fail to support the formal cost-analysis of the effect of time-to-surgery in hip fracture care, a simple value-based analysis indicates that quality is preserved (no difference in outcome), whereas costly hospital days are eliminated with earlier surgery. The value in elderly hip fracture care. defined as the outcomes relative to the costs,7 is ultimately optimized by earlier time-to-surgery.

Although using a large, multi-institutional database is advantageous for finding population-based trends that are representative of a large cohort, using the ACS-NSQIP database features its limitations. Our analysis was limited to the defined scope of NSQIP and nature of the injury, whereas root cause for delay was not available for study. We were unable to identify which patients were delayed for administrative reasons or surgical convenience and which were delayed for medical optimization. Participation in the ACS-NSQIP database is voluntary, and no randomized hospital sampling was conducted. Participating hospitals were de-identified in the database. As expected, we were unable to identify the specific institution-based hip fracture protocols that may affect the outcomes following treatment for these fractures. Further, socioeconomic information and payer-status are unavailable for the study. Additionally, observations are limited to 30 days postoperative, and we cannot comment on longer-term outcomes. Finally, discharge disposition and functional outcome data are not represented, and we were unable to correlate time-to-surgery and functional recovery. However, previous studies have established that delay in time-to-surgery following hip fractures is negatively correlated with functional outcomes.22-25

Nevertheless, the ACS-NSQIP database remains one of the largest American surgical databases available, and includes care centers from nearly every state with variable demographics including rural, urban, and academic centers. The ACS performs broad-based inter-rater reliability audits on every participating site and has found an overall disagreement rate of only 1.8%. As such, although discrepancies exist between the complete patient chart and the data entered, the data found in the ACS-NSQIP database are reliable and considered a valid source of study.34,35 The large sample size, quality of data collection, wide geographic representation, and varied hospital types within the dataset possibly make our findings relevant in the majority of American healthcare settings.

Conclusion

This study demonstrates an associated increased length of hospital stay, including the increased time from surgery-to-discharge, in patients with hip fractures whose surgical intervention is delayed for >48 hours after presentation. Given the prior evidence that early surgical intervention improves the functional outcomes and the current evidence that surgical delay for any cause increases costly hospital length of stay without corollary improvement in the outcomes, a value-based assessment of hip fracture care argues for early surgical intervention whenever possible. Our findings should inform physician, institution, and policy maker value-based decision making regarding the best practices in geriatric hip fracture care.

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Figures/Tables

Table 2. Estimated Event Rates from Matched Cohorts (Unadjusted)

 

Time From Presentation to Definitive Fixation

Outcomes

<24 hours

24-48 hours

>48 hours

P-value

Overall complication rate

15.30%

15.30%

17.90%

0.034

Total length of stay

5.4

6.7

10.9

<0.001

(mean days, 95% confidence interval)

(5.2, 5.7)

(6.5, 7.0)

(10.3, 11.5)

Time from OR to discharge

-ref-

0.96

0.74

<0.001

(Hazard ratio)

(0.90,1.02)

(0.69, 0.79)

Return to OR

2.40%

2.40%

2.00%

0.554

Readmission

9.60%

8.40%

8.30%

0.285

30-day mortality rate

5.80%

5.30%

7.20%

0.039

Abbreviation: OR, operating room.

Table 3. Estimated Event Rates from Matched Cohorts (Adjusteda)

 

Time from Presentation to Definitive Fixation

Outcomes

<24 hours

24-48 hours

>48 hours

P-value

Overall complication rate

11.70%

10.70%

12.60%

0.143

Total length of stay

4.2

5.1

7.6

<0.001

(mean days, 95% confidence interval)

(4.0, 4.5)

(4.8, 5.5)

(7.1, 8.3)

Time from OR to discharge

-ref-

1.03

0.87

<0.001

(Hazard ratio)

(0.97, 1.09)

(0.81, 0.92)

Return to OR

2.10%

2.10%

1.60%

0.541

Readmission

7.20%

6.40%

6.00%

0.304

30-day mortality rate

4.20%

3.70%

5.20%

0.08

aModel adjusted for race, hypertension medication, cancer, bleeding disorders, transfusion within 72 hours before surgery, emergency status, wound infection, anesthesia type (general), body mass index (18.5-25), history of chronic obstructive pulmonary disease, and preoperative levels of creatinine, platelet count, white blood cell count, and hematocrit.

References

References

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