Pre-injury activity predicts outcomes following distal radius fractures in patients age 60 and older.

INTRODUCTION: One out of every 5 elderly patients will suffer a distal radius fracture and these injuries are often related to poor bone health. Several surgical subspecialties have demonstrated that pre-injury activity level can impact patient outcomes. To determine the importance of physical activity, we examined the relationship between pre-injury activity and patient-reported and functional outcomes among fracture patients.
METHODS: This is a retrospective analysis of prospectively collected data from participants enrolled in the Wrist and Radius Injury Surgical Trial (WRIST) from April 10, 2012 to December 31, 2016. This study included 304 adults, 60 years or older with isolated unstable distal radius fractures; 187 were randomized to one of three surgical treatments and 117 opted for casting. Participants opting for surgery were randomized to receive volar locking plate, percutaneous pinning, or external fixation. Participants who chose not to have surgery were treated with casting. All participants were stratified prior to analysis into highly and less-active groups based on pre-injury Rapid Assessment of Physical Activity Scores.
RESULTS: 280 patients had 12-month assessments of outcomes. Highly active participants scored 8 and 5 points greater on the Michigan Hand Questionnaire at 6 weeks and 3 months respectively, p<0.05. Highly active participants demonstrated greater grip strength at the 3-month (p = 0.017) and 6-month (p = 0.007) time-points. Highly active participants treated with volar locking plate scored 10+ points greater on the Michigan Hand Questionnaire compared to the less-active group at the 6-week (p = 0.032), 3-month (p = 0.009) and 12-month (0.004) time points, with an effect size larger than 0.50, suggesting pre-injury level of activity had a significant clinical impact.
CONCLUSIONS: Higher levels of pre-injury activity are predictive of patient-reported and functional outcomes following distal radius fracture. Because of the greater PROs, the early mobility and lower risk of hardware infection reported in the literature, volar plating is preferable to other treatments for highly active patients who request and meet indications for surgery. TRIAL REGISTRATION: clinicaltrials.gov identifier: NCT01589692.

RCT Entities:   Population Interventions Outcomes

Introduction

Distal radius fractures (DRF) are among the most commonly encountered fractures and affect approximately 18% of older adults. [1-7] Elderly women are at greatest risk of fragility fractures with the decrease in estrogen levels and higher rate of osteoporosis. [7-9] Treatment after DRF includes consideration of a patient’s lifestyle, co-morbidities, fracture stability, surgeon training and procedural expertise, and hospital setting and resources. [10] Much of the DRF literature focuses on fracture pattern, age and invasiveness of surgery to determine who should receive which treatment. Casting is reserved for low-demand, less-active patients or those patients who do not wish to undergo surgery. Surgical reduction and fixation, typically with a volar locking plate system (VLPS) is utilized in high-demand, active patients. [1,3-5]

Wrist fractures in older individuals with osteoporosis have multiple deleterious effects including increased mortality, reduced mobility, decline in physical function, and higher healthcare costs. [9-12] Aerobic and weight-bearing exercise are the most widely accepted, cost-effective means of improving bone health in older patients and are essential to fracture prevention and recovery. [8,13-14] Because sustained physical activity increases bone mineral density and attenuates bone loss, the National Osteoporosis Foundation recommends that women participate in weight-bearing exercise to prevent osteoporosis and fragility fractures. [8-11] Several studies have demonstrated a direct relationship between pre-injury level of physical activity and improved postoperative outcomes in cardiac, breast, hernia, gastrointestinal and orthopedic surgery. [15-22] Medicare recognizes the importance of exercise in preventing and treating several chronic conditions including diabetes and peripheral vascular disease. [23-24] Furthermore, Medicare Part C offers specific exercise benefits including “SilverSneakers” and “Silver and Fit” which partners with thousands of fitness centers across the country to offer supervised exercise, strength and training programs for older individuals. [25]

Related to advances in medicine and the success of programs like SilverSneakers, surgeons are encountering older patients who are increasingly active and independent. For indicated fracture types, this growing group of active patients may wish to undergo surgical treatment despite their age because this could minimize the period of immobilization and lead to earlier return to activity. This study examines patient-reported and functional outcomes in highly and less-active older participants following DRF. We assessed the relationship between pre-injury level of physical activity and post-DRF treatment outcomes after casting, VLPS, closed reduction and percutaneous pinning (CRPP), and external fixator placement. We hypothesized that highly active participants will have better patient-reported and functional outcomes.

Methods

Study cohort

We performed a retrospective analysis of prospectively collected data from the Wrist and Radius Injury Surgical Trial (WRIST). Participants were DRF patients enrolled at 24 sites in the US, Canada, and Singapore. Inclusion criteria included age 60 years or older with an unstable fracture where surgery was the recommended treatment (dorsal angulation >10°, radial inclination <15°, or radial shortening >3mm). Surgical participants were randomized to receive internal fixation with VLPS, closed reduction and external fixation, or CRPP. Participants who did not want surgery were treated with casting and followed as an observation group. Exclusion criteria included nursing home residents or residents of other institutional settings, dementia, open or bilateral fractures, previous DRF to same wrist, and comorbid conditions prohibiting surgery.

Because previous studies in the literature have demonstrated similar functional outcomes following surgical and non-surgical treatment of DRF, we stratified participants based on the Rapid Assessment of Physical Activity (RAPA) at the time of enrollment. RAPA is a 9-item questionnaire developed for use among patients > 50 years old, based on recommendations from the Centers for Disease Control and Prevention regarding the appropriate amount of exercise necessary to decrease falls in this group. Responses are scored and patients are categorized as 1 = sedentary, 2 = underactive and 3 = active. Using this validated questionnaire, we derived two groups for our study: patients who scored 1 or 2 were categorized as “less-active” and those that scored 3 were categorized as “highly active.” [13,26]

Participant assessments took place at 2 weeks, 6 weeks, 3, 6, and 12 months following final fracture reduction or surgery. Patient-reported outcomes included the Short-Form 36 (SF-36) and MHQ summary scores. SF-36 and MHQ were chosen as they are validated assessments of overall health and hand-specific disability respectively. [2,27,28] Functional outcomes included assessment of grip strength, wrist and forearm arc of motion at 6 weeks, 3, 6, and 12 months among the two groups. MHQ assessments were performed at the 6-week, 3-, 6- and 12-month time-points, whereas SF-36 was performed at the time of enrollment, 3-, 6-, and 12-months. The WRIST protocol was approved by institutional review boards at all sites. Written informed consent was obtained from all WRIST participants. A Data Safety and Monitoring Board appointed by the National Institute of Arthritis and Musculoskeletal and Skin Diseases oversaw the study.

Statistical methods

The primary outcome was the MHQ summary score between highly- and less-active participants. Secondary outcomes included SF-36 score, grip strength, wrist and forearm arc of motion. To determine the appropriateness of comparing casted and surgical patients, we performed a statistical analysis of the demographic characteristics of the respective groups. Descriptive statistics were computed for the entire study cohort and for each activity level group separately, including mean and standard deviation for continuous variables, and frequency and percentage for categorical variables. Unadjusted between-group comparisons were conducted using two-sample t-tests or Fisher’s exact tests to evaluate the group mean difference of each demographic variable. Mean outcome scores over time stratified by treatment were plotted for highly and less-active participants to visually examine recovery trends in each treatment group and physical activity combination.

Two sample t-tests and multivariate linear models adjusting for demographic variables were performed to provide adjusted comparisons between activity groups on the outcomes of interest at each time-point. To confirm the difference at each time-point was clinically significant, we calculated an effect size that was derived using the estimated adjusted mean difference of each patient-reported or functional outcome measure between highly and less-active participants and standard deviation of the outcome measure among the entire group. [27] Effect sizes are classified as small (0.20), medium (0.50), large (0.80) and very large (1.20). [29-31] Because each participant had longitudinal data collected, we examined the association between activity level and MHQ summary score, grip strength, wrist and forearm arc of motion among participants who underwent casting, VLPS, CRPP, and external fixation treatments separately using Generalized Estimating Equations (GEE) with unstructured correlation structure to account for correlated repeated outcomes that are not normally distributed. GEE down-weighs redundant information among highly correlated outcomes from one individual so that they have a cluster effect toward the association between activity level and health outcomes. Time is coded as a categorical variable with reference cell coding (reference group: 6 weeks). The GEE model for each health outcome is specified as: where i indicates the patient and j indicates time points including 6 weeks, 3 months, 6 months and 12 months. We calculated the adjusted mean differences in patient health care outcomes and corresponding effect sizes at different time points between the highly and less-active participants based on surgical treatment. The Wald test was utilized to derive the p-values for group differences at each time point.

Results

A total of 280 participants had at least one observation for outcomes of interest during the 12-month study period. Two participants had missing RAPA scores and were excluded from the analysis. Comparison between the randomized surgical groups and non-randomized casting group revealed age (68 vs. 76 years, p<0.001) and race (p = 0.008) as the only significant demographic differences. (Table 1). There were no significant differences in sex, level of education, co-morbidities, smoking, employment status, or income (Table 1). Because there were minor demographic differences between the casted and non-casted group, we felt it was appropriate to compare all participants based on pre-injury activity level.

Table 1

Comparison of demographic characteristics among the surgical group (VLPS, ExFix, Pinning) and the casting group.

	Surgical Group (n = 180)	Casting Group (n = 100)	P-value
Average Age at Enrollment (mean (SD)	68.48 (7.29)	75.68 (9.81)	<0.001
Sex Count (%)
Male (1)	22 (12.2)	14 (14.0)
Female (2)	158 (87.8)	86 (86.0)	0.811
Race count (%)			0.008
American Indian/Alaskan Native	1 (0.6)	0 (0.0)
Asian	6 (3.3)	15 (15.0)
Pacific Islander/ Hawaii Native	0 (0.0)	1 (1.0)
Black	11 (6.1)	5 (5.0)
White	159 (88.3)	77 (77.0)
2+ or other	1 (0.6)	2 (2.0)
Missing (NA)	2 (1.1)	0 (0.0)
Highest Level of Education count (%)			0.228
<HS graduate	19 (10.6)	19 (19.0)
HS diploma/GED	39 (21.7)	24 (24.0)
Vocational/Technical School	13 (7.2)	2 (2.0)
Some college/Associate	44 (24.4)	25 (25.0)
College Graduate	27 (15.0)	13 (13.0)
Professional	33 (18.3)	16 (16.0)
Missing (NA)	5 (2.8)	1 (1.0)
Comorbidities count (%)
Hypertension			0.171
No	89 (49.4)	39 (39.0)
Yes	90 (50.0)	61 (61.0)
Missing (NA)	1 (0.6)	0 (0.0)
Diabetes			0.749
No	155 (86.1)	86 (86.0)
Yes	24 (13.3)	14 (14.0)
Missing (NA)	1 (0.6)	0 (0.0)
COPD			0.647
No	163 (90.6)	89 (89.0)
Yes	16 (8.9)	11 (11.0)
Missing (NA)	1 (0.6)	0 (0.0)
Smoking count (%)			0.546
Never	95 (52.8)	52 (52.0)
Current smoker	18 (10.0)	8 (8.0)
Former smoker <10 years	9 (5.0)	2 (2.0)
Former smoker >10 years	57 (31.7)	38 (38.0)
Missing (NA)	1 (0.6)	0 (0.0)
Employment Status count (%)			0.270
Full-time	36 (20.0)	9 (9.0)
Part-time	22 (12.2)	12 (12.0)
Retired	109 (60.6)	72 (72.0)
Disability	5 (2.8)	2 (2.0)
Full-time student	0 (0.0)	0 (0.0)
Part-time student	0 (0.0)	0 (0.0)
Unemployed	6 (3.3)	4 (4.0)
Missing (NA)	2 (1.1)	1 (1.0)
Income count (%)			0.114
<$10K	9 (5.0)	9 (9.0)
$10K-$59999	94 (52.2)	61 (61.0)
>$60K	58 (32.2)	20 (20.0)
Missing (NA)	19 (10.6)	10 (10.0)

After stratification of patients based on RAPA score, 110 participants were classified as highly active and 170 were classified as less active (Table 2). A greater proportion of participants in the less-active group (42%) received casting compared with the highly active group (26%), p<0.05 (Table 2). On average, highly active participants were younger than less active participants, (68 vs. 73 years, p<0.001). 67% of highly active participants had some college or professional education (p = 0.03) and 40% of them earned $60,000 or more (p<0.01). Less active participants had a higher rate of hypertension (p = 0.03) and chronic obstructive pulmonary disease (p = 0.03). Both activity level groups were similar in terms of race, diabetes, smoking and employment status.

Table 2

Demographic characteristics of highly and less-active patients.

	Overall (n = 280)	Less Active (n = 170, 61%)	Highly Active (n = 110, 39%)	P-value
Treatment count (% of all patients in group)				0.072
VLPS	63 (22.5)	34 (20.0)	29 (26.4)	0.272
Ex-Fix	62 (22.1)	35 (20.6)	27 (24.5)	0.528
Pinning	55 (19.6)	30 (17.6)	25 (22.7)	0.373
Casting	100 (35.7)	71 (41.8)	29 (26.4)	0.012
Average Age at Enrollment mean (SD)	71.05 (8.95)	72.9 (9.08)	68.2 (8.01)	<0.001
Sex count (%)				0.220
Male (1)	36 (12.9)	18 (10.6)	18 (16.4)
Female (2)	244 (87.1)	152 (89.4)	92 (83.6)
Race count (%)				0.138
American Indian/Alaskan Native	1 (0.4)	0 (0.0)	1 (0.9)
Asian	21 (7.5)	17 (10.0)	4 (3.6)
Pacific Islander/ Hawaii Native	1 (0.4)	1 (0.6)	0 (0.0)
Black	16 (5.7)	9 (5.3)	7 (6.4)
White	236 (84.3)	138 (81.2)	98 (89.1)
2+ or other	3 (1.1)	3 (1.8)	0 (0.0)
Missing (NA)	2 (0.7)	2 (1.2)	0 (0.0)
Highest Level of Education count (%)				0.027
<HS graduate	38 (13.6)	30 (17.6)	8 (7.3)
HS diploma/GED	63 (22.5)	43 (25.3)	20 (18.2)
Vocational/Technical School	15 (5.4)	9 (5.3)	6 (5.5)
Some college/Associate	69 (24.6)	39 (22.9)	30 (27.3)
College Graduate	40 (14.3)	23 (13.5)	17 (15.5)
Professional	49 (17.5)	22 (12.9)	27 (24.5)
Missing (NA)	6 (2.1)	4 (2.4)	2 (1.8)
Comorbidities count (%)
Hypertension				0.026
No	128 (45.7)	68 (40.0)	60 (54.5)
Yes	151 (53.9)	101 (59.4)	50 (45.5)
Missing (NA)	1 (0.4)	1 (0.6)	0 (0.0)
Diabetes				0.214
No	241 (86.1)	142 (83.5)	99 (90.0)
Yes	38 (13.6)	27 (15.9)	11 (10.0)
Missing (NA)	1 (0.4)	1 (0.6)	0 (0.0)
COPD				0.033
No	252 (90.0)	147 (86.5)	105 (95.5)
Yes	27 (9.6)	22 (12.9)	5 (4.5)
Missing (NA)	1 (0.4)	1 (0.6)	0 (0.0)
Smoking count (%)				0.701
Never	147 (52.5)	85 (50.0)	62 (56.4)
Current smoker	26 (9.3)	18 (10.6)	8 (7.3)
Former smoker <10 years	11 (3.9)	7 (4.1)	4 (3.6)
Former smoker >10 years	95 (33.9)	59 (34.7)	36 (32.7)
Missing (NA)	1 (0.4)	1 (0.6)	0 (0.0)
Employment Status count (%)				0.094
Full-time	45 (16.1)	20 (11.8)	25 (22.7)
Part-time	34 (12.1)	20 (11.8)	14 (12.7)
Retired	181 (64.6)	120 (70.6)	61 (55.5)
Disability	7 (2.5)	4 (2.4)	3 (2.7)
Full-time student	0 (0.0)	0 (0.0)	0 (0.0)
Part-time student	0 (0.0)	0 (0.0)	0 (0.0)
Unemployed	10 (3.6)	5 (2.9)	5 (4.5)
Missing (NA)	3 (1.1)	1 (0.6)	2 (1.8)
Income				0.001
<$10K	18 (6.4)	14 (8.2)	4 (3.6)
$10K-$59999	155 (55.4)	103 (60.6)	52 (47.3)
>$60K	78 (27.9)	34 (20.0)	44 (40.0)
Missing (NA)	29 (10.4)	19 (11.2)	10 (9.1)

Highly active participants demonstrated (p<0.05) greater MHQ summary scores at all time-points. This trend remained significant at the 6-week and 3-month time points with highly active patients scoring on average 8 (p<0.01) and 5 (p<0.05) points greater at the respective time points, after controlling for demographic variables including surgery treatment type, age at enrollment, sex, race, highest level of education, co-morbidities, smoking, employment status, and income (Table 3). The effect size of differences between the two groups was 0.40 and 0.30 at the 6-week and 3-month time-points suggesting these differences represents a small effect.

Table 3

Patient-reported and functional outcome comparisons between highly and less-active participants.

Health Outcomes	Highly Active (n = 112,38.1%) Mean (SD)	Less Active (n = 182,61.9%) Mean (SD)	Adjusted Difference (P-value)	Adjusted Difference Effect Size	Adjusted Change from 6 Week (P-value)
MHQ summary score
6 weeks	51 (20.68)	42 (18.30)	7.80 (0.003)	0.40
3 months	71 (19.29)	65 (19.66)	5.20 (0.051)	0.26	-2.19 (0.379)
6 months	79 (19.58)	75 (18.68)	1.19 (0.650)	0.06	-7.94 (0.005)
12 months	86 (16.40)	80 (18.13)	2.75 (0.324)	0.16	-5.81 (0.082)
SF-36 Physical
Baseline	37 (9.92)	33 (10.13)	2.93 (0.019)	0.28
3 months	48 (8.36)	42 (9.69)	5.50 (<0.001)	0.57	2.86 (0.047)
6 months	50 (8.81)	43 (11.07)	5.68 (<0.001)	0.52	2.79 (0.079)
12 months	50 (9.57)	43 (11.38)	5.31 (<0.001)	0.47	3.48 (0.032)
SF-36 Mental
Baseline	51 (13.15)	49 (14.09)	1.05 (0.561)	0.08
3 months	55 (9.25)	54 (11.01)	0.05 (0.975)	0.01	-1.16 (0.524)
6 months	54 (9.21)	55 (9.45)	-1.37 (0.328)	-0.15	-3.29 (0.100)
12 months	55 (8.40)	54 (10.43)	0.52 (0.733)	0.05	-0.50 (0.814)
Wrist Arc of Motion (degrees)
6 weeks	56 (27.89)	60 (29.36)	-5.26 (0.241)	-0.18
3 months	90 (24.31)	88 (27.11)	0.20 (0.959)	0.01	2.68 (0.594)
6 months	108 (22.82)	102 (25.47)	4.23 (0.284)	0.17	2.51 (0.674)
12 months	115 (20.41)	106 (26.53)	6.35 (0.111)	0.26	9.74 (0.148)
Forearm Arc of Motion
6 weeks	129 (36.88)	125 (44.24)	2.73 (0.656)	0.07
3 months	152 (23.25)	152 (27.11)	0.65 (0.861)	0.03	-3.85 (0.501)
6 months	161 (18.23)	160 (25.40)	0.80 (0.830)	0.04	-3.82 (0.622)
12 months	166 (20.41)	167 (18.28)	-1.81 (0.544)	-0.10	10.95 (0.148)
Grip strength
6 weeks	6 (5.12)	4 (4.60)	0.79 (0.289)	0.16
3 months	11 (6.93)	8 (5.31)	2.00 (0.017)	0.32	0.74 (0.302)
6 months	16 (7.40)	11 (6.22)	2.67 (0.007)	0.38	0.54 (0.602)
12 months	18 (7.47)	15 (7.02)	1.46 (0.163)	0.20	0.08 (0.949)

Controlled demographics: treatment, age at enrollment, sex, race, highest level of education, co-morbidities (hypertension, diabetes, chronic obstructive pulmonary disease), smoking, employment status, and income. Effect sizes: small (0.20–0.50), medium (0.51–0.80), large (> 0.80).

Highly active patients reported greater mean SF-36 physical scores at all examined time-points, p<0.01. After controlling for all other demographic variables, highly active participants on average scored 4, 6, 7, and 7 points greater on the SF-36 physical domain compared to the less active participants at enrollment and 3, 6, and 12 months respectively, p<0.001 (Table 3). A similar trend was noted in effect size; at baseline, 3-,6-, and 12-month time-points where the effect size was 0.30, 0.60, 0.50 and 0.50 at each time point respectively, suggesting these discernible differences have medium clinical significance and implications.

Highly active participants demonstrated significantly greater grip strength at the 3-month (p = 0.017) and 6-month (p = 0.007) time points when compared to less-active participants. The effect size of these differences was 0.30 and 0.40 at 3 months and 6 months respectively, demonstrating that the observed differences are of small clinical magnitude. Examination of wrist and forearm arc of motion revealed no significant functional outcome difference between the two activity groups.

The overall trend in recovery stratified by treatment group demonstrates that the rate of recovery is similar for both less and highly active groups; there were no significant differences in the recovery trend among VLPS highly and less active patients in wrist and forearm arc of rotation, or grip strength. (Fig 1). Whereas the absolute mean of the MHQ summary scores for highly active participants were greater at all time-points, the rate of MHQ score increase over time was similar among the highly and less active groups that underwent CRPP. Although the change is similar, greater patient-reported outcomes earlier in the recovery process among highly active patients over age 60, especially those who undergo VLPS is an important consideration during consultation with these patients to help them make a decision for or against surgery.

Fig 1

Table 4 compares patient-reported and functional outcomes between the highly and less-active participants in each treatment group over time. Highly active participants who underwent VLPS demonstrated a 10 to 14-point improvement on the MHQ questionnaire over less-active patients with medium effect size at 6 weeks (p = 0.032) and 3 (p = 0.009), and 12 months (p = 0.004) respectively. Highly active participants in the CRPP group scored 24, 13, 9, and 12 points greater on the MHQ assessment at 6 weeks and 3, 6, and 12 months respectively, p<0.001 (Table 4). With the exception of the 6-month time point, the effect size of these differences in MHQ scores between the groups were medium to large. Additionally, highly active participants who underwent CRPP demonstrated a 9 to 11 points greater SF-36 physical questionnaire score at all time points (p < 0.01) with large effect size (Table 4). Among participants treated with casting there were no significant differences in MHQ scores between the groups; however, highly active participants demonstrated a greater grip strength at all time points with small to medium effect sizes (Table 4).

Table 4

Generalized estimating equation model results comparing highly and less-active participants based on treatment.

The estimated mean differences and p-values are for β1 (6 weeks), β1+β2 (3 months), β1+β3 (6 months) and β1+β4 (12 months), respectively.

	Treatment Groups
	VLPS		Pinning		ExFix		Casting
Health Outcomes	Estimated Mean Difference (P-value)	Effect Size	Estimated Mean Difference (P-value)	Effect Size	Estimated Mean Difference (P-value)	Effect Size	Estimated Mean Difference (P-value)	EffectSize
MHQ Summary Score
6 weeks	9.70 (0.032)	0.52	24.27 (<0.001)	1.13	10.14 (0.033)	0.49	-1.22 (0.770)	-0.07
3 months	13.40 (0.009)	0.67	12.95 (<0.001)	0.66	7.52 (0.194)	0.57	-1.24 (0.117)	-0.08
6 months	9.83 (0.079)	0.49	9.27 (<0.001)	0.46	2.77 (0.132)	0.48	-3.27 (0.541)	-0.20
12 months	13.73 (0.004)	0.75	12.19 (<0.001)	0.78	4.88 (0.199)	0.79	-5.29 (0.992)	-0.28
Wrist Arc of Motion
6 weeks	-6.11 (0.449)	-0.24	-1.58 (0.856)	-0.06	12.68 (0.250)	0.40	-7.39 (0.269)	-0.26
3 months	5.56 (0.565)	0.23	-0.33 (0.033)	-0.02	6.90 (0.805)	0.26	-3.19 (0.916)	-0.12
6 months	7.20 (0.613)	0.30	-5.22 (0.566)	-0.25	18.27 (0.118)	0.65	-1.13 (0.915)	-0.05
12 months	5.65 (0.802)	0.26	2.20 (0.132)	0.10	22.03 (0.009)	0.97	3.97 (0.752)	0.13
Forearm Arc of Motion
6 weeks	-3.07 (0.747)	-0.08	12.80 (0.344)	0.29	35.11(0.009)	0.66	-11.02 (0.151)	-0.31
3 months	0.95 (0.167)	0.05	-1.75 (0.895)	-0.08	0.16 (0.049)	0.01	0.58 (0.344)	0.02
6 months	8.15 (0.752)	0.29	4.02 (0.845)	0.20	-3.46 (0.039)	-0.23	2.01 (0.456)	0.09
12 months	1.40 (0.185)	0.09	10.38 (0.182)	0.74	-5.58 (0.029)	-0.34	-8.08 (0.535)	-0.35
SF-36 Physical
6 weeks	5.86 (0.011)	0.62	9.54 (0.003)	0.88	-2.85 (0.268)	-0.28	3.41 (0.045)	0.33
3 months	5.48 (0.056)	0.54	9.11 (<0.001)	0.89	3.12 (0.314)	0.38	7.32 (0.001)	0.73
6 months	7.98 (0.006)	0.75	11.43 (<0.001)	1.02	3.50 (0.273)	0.31	6.71 (0.002)	0.62
12 months	9.35 (<0.001)	0.82	10.66 (<0.001)	0.85	2.32 (0.532)	0.21	7.41 (0.001)	0.71
Grip Strength
6 weeks	-2.42 (0.154)	-0.41	5.25 (<0.001)	1.14	1.47 (0.367)	0.35	-1.19 (0.277)	-0.30
3 month	-0.20 (0.383)	-0.03	4.60 (0.860)	0.73	2.64 (0.854)	0.44	1.08 (0.134)	0.24
6 month	0.30 (0.340)	0.04	4.78 (0.094)	0.91	3.29 (0.374)	0.55	3.93 (0.750)	0.57
12 month	0.01 (0.875)	0.00	2.84 (0.939)	0.42	1.74 (0.407)	0.28	4.87 (0.214)	0.81

Controlled demographics: age at enrollment, sex, race, highest level of education, co-morbidities (hypertension, diabetes, chronic obstructive pulmonary disease), smoking, employment status, and income.

Effect sizes: small (0.20–0.50), medium (0.51–0.80), large (> 0.80).

Discussion

By 2030, the US Census projects that persons over 65 years of age will outnumber children for the first time in US history. [32] DRFs are the second most common fracture in the elderly and an estimated 18% of the growing older population stand to suffer this fracture. [9,12] Exercise increases bone mineral density and functional adaptation in response to loading. [8] Wrist fractures are often the gateway to subsequent fragility fractures including hip and vertebral fractures and much attention has been given to the prevention and treatment of these fractures. [12] Most of the previous DRF literature examines the impact of age, treatment, and therapy on outcomes. [1–7, 27] Ikpeze et al, reported that women who suffered a DRF experienced a 50% functional decline compared to uninjured women. [9] Hakestad et al, compared postmenopausal women with low bone mineral density who suffered DRFs to uninjured healthy age-matched controls and found DRF patients with low bone mineral density had poor quality of life, decreased dynamic balance and physical capacity compared to controls. [12] Because there is an increasing number of older patients at risk of suffering a DRF, it is prudent that we devote attention to prevention and treatment strategies to facilitate quick and safe return to baseline function and high quality of life.

“Prehabilitation” or “training for surgery” has been widely adopted in other surgical subspecialties. [15-20] Within the DRF literature, little is known about how level of pre-injury activity influences functional outcomes. [1,4-5,9,20,33,27] In addition to age, co-morbidities, occupation, and fracture pattern/geometry, activity level is an important consideration in the DRF treatment algorithm. The current study demonstrates that increased pre-injury activity level has a positive impact on patient-reported and functional outcomes. Highly active participants had greater grip strength at all times points with a medium effect size. Additionally, highly active patients in the VLPS treatment group had greater MHQ summary scores at the 6-week time-point; among CRPP participants, greater MHQ scores were demonstrated at all time-points with a corresponding high effect size. Among VLPS patients, there were no significant functional outcomes between highly and less active patients. Active CRPP participants had significantly greater MHQ summary scores at the 6-week time point. Although highly active participants treated with CRPP had greater patient-reported and functional outcomes, the pin care requirements, infection, and pin migration in the literature may outweigh these benefits. [27] Because of the aforementioned factors, the majority of operative distal radius fractures are treated with volar plating. However, at their last meeting, the American Academy of Orthopedic Surgery was unable to recommend for or against one method of fixation above another. [34] Thus, surgeons and patients must weigh the importance of early active range of motion, need for pin care, risk of hardware infection, as well as patient-reported outcomes in their ultimate decision for fixation of distal radius fractures.

There are some limitations to the current study. RAPA was determined by a self-reported questionnaire and may suffer from patient recall bias; however, the validity of patient-reported physical activity has been well-established and used routinely in research. [13-26,27] Bone mineral density and radiographic appearance of fracture sites were not specifically measured and would be of benefit to substantiate the mentioned benefits of weight bearing, high intensity exercises on healing and bone health. A greater proportion of less-active participants opted for casting and this is a potential confounder of the patient-reported and functional outcome differences; however, comparison of the casted and non-casted groups revealed no significant differences in medical co-morbidities.

Conclusions

With later retirement, increased need for independence and demands for high quality treatment, surgeons must carefully determine which intervention an older DRF patient may warrant. Based on this study, higher levels of pre-injury activity are predictive of better patient-reported and functional outcomes. Because there is an increased risk of falls and fractures with more activity, supervised physical activity among the elderly is recommended. As surgeon proficiency grows with VLPS, we believe this method of fixation should be considered for DRF in highly active patients regardless of age given the improved patient-reported outcomes. Because casting produced comparable patient-reported outcomes among highly and less-active participants, we believe this is a suitable treatment for less active patients. We suggest surgeons continue to specifically incorporate activity level during pre-surgical evaluation and use activity level as a tool to guide patient treatment and predict outcomes.

List of intuitional review boards and ethics committees involved in WRIST.

(DOCX)

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Data file.

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24 Feb 2020

PONE-D-20-03237

Pre-Injury Activity Predicts Outcomes Following Distal Radius Fractures in Patients Age 60 and Older

PLOS ONE

Dear Dr. Hooper,

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Reviewer #2: Yes

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Reviewer #1: The authors (including the WRIST group) presented their prospectively collected data about elderly patients with a distal radius fracture. Enrolled patients were stratified into highly and less-active groups based on an activity score. Next, patients were either randomized to one of three surgical treatment modalities or opted for casting. Highly active patients showed better patient-reported and functional outcomes than less-active patients during a 12-months-study period.

While the study and the manuscript are nicely written, I have some concerns:

Abstract:

Please make clear if the stratification into highly and less-active groups took place before randomization or before analysis.

I disagree with some conclusions and I would focus on your findings.

Methods:

Any other instability criteria?

Results:

I suggest to start this part with a positive sentence.

From the data (especially the figures), I get the impression that highly active patients start high in the scores and end up high. However, the difference (delta) between 6 weeks and 12 months seem independent of the activity level and the treatment modality. All improved about the same %. Please comment on this topic.

Patients after an operation usually get hand herapy. What kind of hand therapy did the enrolled patients receive?

Discussion:

I expect some limitations due to multicentricity and enrollment of American, Canadian, and Singapore patients.

Reviewer #2: The claim of this paper is to examine patient-reported and functional outcomes in highly and less-active older participants following distal radius fracture. Additionally the authors assessed the relationship between pre-injury level of physical activity and postoperative outcomes after casting, volar plating system, percutaneous pinning and external fixator placement. How significant is for the traumatology to know the pre-injury level of physical acitivity if the surgeon choose the percutaneous pinning or the external fixator methods?

In the current literature there are main reasons in operating elder patient with isolated radius fractures. On the one hand they have bad soft tissue conditions on the other hand you have to avoid a long anesthesia periode. The claims of the study are not properly placed in this context.

The date and analyses support the claims but in their conclusion the authors are saying casting is a suitable treatment for less active patients based on comparable patient-reported outcomes. But this decision making has to set in a context related to soft tissue damage or other contraindication for an operative treatment of distal radius fractures.

Abstract

Line 58: Volare plates cannot be used in all elderly patients. The above conclusion applies only to a selective patient population

Introduction

Line 70: Casting is reserved for low-demand, less-acitve patients…. There are also active patients who simply do not want surgery and therefore also qualify for casting treatments.

Methods

Line 99: The instability criteria listed are not complete. If this is wanted or there were no unstable radius fractures with termination of the palmar / dorsal joint lip, termination of the styloid ulnar process near the base, radioulnar dissociation, dorsal tilt of the peripheral fragment > 20 °, palmar tilt of the peripheral fragment > 20 °.

Results

Unfortunately, no tables were included in the manuscript for the reviewer. The table titles could only be read under numbers 358-363.

Discussion

Line 228/229: I think in the discussion a gradation of the criteria regarding the therapy algorithm should be worked out, whereby the preoperative activity level is weighted less than the fracture pattern

Line 242/243: If you are already performing an operative intervention, you should aim at least for an exercise-stable osteosynthesis in order to be able to carry out a functional after-treatment. Otherwise the operational risk of complications is too great.

Line 256/257: Even if the risk of falls in active patients surely increases, supervision cannot be required as a prerequisite for their activities. That would cause costs to rise massively

**********

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Reviewer #1: Yes: Valentin Neuhaus, MD

Reviewer #2: No

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5 Mar 2020

PONE-D-20-03237: Pre-Injury Activity Predicts Outcomes Following Distal Radius Fractures in Patients Age 60 and Older

Journal Requirements:

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

Response: We have revised the style to meet PLOS ONE requirements.

2. Please provide additional details regarding participant consent. In the ethics statement in the Methods and online submission information, please ensure that you have specified (1) whether consent was suitably informed and (2) what type you obtained (for instance, written or verbal). If the need for consent was waived by the ethics committee, please include this information.

Response: We have made this addition.

Lines 195-196: “Written informed consent was obtained from all WRIST participants.”

3. Thank you for your ethics statement: "The WRIST protocol was approved by institutional review boards at all sites." Please amend your current ethics statement to include the full name of the ethics committee/institutional review board(s) that approved your specific study.

Response: Because there are 24 sites in WRIST we have made the list of ethics committees and institutional review board available in a supplemental file.

S2 File. List of Intuitional Review Boards and Ethics Committees involved in WRIST.

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Response: this has been done

6. One of the noted authors is a group or consortium [WRIST Group]. In addition to naming the author group, please list the individual authors and affiliations within this group in the acknowledgments section of your manuscript. Please also indicate clearly a lead author for this group along with a contact email address.

Response: We have moved the list of WRIST contributors to the acknowledgment section.

Reviewer #1:

1. Abstract: Please make clear if the stratification into highly and less-active groups took place before randomization or before analysis.

Response: The stratification took place before the analysis. This has been added, line 97.

2. Methods: Any other instability criteria?

Response: These are the recommendations from the American Academy of Orthopedic Surgeons on the management of distal radius fractures and thus were used for the study.

3. Results: I suggest to start this part with a positive sentence.

Response: This has been changed, lines 236-237.

4. From the data (especially the figures), I get the impression that highly active patients start high in the scores and end up high. However, the difference (delta) between 6 weeks and 12 months seem independent of the activity level and the treatment modality. All improved about the same %. Please comment on this topic.

Response:

We have clarified this point.

Lines 281-285: “Although the change is similar, greater patient-reported outcomes earlier in the recovery process among highly-active patients over age 60, especially those who undergo VLPS (the most commonly used surgical treatment) is an important consideration during consultation with these patients to help them make a decision for or against surgery.”

5. Patients after an operation usually get hand therapy. What kind of hand therapy did the enrolled patients receive?

Response: We did not standardize hand therapy. Participants received the standard of care therapy regimen at their treating institution.

6. Discussion: I expect some limitations due to multicentricity and enrollment of American, Canadian, and Singapore patients.

Response: 99% of patients were from Canadian and American sites.

Reviewer #2:

1. The claim of this paper is to examine patient-reported and functional outcomes in highly and less-active older participants following distal radius fracture. Additionally the authors assessed the relationship between pre-injury level of physical activity and postoperative outcomes after casting, volar plating system, percutaneous pinning and external fixator placement. How significant is for the traumatology to know the pre-injury level of physical activity if the surgeon choose the percutaneous pinning or the external fixator methods?

Response: Our study demonstrates that traumatologists should be aware that highly-active patients who undergo percutaneous pinning have greater MHQ composite scores (including satisfaction and activities of daily living) compared to less-active patients; however, both percutaneous pinning and external fixation have very specific roles in the management of distal radius fractures (open fractures and significant comminution) related to pin site care, risk of infection, and non-rigid fixation. Regarding fixation and treatment methods, pre-injury level of activity should be used as a guide to help surgeons caring for these older patients. Despite chronological age, highly-active patients who wish to return to their normal activities in the shortest period of time should have the option to undergo surgery, preferably with volar locking plate.

In the current literature there are main reasons in operating elder patient with isolated radius fractures. On the one hand they have bad soft tissue conditions on the other hand you have to avoid a long anesthesia period. The claims of the study are not properly placed in this context.

Response: Although many of the patients likely have osteoporotic bone, all patients had closed distal radius fractures. Despite the swelling and soft tissue injury, wound complications following distal radius fractures are fairly low; Sirnio et al reported an ~0.8% culture-positive wound infection among 881 distal radius fracture patients who underwent volar locking plate [1]. Percutaneous pinning and external fixation pin site infections occurred in about 25% of participants [2].

Regional block is often the anesthesia of choice when fixing distal radius fractures; this obviates the medical risks associated with general anesthesia in this older group. Weighing the risks of wound complications, anesthesia and duration of procedure, treatment of highly-active older patients with distal radius reduction and volar plating is a reasonable option.

2. The date and analyses support the claims but in their conclusion the authors are saying casting is a suitable treatment for less active patients based on comparable patient-reported outcomes. But this decision making has to set in a context related to soft tissue damage or other contraindication for an operative treatment of distal radius fractures.

Response: Although the force required to cause the fracture would also cause significant soft tissue contusion, we did not have any open fractures in this series. The current study includes patients with closed distal radius fractures only; open wounds or substantial soft tissue compromise that necessitated surgery was not encountered. Despite edema, swelling, and soft tissue damage, few patients suffer wound healing complications following ORIF DRF with volar plating.

3. Line 58: Volare plates cannot be used in all elderly patients. The above conclusion applies only to a selective patient population

Response: Agreed. We have clarified this.

Lines 106-108: “This has been changed to, “Because of the greater PROs, the early mobility and lower risk of hardware infection reported in the literature, volar plating is preferable to other treatments for highly-active patients who request and meet indications for surgery.”

4. Line 70: Casting is reserved for low-demand, less-active patients…. There are also active patients who simply do not want surgery and therefore also qualify for casting treatments.

Response: We have edited this.

Lines 121-124: “Casting is reserved for low-demand, less-active patients or those patients who do not wish to undergo surgery. Surgical reduction and fixation, typically with a volar locking plate system (VLPS) is utilized in high-demand, active patients.”

5. Line 99: The instability criteria listed are not complete. If this is wanted or there were no unstable radius fractures with termination of the palmar / dorsal joint lip, termination of the styloid ulnar process near the base, radioulnar dissociation, dorsal tilt of the peripheral fragment > 20 °, palmar tilt of the peripheral fragment > 20 °.

Response: The criteria listed in the manuscript was used for the trial and thus were reported.

6. Unfortunately, no tables were included in the manuscript for the reviewer. The table titles could only be read under numbers 358-363.

Response: Tables are now included in the manuscript.

7. Line 228/229: I think in the discussion a gradation of the criteria regarding the therapy algorithm should be worked out, whereby the preoperative activity level is weighted less than the fracture pattern

Response: We agree the fracture pattern should be the most important factor; however, often times elderly patients who otherwise meet criteria for surgical intervention based on the previously listed criteria are not considered surgical candidates based on chronological age. The purpose of the study is to expand the way we think about suitability for wrist surgery among the elderly.

8. Line 242/243: If you are already performing an operative intervention, you should aim at least for an exercise-stable osteosynthesis in order to be able to carry out a functional after-treatment. Otherwise the operational risk of complications is too great.

Response: Agreed, this is why we recommend volar plating over the other two methods of fixation. Fortunately, volar plating is more commonly used for fixation than some of the other methods.

9. Line 256/257: Even if the risk of falls in active patients surely increases, supervision cannot be required as a prerequisite for their activities. That would cause costs to rise massively

Response: Agreed, complete supervision of all elderly activities would be costly. We advocate continued vigilance in identification and treatment of osteopenia and osteoporosis as falls in the setting of bone mineral deficiency leads to these fragility fractures.

References:

1. Sirnio K, Flinkkila T, Vahakuopus M, Hurskainen A, Ohtonen P, Leppilahti J. Risk Factors for Complications After Volar Plate Fixation of Distal Radius Fractures. J Hand Surgery European Volume. 2019; 44: 456-461.

2. Chung KC, Malay S, Shauver MJ, Kim HM, for the WRIST group. Assessment of distal radius fracture complications among adults 60 years or older: A secondary analysis of the WRIST randomized clinical trial. JAMA Netw Open. 2(1):e187053, 2019.

Submitted filename: response to reviewers.docx

Click here for additional data file.

31 Mar 2020

PONE-D-20-03237R1

Pre-Injury Activity Predicts Outcomes Following Distal Radius Fractures in Patients Age 60 and Older

PLOS ONE

Dear Dr. Hooper,

Thank you for submitting your revised manuscript to PLOS ONE. After careful consideration, we feel that it has improved but does not fully meet the statistical requirements as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the statistical review process.

The comments of the staitistical reviewer are pointed out in detail.

We would appreciate receiving your revised manuscript by may 31, 2020. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

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Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

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Kind regards,

Hans-Peter Simmen, M.D., Professor of Surgery

Academic Editor

PLOS ONE

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Comments to the Author

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Reviewer #3: (No Response)

**********

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Reviewer #3: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: No

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #3: Regarding the statistical methodology used in this manuscript, I have the following concerns:

Once a covariate has been detected as significant, please explain the interest of unadjusted comparisons between groups.

In this manuscript, an effect size measure is mentioned as if there were only one possible index, but there are several choices. To begin with, it must be highlighted that all the effect sizes are standardized ones, in opposition to the raw ones. On the other hand, there are different possibilities for these standardized measures. I am not sure if this manuscript reports Cohen's d or another related effect size. This must be properly stated. On the other hand, Cohen's d has been proved to be a biased standardized effect size and several corrections are available.

Moreover, regarding the effect sizes, I disagree with the idea of these measures are not applicable when a difference is lacking statistical significance. Precisely, the p-values are affected by the sample size while the standardized effect size measures are not. So, standardized effect sizes are a good guideline to assess the statistical power involved in a comparison. On the other hand, there are comparisons (eg table 3) with statistical significance where the effect size is not available.

Linear Mixed Models and GEE are different methodologies. The first one is not mentioned in the section of methodology but it is used to obtain the results in table 4. The election of each methodology must be properly explained.

Regarding table 4, I find weird to give one coefficient estimation of the model for each instant of measure. If the model considers time as a variable, there must be only one coefficient for it (considering the trend is linear), not one coefficient for each time value.

My view is that there is a high level of duplicity between the information given in tables and that which is given in the text.

Finally, decimal figures of p-values must be unified. APA's recommendation is to use three.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

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Reviewer #3: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

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13 Apr 2020

Reviewer #3: Regarding the statistical methodology used in this manuscript, I have the following concerns:

1. Once a covariate has been detected as significant, please explain the interest of unadjusted comparisons between groups.

We appreciate your comment. We intended to use the unadjusted differences to describe the imbalance between the two groups. However, it is not necessary to report the unadjusted p-values.

The modified table 3 has no unadjusted p-values. Formal comparisons are done by the controlled p-values.

2. In this manuscript, an effect size measure is mentioned as if there were only one possible index, but there are several choices. To begin with, it must be highlighted that all the effect sizes are standardized ones, in opposition to the raw ones. On the other hand, there are different possibilities for these standardized measures. I am not sure if this manuscript reports Cohen's d or another related effect size. This must be properly stated. On the other hand, Cohen's d has been proved to be a biased standardized effect size and several corrections are available.

Thank you for pointing this out. The effect size was measured using the standardized mean difference adapted from a paper by Kotsis et. al (https://www-sciencedirect-com.proxy.lib.umich.edu/science/article/pii/S0363502306010859) in a similar clinical setting.

We calculated the standardized mean difference in response using the formula: (mean response in highly active group – mean response in less active group)/SD of the measurement in two groups. It is used to measure the magnitude of difference between the two groups, which is different from Cohen’s d. Initially the Kotsis et. al uses ranges small (0.2-0.4), medium (0.50-0.70) and large (>0.80) as cutoffs. In our scenario, the effect sizes can be negative when less active group have better response. However, the absolute number of effect size specifies the magnitude of the difference clinically and could follow the same ranges. This is present in the manuscript, lines 152-156.

3. Moreover, regarding the effect sizes, I disagree with the idea of these measures are not applicable when a difference is lacking statistical significance. Precisely, the p-values are affected by the sample size while the standardized effect size measures are not. So, standardized effect sizes are a good guideline to assess the statistical power involved in a comparison. On the other hand, there are comparisons (eg table 3) with statistical significance where the effect size is not available.

Thank you so much for your comment. We have added the effect sizes for non-significant parameters and unadjusted comparisons in tables 3 and 4. For table 3, if the estimators are not statistically different from 0, the effect sizes would be small. For table 4, the effect sizes examine the magnitude of the conditional mean difference at a specific time point. We used reference cell coding for time as a categorical variable (please find further explanation in point 5).

4. Linear Mixed Models and GEE are different methodologies. The first one is not mentioned in the section of methodology but it is used to obtain the results in table 4. The election of each methodology must be properly explained.

We apologize. There was a typo in the label for table 4. We corrected the label as the “GEE model results”. The GEE model was preferred compared to the linear mixed model for its flexibility and allowing complicated correlation structures. Moreover, it only needs the 1st moment to be correctly specified rather than the whole likelihood. This has been updated in the manuscript, lines 163-168.

5. Regarding table 4, I find weird to give one coefficient estimation of the model for each instant of measure. If the model considers time as a variable, there must be only one coefficient for it (considering the trend is linear), not one coefficient for each time value.

In the GEE models (table 4), we did not assume time to be linear. We used reference cell coding for time as a categorical variable, since we only have 4 time points in the data.

The model for each patient outcome is specified as:

〖"E(Response" 〗_ij)=β_0+β_1 I("patient i is highly active " )+ β_2 I("patient i is highly active" )×I( 〖"time" 〗_ij="3 months") + β_3 I("patient i is highly active" )×I(〖"time" 〗_ij " = 6 months" )+β_4 I("patient is highly active" )×I(〖"time" 〗_ij " = 12 months" )+〖"demographics" 〗_i

We have updated table 4 to better describe the model. The estimated mean differences are β_1(6 weeks), β_1+β_2 (3 months), β_1+β_3(6 months) and β_1+β_4 (12 months) respectively.

Previously, we have reported p-values for β_1-β_4 in table 4. To better examine the group differences controlling for treatment received, time, within-patient correlation and other covariates, we have updated the p-values in table 4 with Wald test results testing H_a:β_1≠0,H_a: β_1+β_2≠0, H_a: β_1+β_3≠0 and H_a: β_1+β_3≠0 for time specific mean difference in response between highly active and less active groups.

6. My view is that there is a high level of duplicity between the information given in tables and that which is given in the text.

Thank you for your comment. The tables provide all the statistical findings, we wanted to highlight some clinically important statistical findings from the tables in the text. This has been minimized.

7. Finally, decimal figures of p-values must be unified. APA's recommendation is to use three.

Thank you for the suggestion. We have updated the tables 1-4 to unify 3 decimal figures for p-values.

Submitted filename: WRIST LOA Reviewer Comments Part 2.docx

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21 Apr 2020

Pre-Injury Activity Predicts Outcomes Following Distal Radius Fractures in Patients Age 60 and Older

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28 Apr 2020

PONE-D-20-03237R2

Pre-Injury Activity Predicts Outcomes Following Distal Radius Fractures in Patients Age 60 and Older

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