Enter NR in not reported.

Preferentially enter data for total sample only (not per arm). Feel free to calculate weighted means/% as needed. Select and enter data for all that apply. Categorical age data are in the next question.

Preferentially extract total sample only (not per arm). Feel free to determine the weighted average % across reported arms and enter that single number. Select and enter data for all that apply. Percentages only (not proportions).

Preferentially enter data for total sample only (not per arm). Feel free to calculate weighted means/% as needed. Select and enter data for all that apply.

Define the comorbidities. If % reported, enter % for total sample and each study arm. Skip those that are not reported. For BP, enter the mean SBP/DBP (or MAP). Just the mean, not the SD etc. For P<0.10 column, leave blank if no difference between arms.

Preferentially extract total sample only (not per arm). Feel free to determine the weighted average % across reported arms and enter that single number. Select and enter data for all that apply. Percentages only (not proportions). Private, Medicare, Medicaid, Other public (100% for most countries).

Enter NR in not reported.

Extract as defined by study.

Enter NR in not reported.

Enter NR in not reported.

Please select the incision approach used for HIP replacement (NB. the incision approach to the knee is always the same, the anterior)

Please select the approach used for KNEE replacement (https://www.healthline.com/health/total-knee-replacement-surgery/surgical-options#Partial-knee-replacement)

Copy text, where reported

List any used

Only extract for KQs 2 and 4 regarding rehabilitation AFTER the surgery

Use this for papers that were mistakingly screened in.

Check one

Skip if an RCT.

Skip if not an NRCS.

Define non-industry: academia, government, non-profit, etc. Indicate both funding (money) and sponsorship (in-kind contributions including equipment.)

For studies with multiple papers, include identifier (study name, database/registry name, or (medical) center) and years of study if necessary (eg, Albany Medical Center 2001-13).

Enter the PMIDs or other identifiers of co-publications. Skip if none.

Enter NCT number (include "NCT") of associated NCT files. Skip if none.

Years (not months) when people were treated. If either is not reported, enter NR

Enter NR if not reported

Keep succinct. Use common abbreviations. Omit criteria of minor relevance (eg, language, consent)

Keep succinct. Use common abbreviations. Omit criteria of minor relevance (eg, language, consent). Enter NR if not reported.

Choose the best descriptor based on following list of types of hospitals https://www.ncbi.nlm.nih.gov/books/NBK333506/table/ch04.sec1.table1/

Choose the best descriptor

Use (−) numbers to indicate number of weeks prior to surgery and (+) numbers to indicate number of weeks after surgery

Use (−) numbers to indicate number of weeks prior to surgery and (+) numbers to indicate number of weeks after surgery

Selection bias (biased allocation to interventions) due to inadequate generation of a randomized sequence. <br /><span style='color: blue;'>NO (low RoB)<span style='color: black;'> if the investigators describe a random component in the sequence generation process such as: referring to a random number table, using a computer random number generator. If randomization done off-site (e.g., centrally), can assume low risk of bias. <br /><span style='color: red;'>YES (high RoB)<span style='color: black;'> if the investigators describe a non-random component in the sequence generation process, such as: sequence generated by odd or even date of birth, date (or day) of admission, hospital or clinic record number; or allocation by judgement of the clinician, preference of the participant, etc. <br /><span style='color: orange;'>UNSURE<span style='color: black;'> if not reported (e.g., says only "randomized").<br /><span style='color: brown;'>NOT APPLICABLE<span style='color: black;'> if not an RCT.

Selection bias (biased allocation to interventions) due to inadequate concealment of allocations prior to assignment<br /><span style='color: blue;'>NO (low RoB)<span style='color: black;'> if the participants and investigators enrolling participants could not foresee assignment because one of the following, or an equivalent method, was used to conceal allocation: central allocation (including telephone, web-based and pharmacy-controlled randomization); or sequentially numbered, opaque, sealed envelopes. <br /><span style='color: red;'>YES (high RoB)<span style='color: black;'> if participants or investigators enrolling participants could possibly foresee assignments and thus introduce selection bias, such as allocation based on: using an open random allocation schedule (e.g. a list of random numbers); assignment envelopes were used without appropriate safeguards (e.g. if envelopes were unsealed or non-opaque or not sequentially numbered); alternation or rotation; date of birth; case record number; or other explicitly unconcealed procedures. <br /><span style='color: orange;'>UNSURE<span style='color: black;'> if not reported (e.g., says only "randomized"). <br /><span style='color: brown;'>NOT APPLICABLE<span style='color: black;'> if not an RCT.

Detection bias due to knowledge of the allocated interventions by study participants. <br /><span style='color: blue;'>NO (low RoB)<span style='color: black;'> if blinding of patient was ensured and it was unlikely that the blinding could have been broken; if not blinded, may still be low if outcome is not likely to be influenced by lack of blinding (e.g., laboratory data, other fully objective measures). <br /><span style='color: red;'>YES (high RoB)<span style='color: black;'> if no blinding of (potentially) subjective outcome. <span style='color: purple;'>Even if blinding was not possible.<br /><span style='color: orange;'>UNSURE<span style='color: black;'> if not reported and cannot infer one way or the other. <br /><span style='color: brown;'>NB:<span style='color: purple;'> 1) Answer for all study designs. 2) If blinding assessment varies among outcomes, explain in Notes.

Detection bias due to knowledge of the allocated interventions by personnel (eg, therapist). <br /><span style='color: blue;'>NO (low RoB)<span style='color: black;'> if blinding of the provider was ensured and it was unlikely that the blinding could have been broken; if not blinded, may still be low if outcome is not likely to be influenced by lack of blinding (e.g., laboratory data, other fully objective measures). <br /><span style='color: red;'>YES (high RoB)<span style='color: black;'> if no blinding of (potentially) subjective outcome. <span style='color: purple;'>Even if blinding was not possible.<br /><span style='color: orange;'>UNSURE<span style='color: black;'> if not reported and cannot infer one way or the other. <br /><span style='color: brown;'>NB:<span style='color: purple;'> 1) Answer for all study designs. 2) If blinding assessment varies among outcomes, explain in Notes.

Detection bias due to knowledge of the allocated interventions by outcome assessors. NOTE THAT FOR SOME OUTCOMES, THE PATIENT IS THE OUTCOME ASSESSOR. <br /><span style='color: blue;'>NO (low RoB)<span style='color: black;'> if blinding of the outcome assessment was ensured and it was unlikely that the blinding could have been broken; if not blinded, may still be low if outcome is not likely to be influenced by lack of blinding (e.g., laboratory data, other fully objective measures). <br /><span style='color: red;'>YES (high RoB)<span style='color: black;'> if no blinding of (potentially) subjective outcome. <br /><span style='color: orange;'>UNSURE<span style='color: black;'> if not reported and cannot infer one way or the other. <br /><span style='color: brown;'>NB:<span style='color: purple;'> 1) Answer for all study designs. 2) If blinding assessment varies among outcomes, explain in Notes.

Attrition bias due to amount, nature or handling of incomplete outcome data. <br /><span style='color: blue;'>NO (low RoB)<span style='color: black;'> if limited loss of data (between enrolled and analyzed). Operationally, we define as <20% loss-to-followup (see caveat under "high"). However, survival curve analysis (e.g., hazard ratio) with censoring can be considered low risk of bias, regardless of percentage loss. <br /><span style='color: red;'>YES (high RoB)<span style='color: black;'> if ≥20% loss-to-followup or if there is any substantive imbalance between arms (e.g., 2% in one group, 15% in the other). <br /><span style='color: orange;'>UNSURE<span style='color: black;'> only if cannot be assessed because number enrolled (or number who received interventions) or number analyzed not reported. <br /><span style='color: brown;'>NB:<span style='color: purple;'>1) Answer for all study designs. 2) If drop-out varies among outcomes, explain in Notes.

<span style='color: blue;'>NO (low RoB): <span style='color: black;'>There is low risk of reporting bias if the study protocol is available and all of the study’s pre-specified (primary and secondary) outcomes that are of interest in the review have been reported in the pre-specified way, or if the study protocol is not available but it is clear that the published reports include all expected outcome, including those that were pre-specified (convincing text of this nature may be uncommon). <br /><span style='color: red;'>YES (high RoB): <span style='color: black;'>There is a high risk of reporting bias if not all of the study’s pre-specified primary outcomes have been reported; one or more primary outcomes is reported using measurements, analysis methods or subsets of the data (e.g. subscales) that were not pre-specified; one or more reported primary outcomes were not pre-specified (unless clear justification for their reporting is provided, such as an unexpected adverse effect); one or more outcomes of interest in the review are reported incompletely so that they cannot be entered in a meta-analysis; the study report fails to include results for a key outcome that would be expected to have been reported for such a study.<br /><span style='color: orange;'>UNSURE<span style='color: black;'> if no protocol or otherwise cannot tell. <br /><span style='color: brown;'>NB:<span style='color: purple;'>1) Answer for all study designs.

Consider biases due to problems not covered elsewhere. <br /><span style='color: blue;'>NO (low RoB)<span style='color: black;'> if there are no other biases to address. <br /><span style='color: red;'>YES (high RoB)<span style='color: black;'> if other bias or concern. <span style='color: purple;'>Describe these in the Notes.

For RCT: <span style='color: blue;'>NO (low RoB)<span style='color: black;'> unless there is a <span style='color: red;'>clinically important baseline difference<span style='color: black;'> in a characteristic that is unaccounted for.<br /> For NRCS:<span style='color: red;'> YES<span style='color: black;'> except possibly in rare situations, such as when studying harms that are very unlikely to be related to factors that influence treatment decisions, no confounding is expected and the study can be considered to be at low risk of bias due to confounding, equivalent to a fully randomized trial. <br /><span style='color: blue;'> If no risk of confounding, then skip to Question 7 (overall confounding RoB).

Could (or did) participants cross-over between intervention groups after the start of the intervention? <br /><span style='color: red;'>YES<span style='color: black;'> or <span style='color: blue;'>NO<span style='color: black;'> (answer "no" if no reporting about crossovers)

For NRCS (or RCT requiring adjustment): <br /> <span style='color: red;'>YES (higher RoB):<span style='color: black;'> used stratification, regression, or matching. <br /> <span style='color: blue;'>NO (lower RoB):<span style='color: black;'> used propensity score matching (aka inverse probability weighting) or similar.<br /> <span style='color: purple;'>REJECT if NRCS with no adjustment for confounding

Appropriate control of confounding requires that the variables adjusted for are valid and reliable measures of the confounding domains. <br /><span style='color: blue;'>NO (low RoB)<span style='color: black;'> if objective or standard clinical measures (eg, age, sex, time since surgery, duration of osteoarthritis). Also <span style='color: blue;'>NO<span style='color: black;'> if validated subjective measure. For this purpose, we can assume any typically used or named/acronym'ed measure (eg, of severity of osteoarthritis or function) has been validated.<br /><span style='color: red;'>YES<span style='color: black;'> if atypical or one-off subjective measure. <span style='color: red;'> Name the unvalidated measure in the notes.

Controlling for post-intervention (or after the start of the intervention) variables is not appropriate. For example, compliance, number of sessions, intermediate outcomes (like pain during rehab).<br /> <span style='color: red;'>YES<span style='color: black;'> if any variables in model (other than intervention) were measured after the start of the intervention.<span style='color: purple;'> We might reject these studies.<br /> <span style='color: blue;'>NO<span style='color: black;'> if all variables measured pre-intervention (assume this is the case if not fully explicit).

<span style='color: red;'>YES<span style='color: black;'> if answered Yes to any questions 1.1 to 1.6.<br /> <span style='color: blue;'>NO<span style='color: black;'> if answered No to all 1.1-1.6

This domain is concerned only with SELECTION into the study based on participant characteristics observed after the start of intervention. Selection based on characteristics observed before the start of intervention can be addressed by controlling for imbalances between experimental intervention and comparator groups in baseline characteristics that are prognostic for the outcome (baseline confounding).<br /> <span style='color: blue;'>NO (low RoB)<span style='color: black;'> for RCT or for NRCS where eligibility criteria (including exclusion reasons) were based on (for example) receiving surgery or other criteria where those in either treatment group were enrolled based on criteria unrelated to their (rehab) treatment. If NO, skip questions 2.2 and 2.3.<br /> <span style='color: red;'>YES (high RoB)<span style='color: black;'> for NRCS where eligibility criteria were based, at least in part, on factors related to the choice of intervention.

Selection bias occurs when selection is related to an effect of either intervention or a cause of intervention and an effect of either the outcome or a cause of the outcome. Therefore, the result is at risk of selection bias if selection into the study is related to both the intervention and the outcome.<br /> <span style='color: red;'>YES<span style='color: black;'> if an eligibility criterion is/may be related choice of intervention.<br /> <span style='color: blue;'>NO<span style='color: black;'> otherwise.

Selection bias occurs when selection is related to an effect of either intervention or a cause of intervention and an effect of either the outcome or a cause of the outcome. Therefore, the result is at risk of selection bias if selection into the study is related to both the intervention and the outcome.<br /> <span style='color: red;'>YES<span style='color: black;'> if an eligibility criterion is/may be related to both choice of intervention (Question 2.2) and to an outcome of interest.<br /> <span style='color: blue;'>NO<span style='color: black;'> otherwise.

It is in principle possible to correct for selection biases, for example by using inverse probability weights to create a pseudo-population in which the selection bias has been removed, or by modeling the distributions of the missing participants or follow up times and outcome events and including them using missing data methodology. Propensity score analyses etc. would need to specifically account for these issues.<br /> However such methods are rarely used and the answer to this question will usually be <br /><span style='color: red;'>YES<span style='color: black;'>, no appropriate adjustment made.

<span style='color: red;'>YES<span style='color: black;'> if answered Yes to any questions 2.1 to 2.3 and 2.6.<br /> <span style='color: blue;'>NO<span style='color: black;'> if answered No to all 2.1-2.6

Were eligibility/selection criteria for the study population NOT prespecified and clearly described? Question reversed to maintain Yes/No meaning across questions.<br /><span style='color: blue;'>NO (good quality)<span style='color: black;'> if prespecified and clear (you could reasonably determine whether a patient in front of you would have been enrolled). By "prespecified" we mean that there were clear participant eligibility, whether prospective or retrospective design. <br /><span style='color: red;'>YES (poor quality)<span style='color: black;'> if not clearly prespecified or described. Explain in Notes.

Was the intervention NOT clearly described and delivered consistently across the study population? Question reversed to maintain Yes/No meaning across questions.<br /><span style='color: blue;'>NO (good quality)<span style='color: black;'> if clear and consistent. Based on article, you are reasonably confident a therapist could reproduce the intervention AND all participants received the same intervention (in regards to the salient features of the intervention). <br /><span style='color: red;'>YES (poor quality)<span style='color: black;'> if not clear or consistently delivered. <br /><span style='color: purple;'>IF NOT CLEAR AND CONSISTENT, WILL LIKELY REJECT.

Were the outcome measures NOT prespecified, clearly defined, valid, reliable, and assessed consistently across all study participants? Question reversed to maintain Yes/No meaning across questions.<br /><span style='color: blue;'>No (good quality)<span style='color: black;'> if *all outcomes (of interest)* are clear and valid. Scores, scales, tools, etc. do not need to be formally validated, as long as the outcome measure is reasonable and appropriate. <br /><span style='color: red;'>YES (poor quality)<span style='color: black;'> if *all outcomes (of interest)* are problematic. <span style='color: purple;'>Explain in Notes. <br /><span style='color: brown;'>OTHER.<span style='color: black;'> If only some outcomes are high risk of bias. <span style='color: purple;'>Explain in Notes.

... or related to the choice of intervention?<br /> Usually <span style='color: red;'>YES<span style='color: black;'> unless there is documentation that dropouts (or switches) were unrelated (eg, moved out of town)