Prognostic factors for predicting health-related quality of life after intramedullary nailing of tibial fractures: a randomized controlled trial

Abstract

Aims

Using tibial shaft fracture participants from a large, multicentre randomized controlled trial, we investigated if patient and surgical factors were associated with health-related quality of life (HRQoL) at one year post-surgery.

Methods

The Study to Prospectively Evaluate Reamed Intramedullary Nails in Patients with Tibial Fractures (SPRINT) trial examined adults with an open or closed tibial shaft fracture who were treated with either reamed or unreamed intramedullary nails. HRQoL was assessed at hospital discharge (for pre-injury level) and at 12 months post-fracture using the Short Musculoskeletal Functional Assessment (SMFA) Dysfunction, SMFA Bother, 36-Item Short Form 36 (SF-36) Physical, and SF-36 Mental Component scores. We used multiple linear regression analysis to determine if baseline and surgical factors, as well as post-intervention procedures within one year of fracture, were associated with these HRQoL outcomes. Significance was set at p < 0.01. We hypothesize that, irrespective of the four measures used, prognosis is guided by both modifiable and non-modifiable factors and that patients do not return to their pre-injury level of function, nor HRQoL.

Results

For patient and surgical factors, only pre-injury quality of life and isolated fracture showed a statistical effect on all four HRQoL outcomes, while high-energy injury mechanism, smoking, and race or ethnicity, demonstrated statistical significance for three of the four HRQoL outcomes. Patients who did not require reoperation in response to infection, the need for bone grafts, and/or the need for implant exchanges had statistically superior HRQoL outcomes than those who did require intervention within one year after initial tibial fracture nailing.

Conclusion

We identified several baseline patient factors, surgical factors, and post-intervention procedures within one year after intramedullary nailing of a tibial shaft fracture that may influence a patient’s HRQoL.

Cite this article: Bone Jt Open 2021;2(1):22–32.

Introduction

Although intramedullary nailing is the standard treatment method for tibial shaft fractures, these injuries are associated with considerable complications following surgery, including acute compartment syndrome, chronic leg and knee pain, muscle weakness, and limitations in activities of daily living and health-related quality of life (HRQoL).^1-6 Data from the Study to Prospectively Evaluate Reamed Intramedullary Nails in Patients with Tibial Fractures (SPRINT) trial, a multicentre trial of tibial shaft fracture patients treated with intramedullary nailing, found that many patients do not return to a satisfactory level of function at long-term follow-up.⁷

Some previous investigations have assessed the effect of various factors on the success of intramedullary nailing of tibial shaft fractures in terms of function and HRQoL using standardized and validated self-assessment questionnaires.^5,8-13 However, these studies were limited methodologically by either relatively small sample sizes, one or few participating hospitals, lack of adjustment for confounders, and/or non-standardized perioperative patient-care regimens. Thus, a more comprehensive analysis evaluating multiple factors, which addresses these limitations, is warranted to determine which characteristics are most predictive of function and HRQoL following nailing of tibial shaft fractures. The SPRINT trial measured the impact of tibial shaft fractures on an individual’s functioning and mental health using the Short Musculoskeletal Function Assessment¹⁴ (SMFA) Dysfunction and Bother domains that focus on patients with musculoskeletal disorders, as well as the more generic 36-Item Short Form¹⁵ (SF-36) Physical Component Score (SF-36 PCS) and SF-36 Mental Component Score (SF-36 MCS) for a one-year follow-up period. Previous literature has suggested that disease-specific instruments (SMFA) can detect small but important changes as compared to more generic measures (SF-36).^8,16 Given these differences, we included both instruments in this analysis.

Using data from the SPRINT trial, we aimed to investigate whether any baseline or surgical factors, as well as reoperation, were associated with worse function and HRQoL, measured using the SF-36 and SMFA, at one-year post-surgery.⁷ We hypothesize that, irrespective of the four measures used, prognosis is guided by both modifiable and non-modifiable factors and that patients do not return to their pre-injury level of function, nor HRQoL.

Methods

SPRINT was a multicentre, blinded randomized trial that recruited 1,319 adults with a tibial shaft fracture (Tscherne Type 0 to 3,¹⁷ Gustilo Type I to IIIB)¹⁸ from 29 clinical sites in North America and the Netherlands. Participants were randomized to fracture repair with either reamed or unreamed intramedullary nailing and were followed postoperatively for 12 months. Patients with fractures that were not amenable to either reamed or unreamed intramedullary nailing techniques and those with pathological fractures were excluded. The primary composite outcome included bone-grafting, implant exchange, and dynamization in patients with a fracture gap of < 1 cm, as well as infection and need for fasciotomy (ClinicalTrials.gov identifier: NCT00038129).^7,19,20 The trial received approval from the Hamilton Integrated Research Ethics Board (REB# 99-077), and from all participating clinical sites’ Research Ethics Boards.

HRQoL and function questionnaires

At hospital discharge, participants were asked to indicate their pre-injury level HRQoL and function using the SMFA Dysfunction Index, SMFA Bother Index, SF-36 PCS, and SF-36 MCS. HRQoL was measured two weeks after discharge, six weeks postoperatively, and three, six, nine, and 12 months post-fracture. The SMFA is a 46-item questionnaire that has been validated as a measure of patient function.²¹ The minimally important difference (MID) is approximately seven points for the SMFA Dysfunction Index score.⁸ The SF-36 is a validated self-administered or interview administered 36-item questionnaire that measures HRQoL.^7,15 The MID is between three and five points for the SF-36.¹⁵ Scores of each SF-36 and SMFA domain range from 0 to 100. Higher scores on the SF-36 and lower scores on the SMFA indicate better function and HRQoL.

Selection of prognostic factors

We selected baseline factors a priori based on biological rationale and previous reports in the literature.^5,8-13 We included a total of 23 patient, fracture, treatment, and surgical factors in our models and an interaction term of open versus closed and reamed versus unreamed since the treatment effect differed across these subgroups in the primary analysis.⁷ All patient, fracture, treatment, and surgical factors were collected and recorded on case report forms prior to hospital discharge. Categories for the included factors in our analysis were based on the response options on the case report forms. Finally, all models were adjusted for the respective pre-injury HRQoL or function measure. For each potential factor, we proposed an a priori hypothesized effect for all four dependent variables. In the Results section, we will refer to these models examining baseline and surgical factors as being part of Phase I of the analysis.

Post-intervention factors

As separate models, we also looked at post-intervention factors that may be associated with HRQoL or function, which were primarily complications and reoperations. Separate models were developed for each dependent variable. In the results section, we will refer to these models examining post-intervention factors as being part of Phase II of the analysis.

Statistical analysis

We included participants with complete data for all factors and respective HRQoL and function measures in each model. We used descriptive statistics to summarize all factors. To determine which patient, fracture, treatment, and surgical factors were associated with lower HRQoL, we created four multiple linear regression models using backward elimination as the selection procedure with the dependent variables. We decided a priori that the SMFA Dysfunction would be the primary analysis and other questionnaires would be secondary. In a separate analysis, we used the same methodology to determine which post-intervention factors were associated with lower HRQoL at 12 months post-fracture. These models also included the factors in the initial prognostic models that were found to be associated with HRQoL.

All tests were two-tailed and p < 0.01 was considered statistically significant. We reported results as mean differences (MDs) and 95% confidence intervals (CIs). All analyses were done with SAS v. 9.1 (SAS Institute, Cary, North Carolina, USA).

Results

Of the 1,319 fracture patients enrolled into the SPRINT trial, not all completed the SMFA and SF-36 questionnaires at the 12-month follow-up visit. Therefore, a total of 715 SPRINT participants were included in this analysis. The Phase I patient, fracture, treatment, and surgical factor characteristics are displayed in Table I.

Table I.

Phase I incidence of predictor variables (n = 735).

Variable	Total (n = 735)
Patient factors, n (%)
Mean age, yrs (SD)	40.0 (15.8)
Male	530 (72.1)
Race
Black	42 (5.7)
White	622 (84.6)
Other*	71 (9.7)
Mechanism of injury
High-energy	441 (60.1)
Low-energy†	293 (39.9)
Current smoker	223 (30.3)
Bilateral	6 (0.8)
Open	217 (29.5)
Reamed	398 (54.1)
Interaction
Open/reamed	117 (15.9)
Open/non-reamed	100 (13.6)
Closed/reamed	280 (38.1)
Closed/non-reamed	236 (32.1)
Anticoagulants use	105 (14.3)
NSAIDs use	57 (7.8)
Isolated fracture	504 (68.6)
AO/OTA fracture class
A	416 (56.6)
B	221 (30.1)
C	98 (13.3)
Location
Proximal and proximal-middle	44 (8.6)
Distal and distal-middle	357 (69.5)
Middle	113 (22.0)
Surgical factors, n (%)
Surgeon (including fellow)	294 (40.0)
Resident	441 (60.0)
Nail material
Titanium	462 (62.9)
Stainless steel	271 (36.9)
No. of locking screws
≥ 2 or more on both sides	411 (55.9)
< 2 on at least one side	293 (39.9)
Tendon split	188 (25.6)
Tendon retraction	544 (74.0)
Portal
Superior	570 (77.6)
Inferior	161 (21.9)
Fracture gap – adjudicated
Gap ≥ 1 cm	25 (3.4)
Gap < 1 cm	50 (6.8)
No gap	660 (89.8)
Time from injury
Late ( > 24 hours)	272 (37.0)
Middle (6 to 24 hours)	348 (47.3)
Early ( < 6 hours)	112 (15.2)
Interaction
Open/late	8 (1.1)
Open/middle	122 (16.6)
Open/early	86 (11.7)
Closed/late	264 (35.9)
Closed/middle	226 (30.7)
Closed/early	26 (3.5)
Fasciotomy at initial surgery	22 (3.0)
Postoperative weight-bearing
Full	72 (9.8)
Partial or non-weightbearing	663 (90.2)
Time to coverage
Primary closure	127 (17.3)
Delayed Primary closure	54 (7.3)
Secondary closure	36 (4.9)
Closed fracture	518 (70.5)

^*Other includes all ethnicities except for Black and White.

^†High energy includes motor vehicle accident, crush injury, blunt direct trauma. Low energy includes fall, twist, penetrating direct trauma.

NSAIDs, non-steroidal anti-inflammatory drugs

Phase I - SMFA Dysfunction

A higher pre-injury SMFA Dysfunction score (worse function) (MD 3.17 for every ten-point increase (95% CI 2.25 to 4.09); p < 0.001), older age (MD 2.14 for every ten-year increase (95% CI 1.37 to 2.92); p < 0.001), a fracture sustained from a high-energy (vs low-energy) mechanism of injury (MD 4.09 (95% CI 1.38 to 6.79); p = 0.003), being a current smoker (vs non-smoker) (MD 4.43 (95% CI 1.91 to 6.95); p < 0.001), and having a multi-trauma injury (vs isolated fracture) (MD 6.66 (95% CI 4.00 to 9.32); p < 0.001) were associated with statistically significantly higher SMFA Dysfunction scores, indicating worse function, at the one-year follow-up (Table II). The only factor which reached the MID and was clinically significant for worse function was the presence of multiple trauma (vs having an isolated fracture).

Table II.

Short Musculoskeletal Functional Assessment Dysfunction (primary HRQoL outcome) (n = 681).

Factors	Mean difference (95% CI)	p-value
Phase I – Reduced model
Patient factors
Pre-injury QoL score (10-point increase)	3.17 (2.25 to 4.09)	< 0.001
Age (10 yr increase)	2.14 (1.37 to 2.92)	< 0.001
Male vs female	N/A	N/A
Race		0.06
Black vs White	3.72 (-1.29 to 8.73)
Other* vs White	3.98 (-0.03 to 7.99)
Current smoker vs not	4.43 (1.91 to 6.95)	< 0.001
Fracture factors
Mechanism of injury
High-energy vs low-energy†	4.09 (1.38 to 6.79)	0.003
Bilateral vs unilateral	N/A	N/A
Reamed vs non-reamed nail
Open	2.44 (-1.79 to 6.67)	0.26
Closed	0.92 (-1.84 to 3.68)	0.51
Open vs closed
Reamed	4.74 (1.12 to 8.35)	0.010
Non-reamed	3.21 (-0.44 to 6.85)	0.08
Additional injuries vs isolated fracture	6.66 (4.00 to 9.32)	< 0.001
AO/OTA fracture class		0.043
B vs A	2.72 (0.08 to 5.36)
C vs A	3.64 (0.07 to 7.21)
Location of fracture
Proximal and proximal-middle vs middle	N/A	N/A
Distal and distal-middle vs middle	N/A	N/A
Treatment factors
Anticoagulants use vs none	N/A	N/A
NSAIDs use vs none	N/A	N/A
Surgical factors
Resident vs surgeon (including fellow)‡	2.14 (-0.24 to 4.51)	0.08
Nail material
Titanium vs stainless steel	N/A	N/A
No. of locking screws
≥ 2 on both sides vs < 2 on at least one side	3.01 (0.61 to 5.40)	0.014
Tendon split vs tendon retraction	N/A	N/A
Portal
Inferior vs Superior	N/A	N/A
Fracture gap – adjudicated
Gap ≥ 1 cm vs no gap	N/A	N/A
Gap < 1 cm vs no gap	N/A	N/A
Time from injury to surgery
Late vs early	N/A	N/A
Mid vs early	N/A	N/A
Fasciotomy at initial surgery vs none	N/A	N/A
Postoperative weight-bearing status
Full vs partial or non-weightbearing	N/A	N/A
Phase II – Post-intervention model§
Reoperations in response to infection		0.001
Late vs none¶	15.54 (4.07 to 27.01)
Early vs none	10.17 (2.48 to 17.87)
Fasciotomy
Early vs none	-2.84 (-10.39 to 4.72)	0.461
Bone graft or implant exchange		< 0.001
Late vs none	19.70 (9.00 to 30.40)
Early vs none	14.58 (5.56 to 23.59)
Nonoperatively treated infection
Early vs none	-4.22 (-14.37 to 5.93)	0.414
Dynamization		0.420
Late vs none	5.77 (-3.68 to 15.21)
Early vs none	1.22 (-2.70 to 5.15)

^*Other includes all ethnicities except for Black and White.

^†High-energy includes motor vehicle accident, crush injury, blunt direct trauma. Low-energy includes fall, twist, penetrating direct trauma.

^‡Resident becomes MD 0.77 (95% CI 2.11 to 3.66); p = 0.60 when centre is included in the model as a covariate.

^§The Phase II model included the baseline predictor variables from the reduced model as covariates. Phase II models also include the following covariates for adjustment: open, reamed, interaction of open with reamed, baseline SMFA Dysfunction, age, race, mechanism of injury, smoking status, isolated fracture, AO classification, resident, number of locking screws.

^¶Early is defined as prior to eight months from initial surgery and late is defined as eight months up to one year.

N/A, not applicable; NSAIDs, non-steroidal anti-inflammatory drugs; QoL, quality of life

SMFA Bother

A higher pre-injury SMFA Bother score (worse function) (MD 4.44 for every ten-point increase (95% CI 3.32 to 5.56); p < 0.001), being Black (vs White) (MD 1.64 (95% CI -5.13 to 8.40); p = 0.0099), being another race (vs White) (MD 8.51 (95% CI 3.01 to 14.01); p = 0.009), a fracture sustained from a high-energy (vs low-energy) mechanism of injury (MD 5.13 (95% CI 1.41 to 8.84); p = 0.007), being a current smoker (vs non-smoker) (MD 4.65 (95% CI 1.19 to 8.10); p = 0.009) and having a multitrauma injury (vs isolated fracture) (MD 11.76 (95% CI 8.09 to 15.42); p < 0.001) were associated with statistically significantly higher SMFA Bother scores, indicating being more bothered by functional problems, at the one-year follow-up (Table III). The two factors which reached the MID and were clinically significant for worse function were being another race or ethnicity (vs White) and the presence of multiple trauma (vs having an isolated fracture).

Table III.

Short Musculoskeletal Functional Assessment Bother (n = 569).

Factors	Mean difference (95% CI)	p-value
Phase I - Reduced model
Patient factors
Pre-injury QoL score (10-point increase)	4.44 (3.32 to 5.56)	< 0.001
Age (10 yr increase)	1.32 (0.18 to 2.45)	0.02
Male vs female	N/A	N/A
Race		0.009
Black vs White	1.64 (-5.13 to 8.40)
Other* vs White	8.51 (3.01 to 14.01)
Current smoker vs not	4.65 (1.19 to 8.10)	0.009
Fracture factors
Mechanism of injury
High-energy vs low-energy†	5.13 (1.41 to 8.84)	0.007
Bilateral vs unilateral	-12.44 (-24.99 to 0.11)	0.052
Reamed vs non-reamed nail
Open	3.05 (-2.80 to 8.89)	0.31
Closed	3.21 (-0.64 to 7.06)	0.10
Open vs closed
Reamed	5.43 (0.36 to 10.51)	0.04
Non-reamed	5.60 (0.67 to 10.53)	0.03
Additional injuries vs isolated fracture	11.76 (8.09 to 15.42)	< 0.001
AO/OTA fracture class
B vs A	N/A	N/A
C vs A	N/A	N/A
Location of fracture
Proximal and proximal-middle vs middle	N/A	N/A
Distal and distal-middle vs middle	N/A	N/A
Treatment factors
Anticoagulants use vs none	N/A	N/A
NSAIDs use vs none	-6.51 (-12.45 to -0.57)	0.03
Surgical factors
Resident vs surgeon (including fellow)‡	N/A	N/A
Nail material
Titanium vs stainless steel	N/A	N/A
No. of locking screws
≥ 2 on both sides vs < 2 on at least one side	N/A	N/A
Tendon split vs tendon retraction	N/A	N/A
Portal
Inferior vs Superior	N/A	N/A
Fracture gap – adjudicated
Gap ≥ 1 cm vs no gap	N/A	N/A
Gap < 1 cm vs no gap	N/A	N/A
Time from injury to surgery
Late vs early	N/A	N/A
Mid vs early	N/A	N/A
Fasciotomy at initial surgery vs none	9.54 (0.16 to 18.91)	0.046
Postoperative weight-bearing status
Full vs partial or non-weightbearing	-5.95 (-11.41 to -0.49)	0.03
Phase II – Post-intervention model
Reoperations in response to infection		0.036
Late vs none§	20.56 (-2.03 to 43.15)
Early vs none	11.23 (-0.18 to 22.65)
Fasciotomy
Early vs none	-7.97 (-20.12 to 4.17)	0.198
Bone graft or implant exchange		0.027
Late vs none	13.87 (-3.39 to 31.12)
Early vs none	13.75 (1.58 to 25.92)
Nonoperatively treated infection
Early vs none	0.08 (-13.81 to 13.98)	0.991
Dynamization		0.514
Late vs none	7.28 (-5.59 to 20.15)
Early vs none	-0.73 (-6.42 to 4.95)

^*Other includes all ethnicities except for Black and White.

^†High-energy includes motor vehicle accident, crush injury, blunt direct trauma. Low-energy includes fall, twist, penetrating direct trauma.

^‡The Phase II model included the baseline predictor variables from the reduced model as covariates. Phase II models also include the following covariates for adjustment: open, reamed, interaction of open with reamed, baseline SMFA Bother, age, race, mechanism of injury, smoking status, bilateral fractures, NSAID use, isolated fracture, fasciotomy at initial surgery, weight-bearing status.

^§Early is defined as prior to eight months from initial surgery and late is defined as eight months up to one year.

N/A, not applicable.

SF-36 PCS

A lower pre-injury SF-36 PCS score (worse QoL) (MD -3.47 for every 10-point decrease (95% CI -4.43 to -2.62); p < 0.001), older age (MD -1.00 for every 10 year increase (95% CI -1.52 to -0.49);p < 0.001), being Black (vs White) (MD -1.94 (95% CI -5.17 to 1.29); p = 0.003), being another race (vs White) (MD -4.16 (95% CI -6.66 to -1.66); p = 0.003), a fracture sustained from a high-energy (vs low-energy) mechanism of injury (MD -2.44 (95% CI -4.15 to -0.73); p = 0.005), being a current smoker (vs non-smoker) (MD -3.47 (95% CI -5.08 to -1.85); p < 0.001), having a multi-trauma injury (vs isolated fracture) (MD -3.72 (95% CI -5.42 to -2.01); p < 0.001), an open fracture ((vs closed fracture (reamed nail)) (MD -5.39 (95% CI -7.67 to -3.11); p < 0.001), and (vs closed fracture (unreamed nail)) (MD -3.26 (95% CI -5.59 to -0.92); p = 0.006)), and being treated by an orthopaedic resident (vs orthopaedic surgeon, including fellows) (MD -2.03 (95% CI -3.54 to -0.51); p = 0.009) were associated with statistically significantly lower SF-36 PCS scores, indicating worse physical HRQoL, at the one-year follow-up (Table IV). However, if the clinical centre is included as a covariate, then being treated by a resident versus surgeon was no longer statistically significant (p = 0.096). The five factors which were clinically significant for worse physical HRQoL were being another race or ethnicity (vs White), being a current smoker (vs a non-smoker), having an open fracture (vs a closed fracture treated with a reamed or unreamed nail), having a lower pre-injury PCS score, and the presence of multiple trauma (vs having an isolated fracture).

Table IV.

36-Item Short Form Physical Component Score (n = 715).

Factors	Mean difference (95% CI)	p-value
Phase I - Reduced model
Patient factors
Pre-injury QoL score (10-point increase)	-3.47 (-4.32 to -2.62)	< 0.001
Age (10 yr increase)	-1.00 (-1.52 to -0.49)	< 0.001
Male vs female	N/A	N/A
Race		0.003
Black vs White	-1.94 (-5.17 to 1.29)
Other* vs White	-4.16 (-6.66 to -1.66)
Current smoker vs not	-3.47 (-5.08 to -1.85)	< 0.001
Fracture factors
Mechanism of injury
High-energy vs low-energy†	-2.44 (-4.15 to -0.73)	0.005
Bilateral vs unilateral	N/A	N/A
Reamed vs non-reamed nail
Open	-2.53 (-5.23 to 0.17)	0.07
Closed	-0.40 (-2.15 to 1.35)	0.66
Open vs closed
Reamed	-5.39 (-7.67 to -3.11)	< 0.001
Non-reamed	-3.26 (-5.59 to -0.92)	0.006
Additional injuries vs isolated fracture	-3.72 (-5.42 to -2.01)	< 0.001
AO/OTA fracture class
B vs A	N/A	N/A
C vs A	N/A	N/A
Location of fracture
Proximal and proximal-middle vs middle	N/A	N/A
Distal and distal-middle vs middle	N/A	N/A
Treatment factors
Anticoagulants use vs none	N/A	N/A
NSAIDs use vs none	N/A	N/A
Surgical factors
Resident vs surgeon (including fellow)‡	-2.03 (-3.54 to -0.51)	0.009
Nail material
Titanium vs stainless steel	N/A	N/A
No. of locking screws
≥ 2 on both sides vs < 2 on at least one side	N/A	N/A
Tendon split vs tendon retraction	N/A	N/A
Portal
Inferior vs Superior	N/A	N/A
Fracture gap – adjudicated
Gap ≥ 1 cm vs no gap	N/A	N/A
Gap < 1 cm vs no gap	N/A	N/A
Time from injury to surgery
Late vs early	N/A	N/A
Mid vs early	N/A	N/A
Fasciotomy at initial surgery vs none
Postoperative weight-bearing status	N/A	N/A
Full vs partial or non-weightbearing	2.24 (-0.22 to 4.71)	0.07
Phase II – Post-intervention model§
Reoperations in response to infection
Late vs none¶	-8.14 (-15.65 to -0.64)	0.017
Early vs none	-4.78 (-9.41 to -0.15)
Fasciotomy
Early vs none	0.29 (-4.67 to 5.25)	0.908
Bone graft or implant exchange		0.005
Late vs none	-7.98 (-14.27 to -1.68)
Early vs none	-6.31 (-11.99 to -0.62)
Nonoperatively treated infection
Early vs none	3.11 (-3.28 to 9.49)	0.340
Dynamization		0.031
Late vs none	-5.47 (-11.66 to 0.72)
Early vs none	-2.70 (-5.25 to -0.14)

^*Other includes all ethnicities except for Black and White.

^†High-energy includes motor vehicle accident, crush injury, blunt direct trauma. Low-energy includes fall, twist, penetrating direct trauma.

^‡Resident becomes MD -1.59 (95% CI -3.47 to 0.28); p = 0.096 when centre is included in the model as a covariate.

^§The Phase II model included the baseline predictor variables from the reduced model as covariates. Phase II models also include the following covariates for adjustment: open, reamed, interaction of open with reamed, baseline SF-36 PCS, age, race, mechanism of injury, smoking status, isolated fracture, resident, weight-bearing status.

^¶Early is defined as prior to eight months from initial surgery and late is defined as eight months up to one year.

N/A, not applicable; NSAIDs, non-steroidal anti-inflammatory drugs; QoL, quality of life.

SF-36 MCS

A lower pre-injury SF-36 MCS score (worse QoL) (MD -5.13 for every ten-point decrease (95% CI -6.04 to -4.22); p < 0.001), being Black (vs White) (MD -4.16 (95% CI -7.59 to -0.74); p < 0.001), being another race (vs White) (MD -4.82 (95% CI -7.53 to -2.12); p < 0.001), having a multi-trauma injury (vs isolated fracture) (MD -3.53 (95% CI -5.28 to -1.79); p < 0.001), mid tibia fracture (vs distal and distal-mid tibia fracture) (MD -1.84 (95% CI -3.78 to 0.11); p = 0.005), having a proximal and proximal-mid tibia fracture (vs mid tibia fracture) (MD -2.53 (95% CI -5.69 to 0.63); p = 0.005), a gap ≥ 1 cm (vs no gap) (MD -7.79 (95% CI -12.45 to -3.14); p = 0.004), and a gap < 1 cm (vs no gap) (MD -0.84 (95% CI -3.98 to 2.31); p = 0.004) were associated with statistically significantly lower SF-36 MCS scores, indicating worse mental HRQoL, at the one-year follow-up for the reduced model (Table V). The three factors which reached the MID and were clinically significant for worse mental HRQoL were being Black or another race or ethnicity (vs White), having a lower pre-injury MCS score, and the presence of multiple trauma (vs having an isolated fracture).

Table V.

36-Item Short Form Mental Component Score (n = 708).

Factors	Mean difference (95% CI)	p-value
Phase I - Reduced Model
Patient factors
Pre-injury QoL score (10-point increase)	-5.13 (-6.04 to -4.22)	< 0.001
Age (10 yr increase)	N/A	N/A
Male vs female	N/A	N/A
Race		< 0.001
Black vs White	-4.16 (-7.59 to -0.74)
Other* vs White	-4.82 (-7.53 to -2.12)
Current smoker vs not	-1.61 (-3.32 to 0.10)	0.06
Fracture factors
Mechanism of injury
High energy vs low energy†	N/A	N/A
Bilateral vs unilateral	6.58 (0.33 to 12.84)	0.04
Reamed vs non-reamed nail
Open	0.22 (-2.68 to 3.12)	0.88
Closed	-0.70 (-2.56 to 1.17)	0.46
Open vs closed
Reamed	-0.53 (-2.96 to 1.90)	0.67
Non-reamed	-1.45 (-3.96 to 1.05)	0.26
Additional injuries vs isolated fracture	-3.53 (-5.28 to -1.79)	< 0.001
AO/OTA fracture class
B vs A	N/A	N/A
C vs A	N/A	N/A
Location of fracture		0.005
Proximal and proximal-middle vs middle	2.53 (-0.63 to 5.69)
Distal and distal-middle vs middle	-1.84 (-3.78 to 0.11)
Treatment factors
Anticoagulants use vs none	N/A	N/A
NSAIDs use vs none	N/A	N/A
Surgical factors
Resident vs surgeon (including fellow)	N/A	N/A
Nail material
Titanium vs stainless steel	1.85 (0.21 to 3.49)	0.03
No. of locking screws
≥ 2 on both sides vs < 2 on at least one side	N/A	N/A
Tendon split vs tendon retraction	N/A	N/A
Portal
Inferior vs Superior	N/A	N/A
Fracture gap – adjudicated		0.004
Gap ≥ 1 cm vs no gap	-7.79 (-12.45 to -3.14)
Gap < 1 cm vs no gap	-0.84 (-3.98 to 2.31)
Time from injury to surgery
Late vs early	N/A	N/A
Mid vs early	N/A	N/A
Fasciotomy at initial surgery vs none	N/A	N/A
Postoperative weight-bearing status
Full vs partial or non-weightbearing	N/A	N/A
Phase II – Post-intervention model (all post-intervention factors in the same model)‡
Reoperations in response to infection		0.188
Late vs none§	-6.30 (-14.49 to 1.89)
Early vs none	-2.85 (-7.83 to 2.14)
Fasciotomy
Early vs none	0.97 (-4.32 to 6.26)	0.719
Bone graft or implant exchange		0.408
Late vs none	-4.63 (-11.45 to 2.19)
Early vs none	0.29 (-5.84 to 6.42)
Nonoperatively treated infection
Early vs none	-3.26 (-10.14 to 3.61)	0.352
Dynamization		0.826
Late vs none	0.89 (-5.80 to 7.58)
Early vs none	0.82 (-1.99 to 3.62)

^*Other includes all ethnicities except for Black and White.

^†High-energy includes motor vehicle accident, crush injury, blunt direct trauma. Low-energy includes fall, twist, penetrating direct trauma.

^‡The Phase II model included the baseline predictor variables from the reduced model as covariates. Phase II models also include the following covariates for adjustment: open, reamed, interaction of open with reamed, baseline SF-36 MCS, race, smoking status, bilateral fractures, isolated fracture, location of fracture, nail material, fracture gap.

^§Early is defined as prior to eight months from initial surgery and late is defined as eight months up to one year.

N/A, not applicable; NSAIDs, non-steroidal anti-inflammatory drugs; QoL, quality of life.

Phase II - Post-intervention factors

The incidence of the post-intervention factors is presented in Table VI.

Table VI.

Phase II incidence of predictor variables.

Factor	Total (n = 1,226)	Baseline and 12 month SMFA Dysfunction Index (n = 687)
Reoperations in response to infection, n (%)
Late*	12 (1.0)	7 (1.0)
Early	39 (3.2)	16 (2.3)
None	1,175 (95.8)	664 (96.7)
Fasciotomy, n (%)
Late*	0 (0.0)	0 (0.0)
Early	22 (1.8)	16 (2.3)
None	1204 (98.2)	671 (97.7)
Bone graft, n (%)
Late*	6 (0.5)	4 (0.6)
Early	11 (0.9)	5 (0.7)
None	1,209 (98.6)	678 (98.7)
Implant exchange, n (%)
Late*	15 (1.2)	7 (1.0)
Early	25 (2.0)	10 (1.5)
None	1,186 (96.7)	670 (97.5)
Bone graft and/or implant exchange, n (%)
Late*	17 (1.4)	8 (1.2)
Early	31 (2.5)	11 (1.6)
None	1,178 (96.1)	668 (97.2)
Nonoperatively treated infection, n (%)
Late*	0 (0.0)	0 (0.0)
Early	19 (1.5)	9 (1.3)
None	1,207 (98.5)	678 (98.7)
Dynamization, n (%)
Late*	18 (1.5)	11 (1.6)
Early	99 (8.1)	64 (9.3)
None	1,109 (90.5)	612 (89.1)

^*Early is defined as prior to eight months from initial surgery and late is defined as eight months up to one year.

SMFA, Short Musculoskeletal Functional Assessment

SMFA Dysfunction

Having a late reoperation in response to infection (vs no reoperation) (MD 15.54 (95% CI 4.07 to 27.01); p = 0.001), an early reoperation in response to infection (vs no reoperation) (MD 10.17 (95% CI 2.48 to 17.87); p = 0.001), a late bone graft or implant exchange (vs no bone graft or implant exchange) (MD 19.70 (95% CI 9.00 to 30.40); p < 0.001), and an early bone graft or implant exchange (vs no bone graft or implant exchange) (MD 14.58 (95% CI 5.56 to 23.59); p < 0.001) were associated with statistically significantly higher SMFA Dysfunction scores, indicating worse function, at the one-year follow-up (Table II). All the statistically significant mean differences reached the MID for the SMFA Dysfunction Index.

SMFA Bother

No post-intervention factors were found to be associated with SMFA Bother scores (p ≥ 0.01) (Table III).

SF-36 PCS

Having a late bone graft or implant exchange (vs no bone graft or implant exchange) (MD -7.98 (95% CI -14.27 to -1.68); p = 0.005) and an early bone graft or implant exchange (vs no bone graft or implant exchange) (MD -6.31 (95% CI -11.99 to -0.62); p = 0.005) were associated with statistically significantly lower SF-36 PCS scores, indicating worse physical HRQoL, at the one-year follow-up (Table IV). None of the statistically significant mean differences reached the MID for the SF-36.

SF-36 MCS

No post-intervention factors were found to be associated with SF-36 MCS scores (p ≥ 0.01) (Table V).

Discussion

Only pre-injury HRQoL/function and type of injury (isolated fracture vs multi-trauma injury) were found to be statistically significantly associated with all four HRQoL and function outcome measures. Mechanism of injury (high vs low energy), smoking status (current smoker vs a non-smoker), and race (Black vs White and another race vs White) demonstrated association with three of the four HRQoL and function outcome measures.

Cessation of smoking, which is the only aforementioned factor that is under direct control of the patient, should be recommended to patients. Some prior studies have reported that smoking is detrimental to fracture healing and/or may lead to reoperation.^22,23 Smoking rates have been reported to be higher among low socioeconomic groups.^24,25 Given that association, smoking may also be a proxy for socioeconomic variables that are associated with HRQoL and function. Specifically, focusing on tibial fractures, in a prospective longitudinal study that evaluated the socioeconomic implications of isolated tibial and femoral fractures in adults caused by road traffic injuries in Uganda, HRQoL at two years was found to have the strongest association with income at 24 months.²⁶ Other studies evaluating HRQoL and function following any type of fracture have reported lower HRQoL scores among fracture patients with low socioeconomic status compared with high socioeconomic status.^27,28

High-energy mechanisms of injury had a statistically negative effect on three of four HRQoL and function outcome measures compared to low-energy events. This is consistent with the current authors’ prior study on this same group of patients which showed an increased risk of a reoperation within one year of intramedullary nailing for high energy injuries (odds ratio 1.57 (95% CI 1.05 to 2.35).²⁰ Similarly, other researchers have found an association between the mode of injury with time to full weight-bearing and/or incidence of deep infection.²⁹

The impact of race or ethnicity on HRQoL and function has received limited attention in lower limb fracture patients. Dreisman et al³⁰ found that being Black and Hispanic were independent predictors of worse functional outcome at 12 months following fractures of the lower limb. These authors concluded that disparities may result from multifactorial socioeconomic factors, including socioeconomic status and education levels that were not controlled in their study. Furthermore, using population data from New York State, Dy et al³¹ found that there were race- and insurance-based disparities in delivery of care for patients with hip fracture and that targeted interventions should be developed to mitigate effects of disparities on patients at greatest risk. These findings, in addition to those in our study, emphasize the need to focus on factors other than just the fracture and its treatment to improve long-term outcomes.

Patients who did not require reoperation had statistically better HRQoL and function outcomes than those who did, whether these procedures were done early (i.e. prior to eight months) or late (i.e. eight to 12 months) with respect to the time of initial fixation surgery. This result highlights the importance of avoiding a complication post-surgery, if possible, as well as emphasizes that if a patient does experience a complication, the timing of the complication (early vs late) does not make a difference in terms of HRQoL and function outcomes.

In a previous publication using data from the SPRINT trial, a mixed model repeated measures analysis was conducted by Lin et al³² for the entire cohort to determine factors associated with HRQoL. They found that significant predictors of the SF-36 PCS were time from injury to follow-up assessment, open versus closed fracture, open versus closed by time from injury to follow-up assessment interaction, and treatment by time from injury to follow-up assessment interaction. For the SF-36 MCS, significant predictors for functional scores were time from injury to follow-up assessment and open versus closed. For SMFA Dysfunction, significant predictors of functional scores were time from injury to follow-up assessment, open versus closed, and treatment by time from injury to follow-up assessment interaction. For the SMFA Bother, significant predictors of function were time from injury to follow-up assessment and open versus closed.³² The main effect of reamed versus unreamed nailing was not a significant predictor in any of the functional subcategories.³²

In the current secondary study, we obtained results varying from Lin et al’s³² study likely due to differing analyses used. The authors implemented a mixed model repeated measures analysis with two weeks, and three, six, and 12 months post-injury used as timepoints, while our analysis was a multiple linear regression analysis with only one timepoint at 12 months post-fracture. Although Lin et al explored a similar topic, we conducted our analysis to include additional, as well as more comprehensive patient, fracture, treatment, and surgical factors that we thought may be of importance when predicting HRQoL and function. We also wanted to focus on only one timepoint post-tibial shaft fracture to investigate the impact of these factors on HRQoL and function at a relatively longer-term follow-up.

Additionally, it is important to note that our results differ from Lin et al³² due to different levels of significance were used in the analyses. Lin et al considered p < 0.05 as statistically significant, whereas we set statistical significance at p < 0.01 in our analyses. If we had used a similar level of significance to Lin et al, an open fracture ((vs closed fracture (reamed nail)) and (versus closed fracture (unreamed nail)) would have been associated with worse SMFA Bother scores and worse SF-36 PCS scores at the one-year follow-up (p < 0.05). An open fracture (vs closed fracture (reamed nail)) would also have been associated with worse SMFA Dysfunction scores at the one-year follow-up (p < 0.05). Moreover, by using a more comprehensive analysis than Lin et al and focusing only on the 12 month timepoint, it may be that open fractures are less important than other factors in predicting HRQoL and function at 12 months post-fracture.

In a publication by a Busse et al,⁸ the authors focused on comparing the SMFA Dysfunction Index and the SF-36 PCS scores among patients in the SPRINT trial to assess what was gained by adding the SMFA to the SF-36 during the conduct of the trial. Although they found that the SMFA Dysfunction and SF-36 PCS scores were highly correlated, we included the SMFA Dysfunction scores in our analysis as a means to strengthen our conclusions.

Our study includes the largest sample size of patients with tibial shaft fractures, recruited from 29 trauma centres from three nations, thus boosting the generalizability of the results. The use of a standardized protocol for perioperative care, and central adjudication of all events, ensure uniformity. Another benefit of our study is that multivariate analysis was used to minimize the effects of confounding.

The drawbacks of the present study are typical of initial attempts to develop a predictive model.^33,34 First, regression models exploit the play of chance; therefore, analysis of new data using such models commonly fails to confirm initial results. Second, other potential predictor variables were not collected. Consequently, the results of the present analysis may be limited to the specific variables collected and may not be generalizable to other patients. Additionally, we were unable to collect data beyond the one-year follow-up period. Therefore, for participants who underwent a reoperation or experienced a nonoperatively-treated infection within the study follow-up period, we were unable to assess their functional and HRQoL outcomes one year post-reoperation/post-complication. We do acknowledge that patients with ununited fractures are unlikely to return to their pre-injury level of function. However, it is still informative to know which factors are associated with HRQoL at one year post-surgery and the relative impact of those factors.

In conclusion, we identified several baseline patient and surgical factors, as well as post-intervention procedures within one year after primary surgery that may influence a patient’s function and HRQoL. These findings may aid in guiding care by providing those patients with a tibial shaft fracture undergoing intramedullary nailing with more information about their injury and the anticipated functional and HRQoL outcomes at one-year post-injury. Given that many factors are not modifiable, our findings are very important for setting expectations following injury. Additionally, it may also be important for future investigations to focus on other psychosocial or socioeconomic factors that may be related to low functional and HRQoL scores. To the authors’ knowledge, this is the most comprehensive large-scale, multicentre, multinational, randomized controlled trial with a longer-term follow-up which uses multivariate analysis to investigate HRQoL and functional outcomes for tibial shaft fracture repair using intramedullary nailing.

Take home message

- The ability to predict health-related quality of life (HRQoL) after tibial fracture treatment may aid in optimizing patient care since this injury is associated with considerable complications following surgery that affect function and HRQoL.