Preoperative predictors for return to physical activity following anterior cruciate ligament reconstruction (ACLR): a systematic review

doi:10.21203/rs.3.rs-2117434/v1

Download PDF

Research Article

Preoperative predictors for return to physical activity following anterior cruciate ligament reconstruction (ACLR): a systematic review

https://doi.org/10.21203/rs.3.rs-2117434/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 09 Jun, 2023

Read the published version in BMC Musculoskeletal Disorders →

You are reading this latest preprint version

Background

Rates of return to physical activity after anterior cruciate ligament reconstruction surgery are sub-optimal. Optimising presurgical treatment may improve return rates. The purpose of this systematic review was to identify modifiable preoperative predictors for return to physical activity after anterior cruciate ligament reconstruction.

methods

Six electronic databases ( CINAHL, AMED, MEDLINE, SPORTDiscus and PsycINFO via EBSCOhost and Web of Science) were searched from inception to 31 December 2021.

The population of focus was adults aged 18–65 who had undergone primary anterior cruciate ligament reconstruction. Studies needed to identify at least one potential modifiable preoperative predictor variable and the relationship between the predictor(s) and return to physical activity. All time-points of assessment and study designs were included.

Data extraction was completed by one reviewer and verified by a second reviewer. Two reviewers completed the risk of bias assessment using the Quality in Prognostic Studies tool and Grading of Recommendations Assessment, Development and Evaluation system.

Results

The search identified 345 studies, eight met the inclusion criteria. Five studies scored 'high’, and three studies scored ‘moderate’ risk-of-bias. All preoperative predictors were of very low-quality evidence.

Five different outcome measures were used to assess return to physical activity including Tegner, Marx, Physical Activity Scale, return to play at the elite level and return to preinjury level (undefined). This was measured between 1 and 10 years post-surgery. Nine preoperative physical, six psychosocial and five demographic/clinical factors were assessed and five factors were found to be predictive. These included anterior knee laxity, quadriceps strength, psychological profile, patient estimated ability to return and graft type (patella tendon).

Conclusion

Very low-quality evidence supports preoperative physical, psychosocial and demographic/clinical factors to be predictive of return to physical activity between one- and ten-years after anterior cruciate ligament surgery.

Trial registration

This study was prospectively registered in PROSPERO: CRD 42020222567.

Anterior Cruciate Ligament

Preoperative predictors

Return to physical activity

Return to sport

Anterior cruciate ligament (ACL) injuries are a common musculoskeletal disorder among the adult population[1] with an estimated 200,000 ACL injuries occurring each year in the USA.[2] Most patients are treated surgically with an ACL reconstruction[3] (anterior cruciate ligament reconstruction, ACLR) following diagnosis. Those who do opt for surgery usually aim to return to their preinjury physical activity levels and expect this to be an achievable outcome.[4–7] However, this outcome is frequently documented to be sub-optimal, with only 24% returning at 1-year[6] 28% at 18 months[8] and less than 45% returning at 2-years.[9, 10] Psychological factors are the most commonly cited reason for failing to return to physical activity after ACLR.[11–13]

Understanding return to physical activity after ACLR remains a challenge. There is limited consensus on an agreed outcome measure to be used and time-frame for this to be assessed.[14] In 2016, a return to sport consensus statement suggested return to be viewed as a continuum progressing from return to participation towards return to sport and finally return to performance.[15] A more recent consensus exercise in 2020 suggested a minimum two-year follow-up that records activity level and return to sport (among other outcomes).[14] However, a range of example tools were suggested for use and so no one universally agreed return to physical activity outcome exists. For the purpose of this review, we will use the umbrella term ‘return to physical activity (RTPA)’ to encapsulate all measures of return to physical activity/sport/preinjury level of activity.

Furthermore, there are a number of physical tests documented in the literature to support patients and clinicians to make decisions regarding the readiness and timing of RTPA,[16, 17] although the relationship between performance in these tests and returning to activity is not always clear.[16] Thus, clinical decision making remains a challenge.

ACLR is followed by an extensive postoperative rehabilitation period that typically lasts a minimum of 9 months and is usually progressed based on objective criteria.[18] What is less clear is how to manage patients in the preoperative period. There is typically a lengthy wait for an ACLR following injury in the UK National Health Service (NHS). This wait has been estimated at 4–12 months;[2] however, in recent years this has increased upwards of 12-months due to COVID-19 and the cancellation of elective procedures.[19, 20] Optimal treatment during this waiting time is currently unknown.[21]

Optimal presurgical treatment and clinical decision making regarding RTPA following ACLR could be facilitated by understanding preoperative variables that are associated with RTPA following surgery. This could aid hypothesis generation for novel treatment pathways to facilitate RTPA, allow clinicians to educate patients on the likely outcome of their surgery, and utilise appropriate outcome measures both pre- and post-operatively to track patients' progress. As far as the authors are aware, no study to date has collated the evidence to identify modifiable preoperative predictors for RTPA after ACLR.

Objective

The aim of this review is to identify the modifiable preoperative predictors for RTPA after ACLR.

Protocol and Registration

This systematic review followed a published protocol[22] and was prospectively registered in PROSPERO (02 Dec 2020, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020222567). The review is reported in line with the 2020 PRISMA checklist (available in supplementary file 1)[23] facilitated by the PERSiST guidance.[24]

Eligibility Criteria

The eligibility criteria were pre-specified by the Population-Exposure-Outcome-Study (PEOS) design and are described below.

Population

The population of focus was adults aged 18 – 65 years old who had undergone a primary ACLR with no concomitant injuries. Studies were included where participants were <18 years but the mean age of the overall population was ≥18. Studies were included where participants had sustained a concomitant injury where results were separated.

Exposure

To be included, studies needed to identify at least one potential modifiable preoperative predictor variable and the relationship between the predictor(s) and RTPA. All estimates considered to determine the relationship between the predictive factor and outcome of interest were included (e.g., odds ratio and p-value). Predictive factors could be physical (e.g., quadriceps strength), psychosocial (e.g., anxiety) or demographic/clinical (e.g., graft type and time to surgery). We defined modifiable predictor variables as any factor that can be assessed and altered prior to surgery.

Outcome

The main outcome of interest was the success of RTPA. The identified preoperative risk factors needed to be linked to the outcome of interest. No time limit post-ACLR was defined for the reported outcome. If a study included multiple post-operative time-points, all were included. All measures of RTPA were included (e.g., participant reported [yes/no] or validated measures [Tegner, Marx scale], this list was, however, not exhaustive).

Study

Prospective, retrospective and cross-sectional study designs published in English with full texts available were included.

Search Strategy

A pre-defined and published search strategy was followed and completed in December 2020[22]. The search strategy included a combination of key words in four categories: (1) ACL, (2) preoperative, (3) risk factor and (4) RTPA. Terms were matched to Medical Subject Headings (MeSH) and combined using Boolean operators (e.g. Preoperative period OR Preop* OR Pre-op* OR Periop*). This search was carried out in six electronic databases in addition to screening the reference lists of included articles. This was updated in December 2021 to ensure no new studies were published during the write-up phase of this review.

Study Selection

Title and abstract screening was completed by one reviewer (HC). Two reviewers (HC and BS) independently screened full text articles for inclusion against the eligibility criteria. Agreement was discussed to reach consensus with discrepancies solved by the third reviewer (GL). Authors were contacted via the corresponding details if further information was required.

Data Extraction

Data extraction was completed by one reviewer (HC) in a form that was piloted prior to the review and described in the published protocol. Extracted data included study design, participant details (number, age, sex), preoperative predictors, outcome measures and time point of outcome assessment post-surgery.[22] The accuracy of data extraction was verified by a second reviewer (BS).

Risk of Bias Assessment

The Quality in Prognostic Studies (QUIPS) tool was used to assess for risk of bias for all included studies by two reviewers (HC and BS) independently. The QUIPS tool comprises of six domains to assess study participation, study attrition, prognostic factor measurement, outcome measurement, study confounding and statistical analysis and reporting.[25–27] A rating of low, moderate or high risk of bias is given for each domain to facilitate an overall risk of bias rating for each study. Disagreements between the reviewers were resolved through discussion.

GRADE

The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system was also used to rate each predictor variable. GRADE has previously been adapted for prognostic research[28] to consider two factors that may increase the quality (moderate or large effect size and exposure-response gradient) and six factors that may decrease the quality (phase of investigation, study limitations, inconsistency, indirectness, imprecision and publication bias). This was therefore considered alongside the original framework.[29,30]

The starting point of assessment for all studies was to determine the phase of investigation as advised by Huguet et al.[28] It was deemed all studies sought to identify associations between potential prognostic factors and the outcome of interest and so all started at a 'moderate' level of evidence. Publication bias was not assessed as funnel plot asymmetry is recommended to only be used when there are ten or more studies included.[31] Two reviewers independently rated each prognostic factor (HC and BS) and discrepancies were resolved through discussion.

Data Synthesis and Analysis

Clinical heterogeneity was assessed through visual examination of the data extraction table on details related to participant characteristics, risk factors, study design and processes in the included studies. Data were deemed to be heterogeneous due to the wide variety in study design, risk factors, reported outcome measures (e.g. Tegner and patient reported yes/no) and time to follow-up (e.g. 1 year, 2 years and 5-10 years) and so a narrative synthesis was completed.

Predictor variables were classified as physical, psychosocial, or demographic/clinical. For each variable, the number of studies it was investigated in and the number of studies showing a relationship to RTPA were determined. Predictor variables were classified as having a predictive, variable, or non-predictive relationship to RTPA based on a synthesis of these findings.

Study Selection

The study selection process is presented in FIGURE 1. The initial database search yielded 345 articles. After duplicates were removed, 197 articles were screened for inclusion. No additional articles were found from the screening of unpublished searches. After title and abstract screening, 27 full-text articles were assessed for eligibility and 23 were excluded due to study design (conference paper), population (included concomitant injuries and mean age < 18), preoperative variables were deemed to be non-modifiable (e.g. age and sex), preoperative variables were not assessed against the outcome of interest and the outcome measure not related to RTPA. A further 18 potential articles were found from reference list screening. Four articles were deemed to meet the inclusion criteria (remaining articles excluded due to only including postoperative predictor variables, preoperative variables were deemed to be non-modifiable, population included concomitant injuries and preoperative variables were not assessed against the outcome of interest). An updated search carried out from December 2020 – December 2021 yielded no new articles for inclusion in the review. The total number of studies included in the review was eight.[32–39]

Characteristics of the included studies

The characteristics of the included studies are summarised in Table 1 and below.

Table 1

, Study characteristics
Author	Year	Design	Participant details (n, mean age, % male)	Preoperative Predictors (Physical, Psychosocial and Demographic/clinical)	Outcome Measures	Time point of outcome assessment
Gobbi and Francisco	2006	Prospective	n = 100 Mean age: 28 % male: 67	PHYSICAL 1. Knee scores – Tegner, Noyes, and Marx 2. Knee specific patient reported outcome measure's – Lysholm and International Knee Documentation Committee (IKDC) There were no significant differences in pre-operatively mean Tegner, Noyes, Lysholm and IKDC between those who return to sport (RTS) and those who didn't RTS. The Marx scale showed a significant difference between athletes who were able to return to sport and those who did not return. It is however not clear from the reporting whether this was from the Marx scores taken pre-operatively or at final follow up. The authors were contacted but the corresponding email address provided on the article was no longer in use. This was therefore not included in the final analysis. PSYCHOSOCIAL 1. Psychovitality questionnaire* 28.6% of the athletes that ‘‘did not return to sport’’ scored ≤ 15 points preoperatively. Whereas, 67% of the athletes that ‘‘returned to sport’’, scored ≥ 15 points. Statistical analysis using the Mann–Whitney U-test revealed a significant difference (P < 0.001) between these two groups (Fig. 5a, b). DEMOGRAPHIC/CLINICAL n/a	Marx	Minimum of 24 months
Heijne, Äng and Werner	2009	Prospective	n = 64 Mean age: 30.1 % male: 45.3	PHYSICAL 1. Passive knee range of motion (ROM) 2. Anterior knee laxity* 3. Rotational knee laxity (pivot shift) 4. Thigh muscle torque (Concentric quadriceps* and hamstrings, Eccentric quadriceps and hamstrings) 5. Knee function (2 questions from IKDC) 6. Anterior knee pain PSYCHOSOCIAL n/a DEMOGRAPHIC/CLINICAL 1. Weight and BMI 2. Graft type* 3. Time to surgery* Four pre-operative variables were correlated with the Tegner activity scale: 1. Concentric quadriceps torque (P = 0.004) 2. Graft type – patella tendon (P = 0.006) 3. Time between injury and reconstruction surgery (P = 0.02) 4. Anterior knee laxity (P = 0.1) (Table 3). These four variables explained 21% (P = 0.006) of the outcome variance. The use of a patellar tendon graft in favour of a hamstring graft was shown to be the strongest predictor in the forward step-wise regression analysis, but explained only 8% of the outcome variance (Table 4).	Tegner	12 months (range 12–16)
Hetsroni et al.,	2017	Retrospective	n = 55 Mean age: 25.3 % male: 100	PHYSICAL 1. Physical activity rating scales - Tegner* and Marx Standard correlation coefficient for Tegner preinjury score as the independent variable and Tegner at follow-up as the dependent variable 𝜷^b 0.423 (0.437), p = 0.01 (< .01). Standard correlation coefficient for Tegner preinjury score as the independent variable and Marx at follow-up as the dependent variable 𝜷^b 0.405 (0.457), p = 0.02 (< .01). There was no correlation between the Marx pre-injury scores and follow-up Marx and Tegner scores. Standard correlation coefficient for the Marx pre-injury score as independent variable and Marx follow-up as the dependent variable 𝜷^b -0.088, p = 0.6 and for Tegner follow-up as the dependent variable 𝜷^b -0.164, p = 0.29. PSYCHOSCOCIAL n/a DEMOGRAPHIC/CLINICAL 1. Time to surgery 2. Smoking status There was no association between time to surgery and smoking status with the outcome measure.	Tegner Marx	5–10 years (mean 7.1 years)
Jurkonis, Gudas and Smailys	2018	Prospective	n = 214 Mean age: 33.2 % male: 74.3	PHYSICAL 1. Physical activity rating scale - Tegner* A positive correlation was found between pre-injury Tegner activity score and Tegner activity score 12 months after surgery (r = 0.728, p < 0.001) PSYCHOSCOCIAL n/a DEMOGRAPHIC/CLINICAL 1. BMI* A multiple regression analysis indicated that a model including age, sex, BMI and pre-injury Tegner was a significant predictor of Tegner 12-months after ACLR, BMI (b₂= -0.042, p = 0.008). Table 3 shows Tegner activity score pre-injury and at 12 months after ACLR in BMI groups, with statistically significant differences between Tegner activity scores in BMI groups.	Tegner	12 months
Liptak and Angel	2017	Retrospective	n = 115 Mean age: 24 % male: 100	PHYSICAL n/a PSYCHOSCOCIAL n/a DEMOGRAPHIC/CLINICAL 1. Weight* Player weight was identified as significantly associated with returning to play at the elite level. Heavier players displayed a tendency to be more likely to return to play at the elite level when compared with lighter players (70–79 kg). Players weighing between 90 and 99 kg were nearly 15 times more likely to return to play at the elite level (OR, 14.93; 95% CI, 2.13-104.76; P = .007).	Return to play at the elite level (AFL Medical Officers Association [AFLMOA] data)	No pre-defined time of assessment but documented as < 1 year after injury or 1 year or longer
McGrath et al.,	2016	Prospective	n = 64 Mean age: 26.9 (LARS group) and 28.9 (2ST/2GR group) % male: 68.8	PHYSICAL 1. Physical activity rating scale - Tegner* Preoperative Tegner scores had a moderate correlation with postoperative activity levels at 12 (r_s = 0.347, P = .005) and 24 months (r_s = 0.326, P = .009). PSYCHOSCOCIAL n/a DEMOGRAPHIC/CLINICAL n/a	Tegner	12 and 24 months
Sonesson et al.,	2016	Prospective	n = 65 Median age: 22 % male: 52.3	PHYSICAL n/a PSYCHOSCOCIAL 1. Estimation – Time to achieve postoperative markers and ability to return to preinjury level* There were no differences between participants who had returned to their pre-injury sport activity at 1 year and those who had not returned, regarding preoperative estimated time to: - complete rehab (n.s) - be able to run/jump (n.s) - return to pre-injury sport activity (n.s) However, participants who had returned to their pre-injury sport activity at 1 year, to a greater extent estimated pre-operatively that it was possible to return to their preinjury activity level compared to those who had not returned at 52 weeks (P = 0.019, Table 4). 2. Goals Returning to preinjury sport activity at 1 year was not related to whether participants said their goal was to return preoperatively (n.s). DEMOGRAPHIC/CLINICAL n/a	Return to preinjury level (unspecified)	12 months
Thomeé et al.,	2008	Prospective	n = 38 Mean age: 29.7 % male: 65.8	PHYSICAL 1. Physical activity rating scale - Tegner* Tegner_Pre−injury was a significant predictor (P = 0.002, 𝜷 = 0.28) of Tegner_Present at the 1-year follow-up when adjusted for age, gender, K-SES_Present and K-SES_Future (R² = 0.25). PSYCHOSCOCIAL 1. K-SES present* The pre-operative K-SES_Present correlated significantly (P = 0.03) (r_s = 0.37) with Tegner_Present at the 1-year follow-up. But did not correlate significantly (P = 0.20) (r_s = 0.32) with PAS_Present at the 1-year follow-up. 2. K-SES future The pre-operative K-SES_Future did not correlated significantly (P = 0.56) (r_s = 0.10) with Tegner_Present or PAS_Present P = 0.76) (r_s = 0.01) at the 1-year follow-up DEMOGRAPHIC/CLINICAL n/a	Tegner Physical Activity Scale (PAS)	12 months
*Predictive factor

[Table 1 to be inserted]

Study Designs

Of the eight studies, six were a prospective design and the remaining two were retrospective. The included studies were published between 2006 and 2018 in five different countries (Australia, Italy, Israel, Sweden and Lithuania).

Participants

The studies investigated a total of 715 participants. Sample sizes ranged from 38–214. The age of participants ranged from 12–64 years. The overall mean age was > 18 for seven studies with one study reporting a median (22 years) only. Females were underrepresented among the total participants (n = 187, 26.15%), with two studies excluding female participation.

The population of two studies included concomitant injuries (meniscal injuries requiring surgery).[32, 34] However, both stated that inclusion of these participants did not impact the results.

Predictive factors

A total of 20 predictive factors were assessed across the eight studies (Table 2), which are discussed below.

Table 2

, Predictive factors investigated across the eight studies
Predictor Variable
Physical	Psychosocial	Demographic / Clinical
Physical activity rating scale (Tegner,^{15, 22, 25, 31, 44}, Noyes¹⁵ and Marx²²)	Psychovitality questionnaire¹⁵ (score ≥ 15)	Body Mass Index (BMI)^{21, 25}
Knee specific patient reported outcome measure (Lysholm,¹⁵ International Knee Documentation Committee [IKDC]¹⁵ and 'knee function'²¹ (defined as 2 questions from IKDC)	Knee-Self Efficacy Scale (K-SES) Present⁴⁴	Weight^{21, 27}
Anterior knee laxity²¹	K-SES Future⁴⁴	Time to surgery^21,22
Rotational knee laxity (pivot shift)²¹	Estimation of ability to return to preinjury level⁴²	Graft type²¹
Passive knee range of motion²¹	Estimation of time (number of months) to achieve postoperative markers⁴²	Smoking status²²
Concentric quadriceps torque²¹	Goal to return to preinjury level⁴²
Eccentric quadriceps torque²¹
Concentric and eccentric hamstring torque²¹
Anterior knee pain²¹

Physical factors

Physical factors were assessed in six of the eight studies. There were three scales used to assess physical activity engagement: Tegner activity scale (assessed in five studies^{24, 26, 27, 29, 31}),[40] Noyes (assessed in one study²⁴)[41] and Marx scale (assessed in one study²⁶).[42] There were also three knee specific patient reported outcome measures: Lysholm score (assessed in one study²⁴),[43] International Knee Documentation Committee (IKDC) (assessed in one study²⁴),[44] and 'knee function' which asked two questions from the IKDC (assessed in one study²⁵). The remaining measures were physical assessments of knee/lower limb function and pain (all assessed in one study²⁵), including passive range of motion (ROM), knee laxity (anterior and rotational), muscle strength (torque) and anterior knee pain.

Psychosocial factors

Psychosocial factors were assessed in three of the eight studies. One study[32] produced a bespoke outcome measure called ‘psychovitality’ which was described as a psychological profile questionnaire. In this questionnaire, psychological factors including patients’ expectations relating to treatment outcomes and motivation to resume pre-injury activity levels were assessed. Scores could range from three to 18 points, with a higher score indicating higher levels of motivation of the patient.

The second study[39] used the Knee Self-Efficacy Scale (K-SES) which is a 22-item scale used to assess a patients perceived self-efficacy under four headings: (1) daily activities, (2) sports and leisure activities, (3) physical activities and (4) your knee function in the future.

The final study[38] asked patients to estimate the number of months it would take to achieve a number of postoperative markers (complete rehabilitation, be able to run/jump and return to their preinjury sport activity), their ability to return to their preinjury level of activity, and whether their goal was to return to their preinjury level.

Demographic/Clinical factors

Demographic and clinical factors were assessed in four of the eight studies. This included body mass index (BMI; assessed in two studies[33, 35]), weight (assessed in two studies[33, 36]), time from injury to surgery (assessed in two studies[33, 34]), graft type[33] and smoking status.[34]

Outcome Measures

Five different outcome measures were used across the eight studies (Table 3): (1) Tegner (2) Marx (3) Physical Activity Scale (PAS) (4) Return to play at the elite level (5) Return to preinjury level (the authors did not specify how this was measured and did not respond to our email asking for clarification). These were measured at a range of different time-points from 1 to 10 years post-operatively.

Table 3

, Outcome measures used and time-point of assessment
Study	Outcome Measure	Time-point of Assessment
Gobbi and Francisco	Marx	Minimum of 24 months
Heijne, Äng and Werner	Tegner	12 months (range 12–16 months)
Hetsroni et al.,	Tegner Marx	7.1 years (range 5–10 years)
Jurkonis, Gudas and Smailys	Tegner	12 months
Liptak and Angel	Return to play at the elite level (AFL Medical Officers Association [AFLMOA] data)	No pre-defined time of assessment but documented as < 1 year after injury or 1 year or longer
McGrath et al.,	Tegner	12 and 24 months
Sonesson et al.,	Return to preinjury level (unspecified)	12 months
Thomeé et al.,	Tegner Physical activity scale (PAS)	12 months

Risk of Bias Assessment

A summary of the risk of bias assessment, using the QUIPS tool, is shown in Table 4. Of the eight studies, five assessed as high risk of bias and three assessed as moderate risk of bias. Percentage agreement between the two reviewers (HC and BS) for the individual risk of bias domains for the QUIPS tool was 88%. Cohen’s kappa statistic, indicating the agreement between reviewers, was k = 0.82, which is considered almost perfect.[45] All discrepancies were resolved through discussion.

Table 4, QUIPS scores showing risk of bias

GRADE

A summary of the GRADE assessment for each predictive factor is shown in Table 5.

Table 5, GRADE scores for each predictive variable

Summary of Results		GRADE Assessment
Summary of Results		Factors that may decrease the quality				Factors that may increase the quality		Quality
Preoperative Predictive Factor	Number of Participants (studies)	Study Limitations	Inconsistency	Indirectness	Imprecision	Moderate/large effect size	Dose effect	Quality
Physical activity rating scale Tegner Marx	403 (4)	High/moderate risk of bias using QUIPS	Inconsistency^b	Indirectness^c	No imprecision	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Knee specific patient reported outcome measure Lysholm IKDC 'Knee function' (measured using two questions from the IKDC) Noyes	164 (2)	High risk of bias using QUIPS	Inconsistency^b	Indirectness^c	Imprecision^e	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Passive knee range of motion	64 (1)	High risk of bias using QUIPS	Inconsistency^a	Indirectness^d	Imprecision^e	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Knee laxity Anterior tibial translation Rotational (Pivot shift)	64 (1)	High risk of bias using QUIPS	Inconsistency^a	Indirectness^d	Imprecision^e	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Thigh muscle torque	64 (1)	High risk of bias using QUIPS	Inconsistency^a	Indirectness^d	Imprecision^e	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Anterior knee pain	64 (1)	High risk of bias using QUIPS	Inconsistency^a	Indirectness^d	Imprecision^e	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Weight	179 (2)	High/moderate risk of bias using QUIPS	Inconsistency^b	Indirectness^c	Imprecision^ef	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
BMI	278 (2)	High risk of bias using QUIPS	Inconsistency^b	Indirectness^c	Imprecision^g	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Graft type	64 (1)	High risk of bias using QUIPS	Inconsistency^a	Indirectness^d	Imprecision^e	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Psychovitality	100 (1)	High risk of bias using QUIPS	Inconsistency^a	No indirectness	Imprecision^e	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Estimation of time (number of months) to achieve postoperative outcomes markers	65 (1)	Moderate risk of bias using QUIPS	Inconsistency^a	No indirectness	Imprecision^e	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Goal to return to preinjury level	65 (1)	Moderate risk of bias using QUIPS	Inconsistency^a	No indirectness	Imprecision^e	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Estimation of ability to return to preinjury level	65 (1)	Moderate risk of bias using QUIPS	Inconsistency^a	No indirectness	Imprecision^e	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Knee Self-Efficacy Scale (K-SES)	38 (1)	High risk of bias using QUIPS	Inconsistency^a	No indirectness	Imprecision^e	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Time to surgery	119 (2)	High/moderate risk of bias using QUIPS	Inconsistency^b	Indirectness^c	Imprecision^g	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low
Smoking status	55 (1)	Moderate risk of bias using QUIPS	Inconsistency^a	Indirectness^d	Imprecision^e	No moderate or large effect size	No exposure-response gradient	⨁◯◯◯ Very low

^aOnly single trial available
^bEstimates of the predictive factors association with the outcome vary in direction and/or no confidence intervals available to assess overlap
^cVariety in the outcome measures used and time-points at which they were assessed

^dThe final sample only represents a subset of the population of interest
^eSmall sample size <400 – single study

^fVariety in time-points at which the preoperative factor is assessed
^gSmall sample size <400 – multiple studies

Table 5, GRADE scores for each predictive variable

[Table 5 to be inserted]

All preoperative variables were assessed to be very low-quality. All factors were downgraded for (1) study limitations, as all studies were graded as ‘high’ or ‘moderate’ risk of bias using the QUIPS tool, (2) inconsistency, as only a single trial was available for most predictive factors or, where more than one trial was available, there was inconsistency in association between the predictive factor and the outcome of interest and no confidence intervals were available to assess overlap. Some factors were downgraded for indirectness where it was determined that the study population was unlikely to be representative of the entire population of interest or where outcome measures and time-points of assessment differed between studies assessing the same preoperative factor. Only one variable was not downgraded for imprecision as the combined sample size of the studies it was assessed in was greater than 400 participants. No factor was deemed to fit the criteria to increase the quality in either of the two categories.

Study Outcomes

Of the 20 predictor variables, two physical factors (low anterior knee laxity and high concentric quadriceps torque), two psychosocial factors (high psychovitality, and positive estimation of ability to return to preinjury level) and one demographic/clinical factor (patella-tendon graft) were found to be positively associated with RTPA between one and ten years post-ACLR. Six physical factors (knee specific patient reported outcome measure, pivot shift, passive knee range of motion, eccentric quadriceps torque, concentric and eccentric hamstrings torque and anterior knee pain), three psychosocial factors (K-SES_Future, patient estimation of time to achieve postoperative markers and goal to return to preinjury level) and one demographic/clinical factor (smoking status) were not found to be associated with RTPA within ten years of an ACLR. There were five factors (one physical: high physical activity recorded on a rating scale, one psychosocial: higher K-SES_Present and three clinical/demographic: low BMI, weight and time to surgery) with variable results as to whether they were predictive or not predictive of returning. The 20 variables are summarised in supplementary file 2, grouped by the categories discussed above.

Summary of main findings

To our knowledge, this is the first systematic review to identify the association between preoperative variables and post-operative RTPA outcomes from ACL surgery. We synthesised variables and post-operative outcomes in eight prospective and retrospective studies. A total of 20 potential predictor variables were identified, of which five were found to be predictive of the outcome of interest. However, the QUIPS tool and GRADE framework challenge the certainty of these results.

Clinical and Research Implications

Of the eight studies in this review, there were five modifiable factors associated with an improved return to physical activity outcome after ACLR. These could therefore be assessed and targeted as potential areas for improvement in the wait time prior to surgery. Identified areas include: anterior knee laxity, quadriceps strength (concentric quadriceps torque), psychovitality, patients’ estimation of their ability to return to their preinjury level and graft choice. This is a key finding of relevance to clinical practice, particularly in the absence of formal guidelines to direct the preoperative stage of patient care. However, future research is needed to determine the success of addressing these variables on RTPA outcomes.

Whilst awaiting surgery, preoperative rehabilitation (also termed 'prehabilitation') has been identified as an important component to help patients prepare, both physically and mentally, for surgery and postoperative rehabilitation.[46–48] However, there is currently no agreed definition of prehabilitation and the evidence base supporting treatment options during this phase is limited.[21] It is therefore of no surprise that clinical practice varies.[49] Typically, prehabilitation research to date has concentrated on physical aspects alone, which is likely to provide limited benefit[21] given the variety of preoperative variables identified. We suggest the consideration of a multi-disciplinary approach to prehabilitation to address physical and psychosocial factors, while also considering demographic/clinical factors. Future research is needed to consolidate these findings but clinical recommendations from this research suggest that programmes could aim to: increase quadriceps strength, improve knee stability, motivate patients to engage in rehabilitation, and addresses patients’ expectations and beliefs in their ability to return to preinjury levels of physical activity. Factors with variable results that could also be considered include overall physical activity level, weight/BMI and shorter time to surgery. Further, high-quality research looking to identify preoperative predictor variables may help to guide future research and clinical practice to improve the development and delivery of prehabilitation packages.

Another factor identified to be predictive of returning to physical activity was a patella tendon graft in favour of a hamstring graft. The graft type of choice is most commonly based on surgeon recommendation with mixed results reported in the literature for the optimum graft choice.[50] There are a number of options available with most recent recommendations suggesting the choice to be made individual to each patient to match their anatomy, age, needs and expectations.[51]

A further point for consideration is the use of predictor variables to facilitate patients and clinicians to set realistic expectations of the outcome of ACLR surgery - an important component of patient care.[52] Patients' preoperative expectations have previously been linked to motivation to engage in rehabilitation and overall satisfaction.[38, 53, 54] It will further allow for appropriate outcome measures to be selected to measure patients' progress. There are a number of outcome measures used in ACL rehabilitation, which was evident in this study with five different outcomes used to assess physical activity/sport engagement at four different postoperative time points. A recently published consensus statement highlighted this controversy in defining how and when we measure RTPA after ACLR and what is deemed to be a successful outcome.[55] Currently, no standard set of outcome measures exist (e.g. core outcome set) to allow for consistent reporting of ACLR outcomes in clinical practice. This is an important gap within the research.

Clinical practice summary

One of the primary goals driving completion of this review was to provide up-to-date evidence for healthcare professionals to support decision making in clinical practice. Specifically, to identify those factors that are associated with RTPA outcomes which are modifiable, as knowledge of these may help to direct treatment. The predictors identified in this review may support clinicians in focussing preoperative treatment and have constructive conversations with patients about important lifestyle changes that may improve long-term outcomes. However, it is important to highlight that although a number of factors were found to be predictive, based on the risk of bias and level of evidence assessment, no strong conclusions can be made.

Future research summary

This review has highlighted a number of areas of focus for future research. Firstly, that further high-quality prospective predictor studies are needed that consider relevant confounding factors to determine preoperative predictor variables of ACLR outcomes. Secondly, determining an optimal preoperative treatment package and understanding the clinical implications of this. Finally, mirroring other recent research findings, a consistent set of outcome measures needs to be developed with an agreed time frame of assessment to determine the success of ACLR.

Strengths and Limitations

An inclusive approach was taken allowing for the inclusion of all study designs, outcome measures of interest and time-points of assessment. A risk of bias and certainty of evidence assessment was completed, and the initial search was updated closer to the time of submission to ensure newer studies were not missed.

However, five of the eight studies included in this review were scored as 'high' on the risk of bias assessment with an overall very low-quality of evidence using the GRADE framework. Only English studies were included in the review, thus introducing publication bias. The overall population group included in this review was dominated by males (> 70%), despite females being at a greater risk of sustaining an ACL injury.[56] This is an important consideration when interpreting the results.

In addition, we were unable to complete a meta-analysis as data were deemed to be heterogeneous, which limits robust analysis of the results. Further, four of the final eight studies were identified through reference list searching and so, there is the potential that further relevant studies may have been missed.

The findings of this review indicate that very-low level evidence exists to support the use of any physical, psychosocial, or demographic/clinical preoperative variable as a predictor of return to physical activity after ACL surgery.

Further low-risk studies are required to support the use of preoperative predictor variables. Further work is also needed to support the development and delivery of prehabilitation packages and to provide consistency in the reporting of ACLR outcomes.

ACL Anterior Cruciate Ligament

ACLR Anterior Cruciate Ligament Reconstruction

AFLMOA American Football League Medical Officers Association

BMI Body Mass Index

GRADE Grading of Recommendations Assessment, Development and Evaluation

IKDC International Knee Documentation Committee

K-SES Knee Self-Efficacy Scale

MeSH Medical Subject Heading

NHS National Health Service

PAS Physical Activity Scale

PEOS Population-Exposure-Outcome-Study

QUIPS Quality in Prognostic Studies

ROM Range of Movement

RTPA Return to Physical Activity

RTS Return to Sport

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable

Availability of data and materials

All data generated or analysed during this study are included in this published article [and its supplementary information files].

Competing interests

The authors declare that they have no competing interests

Funding

HC was supported by an Integrated Clinical Academic Pre-Doctoral Bridging Programme funded by Health Education England/National Institute for Health Research (HEE/NIHR) working in the East Midlands and a subsequent HEE/NIHR Clinical Doctoral Research Fellowship. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the NIHR, HEE or the Department of Health.

Authors' contributions

HC was responsible for conception and design, publication screening, acquisition of data, analysis and interpretation (including risk of bias assessment and GRADE) and drafting and revising the manuscript. BS was responsible for publication screening and risk of bias assessment and GRADE. All authors (HC, GL and BS) were involved in data interpretation, reviewing and revising the manuscript and final approval of the version to be published. All have read and approved the final version.

Acknowledgements

Not applicable

Collins JE, Katz JN, Donnell-Fink LA, Martin SD, Losina E. Cumulative incidence of ACL reconstruction after ACL injury in adults: Role of age, sex and race. Am J Sports Med. 2013;41:544. https://doi.org/10.1177/0363546512472042.
Beard D. The ACL SNNAP Trial: ACL surgery necessity in non acute patients. ISRCTN: 10110685 Clinical Trials Gov: NCT02980367 2017. https://doi.org/https://doi.org/10.1186/ISRCTN10110685.
Webster KE, Hewett TE. Anterior Cruciate Ligament Injury and Knee Osteoarthritis: An Umbrella Systematic Review and Meta-analysis. Clin J Sport Med. 2021;00:1–8. https://doi.org/10.1097/JSM.0000000000000894.
Feucht MJ, Cotic M, Saier T, Minzlaff P, Plath JE, Imhoff AB, et al. Patient expectations of primary and revision anterior cruciate ligament reconstruction. Knee Surg Sports Traumatol Arthrosc. 2016;24:201–7. https://doi.org/10.1007/s00167-014-3364-z.
Feller JA, Webster KE. Return to sport following anterior cruciate ligament reconstruction. Int Orthop. 2013;37:285–90. https://doi.org/10.1007/s00264-012-1690-7.
Webster KE, Feller JA. Expectations for Return to Preinjury Sport Before and After Anterior Cruciate Ligament Reconstruction. Am J Sports Med. 2019;47:578–83. https://doi.org/10.1177/0363546518819454.
Burland JP, Toonstra J, Werner JL, Mattacola CG, Howell DM, Howard JS. Decision to return to sport after anterior cruciate ligament reconstruction, Part I: A qualitative investigation of psychosocial factors. J Athl Train. 2018;53:452–63. https://doi.org/10.4085/1062-6050-313-16.
Beard DJ, Davies L, Cook JA, Stokes J, Leal J, Fletcher H, et al. Rehabilitation versus surgical reconstruction for non-acute anterior cruciate ligament injury (ACL SNNAP): a pragmatic randomised controlled trial. The Lancet. 2022;400:605–15. https://doi.org/10.1016/S0140-6736(22)01424-6.
Dunn WR, Spindler KP. Predictors of activity level 2 years after anterior cruciate ligament reconstruction (ACLR): A multicenter orthopaedic outcomes network (MOON) ACLR cohort study. Am J Sports Med. 2010;38:2040–50. https://doi.org/10.1177/0363546510370280.
Ardern CL, Taylor NF, Feller JA, Whitehead TS, Webster KE. Sports participation 2 years after anterior cruciate ligament reconstruction in athletes who had not returned to sport at 1 year: A prospective follow-up of physical function and psychological factors in 122 athletes. Am J Sports Med. 2015;43:848–56. https://doi.org/10.1177/0363546514563282.
Ardern CL, Österberg A, Tagesson S, Gauffin H, Webster KE, Kvist J. The impact of psychological readiness to return to sport and recreational activities after anterior cruciate ligament reconstruction. Br J Sports Med. 2014;48:1613–9. https://doi.org/10.1136/bjsports-2014-093842.
Flanigan DC, Everhart JS, Pedroza A, Smith T, Kaeding CC. Fear of reinjury (Kinesiophobia) and persistent knee symptoms are common factors for lack of return to sport after anterior cruciate ligament reconstruction. Arthrosc - J Arthroscopic Relat Surg. 2013;29:1322–9. https://doi.org/10.1016/j.arthro.2013.05.015.
Kvist J, Ek A, Sporrstedt K, Good L. Fear of re-injury: A hindrance for returning to sports after anterior cruciate ligament reconstruction. Knee Surg Sports Traumatol Arthrosc. 2005;13:393–7. https://doi.org/10.1007/s00167-004-0591-8.
Svantesson E, Hamrin Senorski E, Webster KE, Karlsson J, Diermeier T, Rothrauff BB, et al. Clinical outcomes after anterior cruciate ligament injury: panther symposium ACL injury clinical outcomes consensus group. Knee Surgery, Sports Traumatology, Arthroscopy 2020;28:2415–34. https://doi.org/10.1007/s00167-020-06061-x.
Ardern CL, Glasgow P, Schneiders A, Witvrouw E, Clarsen B, Cools A, et al. 2016 Consensus statement on return to sport from the First World Congress in Sports Physical Therapy, Bern. Br J Sports Med. 2016;50:853–64. https://doi.org/10.1136/bjsports-2016-096278.
Webster KE, Feller JA. A research update on the state of play for return to sport after anterior cruciate ligament reconstruction. Journal of Orthopaedics and Traumatology 2019;20. https://doi.org/10.1186/s10195-018-0516-9.
Rambaud AJM, Semay B, Samozino P, Morin JB, Testa R, Philippot R, et al. Criteria for Return to Sport after Anterior Cruciate Ligament reconstruction with lower reinjury risk (CR’STAL study): protocol for a prospective observational study in France. BMJ Open 2017;7. https://doi.org/10.1136/BMJOPEN-2016-015087.
Filbay SR, Grindem H. Evidence-based recommendations for the management of anterior cruciate ligament (ACL) rupture. Best Pract Res Clin Rheumatol. 2019;33:33–47. https://doi.org/10.1016/j.berh.2019.01.018.
Liebensteiner MC, Khosravi I, Hirschmann MT, Heuberer PR, Heuberer P, Niemeyer P, et al. Massive cutback in orthopaedic healthcare services due to the COVID-19 pandemic. Knee Surg Sports Traumatol Arthrosc. 2020;28:1. https://doi.org/10.1007/S00167-020-06032-2.
Hampton BM, Riley E, Garneti N, Anderson A, Wembridge K, Hampton M, et al. The orthopaedic waiting list crisis. Https://DoiOrg/101302/2633-146227BJO-2021-0044R1 2021;2:530–4. https://doi.org/10.1302/2633-1462.27.BJO-2021-0044.R1.
Carter HM, Littlewood C, Webster KE, Smith BE. The effectiveness of preoperative rehabilitation programmes on postoperative outcomes following anterior cruciate ligament (ACL) reconstruction: A systematic review. BMC Musculoskelet Disord. 2020;21:1–13. https://doi.org/10.1186/s12891-020-03676-6.
Carter H, Lewis G, Smith BE. Preoperative predictors for a successful return to sport following anterior cruciate ligament reconstruction (ACLR): a protocol for a systematic review and meta-analysis. BMJ Open. 2021;11:e048295. https://doi.org/10.1136/BMJOPEN-2020-048295.
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372. https://doi.org/10.1136/BMJ.N71.
Ardern CL, Büttner F, Andrade R, Weir A, Ashe MC, Holden S, et al. Implementing the 27 PRISMA 2020 Statement items for systematic reviews in the sport and exercise medicine, musculoskeletal rehabilitation and sports science fields: the PERSiST (implementing Prisma in Exercise, Rehabilitation, Sport medicine and SporTs science) guidance. Br J Sports Med 2021;0:bjsports-2021-103987. https://doi.org/10.1136/BJSPORTS-2021-103987.
Riley RD, Moons KGM, Snell KIE, Ensor J, Hooft L, Altman DG, et al. A guide to systematic review and meta-analysis of prognostic factor studies. BMJ (Online) 2019;364. https://doi.org/10.1136/BMJ.K4597.
Hayden JA, Côté P, Bombardier C. Evaluation of the quality of prognosis studies in systematic reviews. Ann Intern Med. 2006;144:427–37. https://doi.org/10.7326/0003-4819-144-6-200603210-00010.
Hayden JA, van der Windt DA, Cartwright JL, Côté P, Bombardier C. Assessing bias in studies of prognostic factors. Ann Intern Med. 2013;158:280–6. https://doi.org/10.7326/0003-4819-158-4-201302190-00009.
Huguet A, Hayden JA, Stinson J, McGrath PJ, Chambers CT, Tougas ME, et al. Judging the quality of evidence in reviews of prognostic factor research: Adapting the GRADE framework. Syst Rev 2013;2. https://doi.org/10.1186/2046-4053-2-71.
Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336:924–6. https://doi.org/10.1136/BMJ.39489.470347.AD.
Schünemann HJ, Oxman AD, Brozek J, Glasziou P, Jaeschke R, Vist GE, et al. Grading quality of evidence and strength of recommendations for diagnostic tests and strategies. BMJ. 2008;336:503–8. https://doi.org/10.1136/BMJ.39500.677199.AE.
Page M, Higgins JPTSJ. Chapter 13: Assessing risk of bias due to missing results in a synthesis. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al., editors. Cochrane Handbook for Systematic Reviews of Interventions Version 6.0. Available from (Updated July 2019). 6.0, n.d.
Gobbi A, Francisco R. Factors affecting return to sports after anterior cruciate ligament reconstruction with patellar tendon and hamstring graft: A prospective clinical investigation. Knee Surg Sports Traumatol Arthrosc. 2006;14:1021–8. https://doi.org/10.1007/S00167-006-0050-9.
Heijne A, Äng BO, Werner S. Predictive factors for 12-month outcome after anterior cruciate ligament reconstruction. Scand J Med Sci Sports. 2009;19:842–9. https://doi.org/10.1111/J.1600-0838.2008.00852.X.
Hetsroni I, Van-Stee M, Marom N, Koch JEJ, Dolev E, Maoz G, et al. Factors Associated With Improved Function and Maintenance of Sports Activities at 5 to 10 Years After Autologous Hamstring ACL Reconstruction in Young Men. Orthop J Sports Med 2017;5. https://doi.org/10.1177/2325967117700841.
Jurkonis R, Gudas R, Smailys A. Influence of Graft Diameter on Functional Outcomes After Anterior Cruciate Ligament Reconstruction: A Prospective Study with a 1-Year Follow-Up. Med Sci Monit. 2018;24:4339. https://doi.org/10.12659/MSM.908212.
Liptak MG, Angel KR. Return to Play and Player Performance After Anterior Cruciate Ligament Injury in Elite Australian Rules Football Players. Orthop J Sports Med. 2017;5:2325967117711885. https://doi.org/10.1177/2325967117711885.
McGrath TM, Waddington G, Scarvell JM, Ball N, Creer R, Woods K, et al. An Ecological Study of Anterior Cruciate Ligament Reconstruction, Part 1: Clinical Tests Do Not Correlate With Return-to-Sport Outcomes. Http://DxDoiOrg/101177/2325967116672208 2016;4. https://doi.org/10.1177/2325967116672208.
Sonesson S, Kvist J, Ardern C, Österberg A, Silbernagel KG. Psychological factors are important to return to pre-injury sport activity after anterior cruciate ligament reconstruction: expect and motivate to satisfy. Knee Surg Sports Traumatol Arthrosc. 2017;25:1375–84. https://doi.org/10.1007/S00167-016-4294-8/TABLES/4.
Thomeé P, Währborg P, Börjesson M, Thomeé R, Eriksson BI, Karlsson J. Self-efficacy of knee function as a pre-operative predictor of outcome 1 year after anterior cruciate ligament reconstruction. Knee Surg Sports Traumatol Arthrosc. 2008;16:118–27. https://doi.org/10.1007/S00167-007-0433-6.
Tegner Y, Lysholm J. Rating systems in the evaluation of knee ligament injuries. Clin Orthop Relat Res 1985;NO. 198:43–9. https://doi.org/10.1097/00003086-198509000-00007.
Noyes F, Barber-Westin S, Mooar L. A Rationale for Assessing Sports Activity Levels and Limitations in Knee Disorders. Clinical Orthopaedics and Related Research · 1989:238–49. https://doi.org/10.1097/00003086-198909000-00034.
Marx RG, Stump TJ, Jones EC, Wickiewicz TL, Warren RF. Development and evaluation of an activity rating scale for disorders of the knee. Am J Sports Med. 2001;29:213–8. https://doi.org/10.1177/03635465010290021601.
Lysholm J, Gillquist J. Evaluation of knee ligament surgery results with special emphasis on use of a scoring scale. Am J Sports Med. 1982;10:150–4. https://doi.org/10.1177/036354658201000306.
Collins NJ, Misra D, Felson DT, Crossley KM, Roos EM. Measures of Knee Function 2011. https://doi.org/10.1002/acr.20632.
McHugh ML. Interrater reliability: the kappa statistic. Biochem Med (Zagreb). 2012;22:276. https://doi.org/10.11613/bm.2012.031.
Everhart JS, Best TM, Flanigan DC. Psychological predictors of anterior cruciate ligament reconstruction outcomes: a systematic review. Knee Surg Sports Traumatol Arthrosc. 2015;23:752–62. https://doi.org/10.1007/s00167-013-2699-1.
Wilk KE, Arrigo CA. Preoperative Phase in the Rehabilitation of the Patient Undergoing Anterior Cruciate Ligament Reconstruction. Oper Tech Sports Med. 2016;24:12–20. https://doi.org/10.1053/j.otsm.2015.10.003.
Gokeler A, Dingenen B, Mouton C, Seil R. Clinical course and recommendations for patients after anterior cruciate ligament injury and subsequent reconstruction: A narrative review. EFORT Open Rev. 2017;2:410–20. https://doi.org/10.1302/2058-5241.2.170011.
Carter HM, Webster KE, Smith BE. Current preoperative physiotherapy management strategies for patients awaiting Anterior Cruciate Ligament Reconstruction (ACLR): A worldwide survey of physiotherapy practice. Knee. 2021;28:300–10. https://doi.org/https://doi.org/10.1016/j.knee.2020.12.018.
Macaulay AA, Perfetti DC, Levine WN. Anterior cruciate ligament graft choices. Sports Health. 2012;4:63–8. https://doi.org/10.1177/1941738111409890.
Buerba RA, Boden SA, Lesniak B, Fu F. Graft Selection in Contemporary Anterior Cruciate Ligament Reconstruction 2021. https://doi.org/10.5435/JAAOSGlobal-D-21-00230.
El-Haddad C, Hegazi I, Hu W. Understanding Patient Expectations of Health Care: A Qualitative Study. J Patient Exp. 2020;7:1724–31. https://doi.org/10.1177/2374373520921692.
Jain D, Bendich I, Nguyen LCL, Nguyen LL, Lewis CG, Huddleston JI, et al. Do Patient Expectations Influence Patient-Reported Outcomes and Satisfaction in Total Hip Arthroplasty? A Prospective, Multicenter Study. J Arthroplasty. 2017;32:3322–7. https://doi.org/10.1016/j.arth.2017.06.017.
Smith MJ, Choma TJ. Patient satisfaction in musculoskeletal medicine. Curr Rev Musculoskelet Med. 2017;10:207–11. https://doi.org/10.1007/s12178-017-9403-x.
Meredith SJ, Rauer T, Chmielewski TL, Fink C, Diermeier T, Rothrauff BB, et al. Return to Sport After Anterior Cruciate Ligament Injury: Panther Symposium ACL Injury Return to Sport Consensus Group. Orthop J Sports Med 2020;8:2325967120930829. https://doi.org/10.1177/2325967120930829.
Montalvo AM, Schneider DK, Webster KE, Yut L, Galloway MT, Heidt RS, et al. Anterior Cruciate Ligament Injury Risk in Sport: A Systematic Review and Meta-Analysis of Injury Incidence by Sex and Sport Classification. J Athl Train. 2019;54:472–82. https://doi.org/10.4085/1062-6050-407-16.

No competing interests reported.

Download PDF

Journal Publication

published 09 Jun, 2023

Read the published version in BMC Musculoskeletal Disorders →

Editorial decision: Major revision
04 Apr, 2023
Reviews received at journal
01 Apr, 2023
Reviewers agreed at journal
19 Jan, 2023
Reviews received at journal
12 Jan, 2023
Reviewers agreed at journal
02 Jan, 2023
Reviewers invited by journal
09 Nov, 2022
Editor assigned by journal
09 Nov, 2022
Editor invited by journal
09 Nov, 2022
Submission checks completed at journal
09 Nov, 2022
First submitted to journal
29 Sep, 2022

You are reading this latest preprint version

Preoperative predictors for return to physical activity following anterior cruciate ligament reconstruction (ACLR): a systematic review

Status:

Journal Publication

Version 1

Abstract

Background

methods

Results

Conclusion

Trial registration

Figures

Background

Objective

Methods

Protocol and Registration

Eligibility Criteria

Population

Exposure

Outcome

Study

Search Strategy

Study Selection

Data Extraction

Risk of Bias Assessment

GRADE

Data Synthesis and Analysis

Results

Study Selection

Characteristics of the included studies

[Table 1 to be inserted]

Study Designs

Participants

Predictive factors

Physical factors

Psychosocial factors

Demographic/Clinical factors

Outcome Measures

Risk of Bias Assessment

Table 4, QUIPS scores showing risk of bias

GRADE

Table 5, GRADE scores for each predictive variable

[Table 5 to be inserted]

Study Outcomes

Discussion

Summary of main findings

Clinical and Research Implications

Clinical practice summary

Future research summary

Strengths and Limitations

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1