Total knee arthroplasty (TKA) is among the most effective and commonly performed orthopaedic procedures for end-stage knee osteoarthritis, reliably relieving pain and restoring function in appropriately selected patients. Global demand for TKA continues to rise substantially, with projections indicating a several-fold increase in procedure volumes over the coming decades [1]. In Pakistan, the burden of knee osteoarthritis is considerable, driven by high rates of obesity, advancing age demographics, and increasing life expectancy. However, the capacity of the healthcare system to deliver safe arthroplasty services is constrained by limited resources [2], late presentation, and a high prevalence of unmanaged comorbid conditions. These factors collectively elevate the risk of perioperative adverse events and challenge the sustainability of arthroplasty programmes in low- and middle-income settings.

The relationship between preoperative patient status and postoperative outcomes following TKA is well established. Modifiable risk factors including poorly controlled diabetes mellitus, anaemia, obesity, tobacco use, malnutrition, and functional deconditioning have each been associated with increased rates of surgical site infection, venous thromboembolism, prolonged hospitalisation, and readmission [3,4]. A large claims-based analysis found that the presence of multiple modifiable risk factors was associated with higher odds of 90-day surgical site infection and venous thromboembolism and of 30-day readmission after total joint arthroplasty, with the threshold being two or more risk factors for surgical site infection after total hip arthroplasty and three or more for total knee arthroplasty [5]. These associations suggest a cumulative effect of multiple risk factors on postoperative morbidity, underscoring the case for addressing them collectively rather than in isolation [5].

Preoperative optimisation has therefore emerged as a critical component of contemporary arthroplasty care. The objective of optimisation is not merely to identify contraindications to surgery but to actively modify patient physiology and functional status in the weeks preceding the operation, thereby reducing the magnitude of surgical stress and enhancing recovery capacity [4,6]. Evidence supports targeted interventions for several key domains: better glycaemic control is associated with a lower risk of periprosthetic joint infection; correction of anaemia diminishes transfusion requirements; smoking cessation improves wound healing and reduces pulmonary complications; and nutritional supplementation addresses catabolic vulnerability [3,4,7]. Despite this evidence base, the translation of optimisation principles into routine practice remains inconsistent, particularly in healthcare systems where multidisciplinary infrastructure and dedicated preoperative clinics are not universally available.

The multidisciplinary pathway model represents a structured approach to preoperative care that integrates orthopaedic surgeons, physicians, anaesthesiologists, nurses, physiotherapists, and nutritionists in a coordinated effort to prepare patients for surgery [8]. Such pathways typically encompass standardised risk assessment, targeted medical intervention, patient education, and discharge planning initiated well before the day of admission. In high-income settings, implementation of standardised perioperative pathways for TKA has been associated with reduced length of stay, decreased opioid consumption, and improved discharge disposition [8–11]. However, the applicability of these models to resource-constrained environments requires careful adaptation, particularly regarding the affordability and practicality of recommended interventions.

A particular challenge in the Pakistani context is the absence of robust preoperative risk stratification tools that are both clinically meaningful and economically feasible. Sophisticated frailty indices, comprehensive laboratory panels, and advanced functional assessments may not be routinely accessible in public sector hospitals. There is therefore a need to identify simple, low-cost screening measures that can identify patients at elevated risk of adverse outcomes, thereby enabling targeted allocation of limited optimisation resources. The 30-second Chair Stand Test, a simple measure of lower extremity strength and functional capacity, has been used in geriatric and rehabilitation settings but has received limited attention as a preoperative risk stratification tool in arthroplasty populations [12]. Its administration requires only a standard chair and a stopwatch, making it well suited to resource-limited environments.

The present study was designed to address these gaps by implementing and evaluating a multidisciplinary preoperative optimisation pathway

 tailored to the context of a tertiary care hospital in Faisalabad, Pakistan. The pathway incorporated evidence-based interventions for modifiable medical risk factors alongside a simple functional screening test. We hypothesised that patients managed through this structured pathway would experience fewer perioperative medical complications and shorter hospital stays compared with those receiving standard preoperative care. The findings are intended to inform the development of feasible, context-appropriate optimisation protocols for arthroplasty services in similar resource-constrained settings.

Study Design and Setting

This prospective, non-randomised, sequential-allocation interventional study was conducted in the Department of Orthopaedic Surgery, Allied Hospital 1, Faisalabad, Pakistan, over a six-month period from January 2026 to June 2026. The hospital is a major tertiary care centre serving a large catchment area in the Punjab province. The study was approved by the Institutional Review Board and Ethics Committee of Allied Hospital 1, Faisalabad. Written informed consent was obtained from all participants prior to enrolment.

Study Population

Consecutive patients aged 45 to 75 years scheduled for primary unilateral total knee arthroplasty for end-stage knee osteoarthritis were screened for eligibility. Exclusion criteria included: revision arthroplasty, bilateral procedures, active infection at the time of assessment, severe cardiac or pulmonary disease precluding surgery (ASA class IV or above), cognitive impairment preventing informed consent, and refusal to participate. A total of 138 patients were assessed for eligibility, of whom 120 met inclusion criteria and were enrolled.

Allocation to Study Groups

Patients were allocated to the Standard Care Group (n=60) or the Optimisation Pathway Group (n=60) according to the date of their scheduled preoperative assessment. Patients assessed during the first three months (January–March 2026) received standard care, while those assessed during the subsequent three months (April–June 2026) were enrolled in the optimisation pathway. Because the pathway began 4–6 weeks before surgery, the operations and 30-day follow-up of pathway patients extended beyond the end of recruitment. This sequential allocation design was adopted to ensure that pathway infrastructure and staff training were fully established before implementation, and to avoid contamination between groups that could occur with concurrent allocation. Allocation was not randomised and neither patients nor assessors were blinded.

Standard Care Group

Patients in the standard care group received the department's usual preoperative preparation. This comprised a routine history and physical examination, baseline laboratory investigations including complete blood count, serum creatinine, fasting blood glucose, and coagulation profile, and anaesthesia consultation. Medical comorbidities were noted, and specialist referral was arranged at the discretion of the treating surgeon if significant abnormalities were identified. No structured protocol for optimisation of modifiable risk factors was applied. Patients received general preoperative advice regarding medication management but no dedicated counselling or targeted interventions.

Optimisation Pathway Group

The multidisciplinary optimisation pathway was developed collaboratively by the Departments of Orthopaedic Surgery, Internal Medicine, Anaesthesiology, and Physiotherapy. The pathway comprised the following components:

Preoperative Medical Assessment and Targeted Intervention (Weeks 4–6 before surgery): All patients underwent a structured medical assessment by a designated internal medicine physician. Modifiable risk factors were systematically identified and addressed according to predefined protocols:

Glycaemic Control: Patients with diabetes mellitus (HbA1c >7.0%) were referred for intensification of therapy under medical supervision, with a target HbA1c of ≤7.5% before surgery where achievable within the available timeframe. Capillary blood glucose was monitored and optimised in the immediate preoperative period.

Anaemia Management: Patients with preoperative haemoglobin below 11 g/dL were investigated for cause. Iron deficiency anaemia was treated with oral iron supplementation (ferrous sulphate 200 mg twice daily) or intravenous iron where oral therapy was not tolerated or time was insufficient. The target was haemoglobin ≥11 g/dL at the time of surgery.

Smoking Cessation: Current smokers received structured brief counselling based on the 5A model and were offered nicotine replacement therapy where available. The importance of cessation for wound healing and pulmonary outcomes was emphasised.

Nutritional Assessment: Body mass index was recorded, and patients with BMI <18.5 kg/m² or clinical signs of malnutrition received dietary counselling and oral nutritional supplementation where feasible.

Functional Screening (Week 4 before surgery): The 30-second Chair Stand Test was administered by a trained physiotherapist. Patients were instructed to sit in a standard armless chair with feet flat on the floor and arms crossed over the chest, and to stand up and sit down as many times as possible within 30 seconds. The number of completed stands was recorded. Patients achieving fewer than 8 stands were classified as having poor functional reserve and were referred for a structured home-based prehabilitation programme comprising simple strengthening and mobility exercises. Baseline chair stand scores were also recorded for the standard care group (Table 1); referral to prehabilitation applied to the pathway group only.

Patient Education (Weeks 2–4 before surgery): A group education session was conducted by a nurse and physiotherapist, covering expectations regarding surgery and recovery, early mobilisation protocols, pain management strategies, and discharge planning. Written materials in Urdu were provided.

Anaesthesia Review and Optimisation (Week 2 before surgery): A consultant anaesthesiologist reviewed all patients in the pathway group to optimise medical status for anaesthesia and to plan the anaesthetic approach, with a preference for spinal anaesthesia where not contraindicated.

Outcome Measures

The primary outcome was the incidence of any perioperative medical complication occurring within 30 days of surgery. Complications were defined as: uncontrolled hyperglycaemia (blood glucose >250 mg/dL requiring acute intervention), symptomatic anaemia requiring blood transfusion, surgical site infection (superficial or deep, according to CDC criteria), venous thromboembolism (deep vein thrombosis or pulmonary embolism confirmed on imaging), acute kidney injury (serum creatinine increase ≥0.3 mg/dL from baseline), respiratory complications (pneumonia, atelectasis requiring intervention), and cardiac events (arrhythmia, myocardial infarction, or decompensated heart failure).

Secondary outcomes included: length of hospital stay (days from surgery to discharge), blood transfusion requirement (proportion transfused and number of units), time to first mobilisation (hours from surgery to first assisted standing), and discharge disposition (discharge directly home versus to a rehabilitation facility or with extended support). Surgical site infection was a component of the primary composite outcome and is reported individually in Table 2.

Statistical Analysis

Data were analysed using SPSS version 26.0. Continuous variables were expressed as mean ± standard deviation and compared using independent samples t-tests or Mann-Whitney U tests as appropriate. Categorical variables were expressed as frequencies and percentages and compared using chi-square tests, or Fisher's exact tests where any expected cell count was less than five. The relative risk with 95% confidence interval was calculated for the primary outcome. A two-sided p-value of <0.05 was considered statistically significant. No adjustment was made for multiple comparisons or for potential confounders, and the individual complication analyses should be regarded as exploratory.

A total of 120 patients were enrolled, with 60 patients in each group. Baseline characteristics were comparable between groups, as summarised in Table 1.

Table 1: Baseline Demographic and Clinical Characteristics

Table 1 Explanation: This table presents the baseline demographic and clinical characteristics of the two study groups. The groups were similar with respect to age, gender distribution, body mass index, and the prevalence of diabetes mellitus and hypertension. Mean preoperative haemoglobin was nearly identical between groups, ASA class distribution was comparable, and baseline chair stand performance did not differ. Baseline similarity on these measured variables is reassuring, but because allocation was sequential rather than randomised, it does not exclude unmeasured differences between the two periods.

Table 2: Primary Outcome – Perioperative Medical Complications Within 30 Days

*Fisher's exact test (expected cell count <5); other comparisons by chi-square test. Patients could have more than one complication; percentages do not sum to the "any complication" row.

Table 2 Explanation: This table details the incidence of individual perioperative medical complications in each group. The overall complication rate was lower in the optimisation group (15.0% versus 33.3%; relative risk 0.45, 95% CI 0.22–0.91; p=0.019), a relative reduction of more than half. The largest differences were in metabolic and haematological complications: uncontrolled hyperglycaemia occurred in 5.0% of optimised patients compared with 18.3% of standard care patients (p=0.023), and transfusion-requiring anaemia in 8.3% versus 21.7% (p=0.041). Expressed per diabetic patient (assuming all events occurred in diabetic patients), hyperglycaemia occurred in 3 of 28 (10.7%) versus 11 of 25 (44.0%; Fisher's exact p=0.011). Surgical site infection rates were numerically lower in the optimisation group (3.3% vs. 8.3%) but this was not statistically significant, and the study was not powered to detect differences in these less frequent events. Venous thromboembolism, acute kidney injury, respiratory complications and cardiac events were also numerically lower but none differed significantly. As a sensitivity check, Fisher's exact test applied to every comparison gave p=0.032 for any complication and p=0.043 for hyperglycaemia, but p=0.071 for transfusion, so the transfusion finding should be regarded as borderline. The direction of effect was the same for every complication category, although this does not by itself establish that the pathway caused the difference. Individual events totalled 14 (in 9 patients) in the optimisation group and 40 (in 20 patients) in the standard care group, so some patients had more than one complication.

Table 3: Secondary Outcomes – Length of Stay, Transfusion, and Mobilisation

Table 3 Explanation: This table presents the secondary outcomes. Mean length of hospital stay was shorter in the optimisation group by approximately 1.4 days (4.2 versus 5.6 days, p<0.001). The proportion of patients requiring transfusion was lower (21.7% to 8.3%, p=0.041; see the sensitivity analysis above). Among transfused patients (5 versus 13), the mean number of units did not differ significantly (p=0.206, Welch t-test), and the numbers are too small for conclusions about transfusion severity. Time to first mobilisation was shorter in the optimisation group (18.6 versus 24.3 hours, p<0.001), which may reflect better physiological status and the preoperative education and physiotherapy input, although the study cannot separate these. A higher proportion of optimised patients were discharged directly home (90.0% vs. 76.7%), a difference at the margin of conventional significance (p=0.050; Fisher's exact p=0.085).

Table 4: Chair Stand Test Performance and Association with Outcomes (all 120 patients pooled)

Table 4 Explanation: This table examines the relationship between preoperative functional reserve, assessed by the 30-second Chair Stand Test, and postoperative outcomes across the pooled cohort. Patients achieving fewer than 8 repetitions had a longer mean length of stay (5.4 versus 4.5 days, p=0.005) and a higher overall complication rate (37.5% versus 15.3%, p=0.005) than those achieving 8 or more. The transfusion rate was numerically higher in the poor reserve group but not significantly so. This is an exploratory, unadjusted association. Patients with poor reserve in the pathway group received prehabilitation, whereas those in the standard care group did not, and group allocation itself was associated with outcome, so the pooled analysis is confounded. Stratified or multivariable analyses and measures of discrimination, such as ROC analysis, were not performed. The test takes under a minute and requires only a chair and a stopwatch, which makes it attractive for resource-limited settings, but the present data do not validate it as a risk stratification tool.

Figure 1: Comparison of Overall Complication Rates and Individual Complication Categories Between Groups

Figure 1 Explanation: This clustered bar chart illustrates the incidence of the primary outcome and individual complication categories in the two groups. The direction of difference favoured the optimisation pathway in all categories. The largest absolute differences were in the metabolic (hyperglycaemia) and haematological (anaemia/transfusion) domains, which were the specific targets of the medical optimisation interventions. This pattern is consistent with, but does not prove, a mechanistic effect of the pathway. Infectious, thromboembolic, renal, respiratory and cardiac complications were less frequent overall and the differences were small in absolute terms.

Figure 2: Length of Stay Distribution by Study Group

Figure 2 Explanation: This histogram illustrates the shift toward earlier discharge in the optimisation group. The modal length of stay was 4 days in the optimisation group compared with 5 days in the standard care group. The standard care group had a longer right tail, with 24 patients (40.0%) staying 6 days or longer compared with 5 patients (8.3%) in the optimisation group. The majority of optimised patients (47 of 60) were discharged within 4 to 5 days.

The present study found that a structured multidisciplinary preoperative optimisation pathway was associated with fewer perioperative medical complications and a shorter hospital stay in patients undergoing primary TKA at a tertiary care hospital in Faisalabad, Pakistan. The overall complication rate was 15.0% in the optimisation group compared with 33.3% in the standard care group, a difference that is statistically significant and of potentially important clinical size. These findings add to the growing body of evidence supporting preoperative optimisation as

a component of arthroplasty care and suggest that such an approach is feasible in a resource-limited setting [8,13]. Because allocation was sequential and not randomised, the results show association rather than proven causation.

The lower rate of uncontrolled perioperative hyperglycaemia observed in this study (5.0% vs. 18.3%) aligns with existing evidence regarding the importance of glycaemic control in arthroplasty outcomes. Diabetes mellitus is highly prevalent among patients undergoing TKA, and poor glycaemic control has been consistently associated with increased risks of periprosthetic joint infection, wound complications, and prolonged hospitalisation [3,4]. The mechanism linking hyperglycaemia to adverse outcomes is multifactorial, encompassing impaired neutrophil function, reduced wound healing capacity, and increased susceptibility to infection. In our pathway, patients with elevated HbA1c were referred for intensification of therapy under medical supervision, with the goal of achieving reasonable glycaemic control before surgery. We did not record HbA1c at the time of surgery, so we cannot confirm that the lower hyperglycaemia rate resulted from better preoperative control rather than from closer perioperative glucose monitoring. This finding is relevant in the Pakistani context, where diabetes prevalence is high and many patients present with suboptimal glycaemic control at the time of surgical referral [14].

The lower transfusion rate (8.3% vs. 21.7%) is another notable outcome, although it was of borderline robustness (p=0.041 by chi-square, p=0.071 by Fisher's exact test). Preoperative anaemia is a well-recognised and modifiable risk factor for perioperative transfusion, which itself carries risks including transfusion-related reactions, immunomodulation, and increased healthcare costs [4,6]. Our protocol incorporated systematic screening for anaemia and targeted treatment with oral or intravenous iron as appropriate. The result is consistent with evidence from enhanced recovery programmes that emphasise preoperative haemoglobin optimisation [10]. We did not record haemoglobin at the time of surgery or the transfusion trigger used in each period, both of which would be needed to attribute the difference to anaemia correction. The mean number of units given to transfused patients did not differ significantly (p=0.206) and the numbers were small, so no conclusion can be drawn about the severity of transfusion need.

The reduction in length of stay by approximately 1.4 days in the optimisation group has potentially substantial implications for healthcare delivery in Pakistan. Bed capacity is a perennial constraint in public sector hospitals, and a shorter length of stay could increase throughput and improve access for other patients awaiting surgery. The mechanisms are likely multifactorial. Improved glycaemic control and correction of anaemia may reduce postoperative complications that prolong hospitalisation. Preoperative patient education and expectation management may facilitate earlier mobilisation and discharge planning. Additionally, the functional screening and prehabilitation component may have enhanced physical readiness for early ambulation. The shorter time to first mobilisation (18.6 vs. 24.3 hours) is compatible with this interpretation, as early mobilisation is a key determinant of discharge readiness following TKA [10]. These explanations remain hypotheses, as the study was not designed to separate the contribution of individual pathway components.

The 30-second Chair Stand Test appears to be a promising addition to preoperative assessment. Patients achieving fewer than 8 repetitions had longer hospital stays and higher complication rates. This finding is consistent with the broader literature on frailty and functional reserve as determinants of surgical outcomes [15]. The analysis was unadjusted and pooled across groups, so we cannot say that the association is independent of age, comorbidity or group allocation, and the cut-off of 8 was not validated against an independent sample. The chair stand test offers practical advantages over more complex frailty assessments: it requires only a chair and a stopwatch, can be administered by any trained staff member in under one minute, adds little cost beyond staff time, and is easily understood by patients. In the context of a resource-constrained healthcare system, simple tools of this kind are valuable for identifying patients who may benefit from more intensive optimisation or alternative care pathways. The test also has the advantage of being a performance-based measure rather than a self-reported instrument, reducing the potential for recall bias or overestimation of functional capacity.

The multidisciplinary structure of the pathway may have contributed to its effect, although the study did not test this. The involvement of internal medicine physicians ensured that medical comorbidities were systematically addressed rather than managed reactively. The role of the physiotherapist extended beyond the traditional postoperative domain to include preoperative functional assessment and prehabilitation prescription. Nursing staff contributed to patient education and expectation setting, which are increasingly recognised as important determinants of patient satisfaction and recovery trajectory [8]. Anaesthesiology input facilitated optimisation of the anaesthetic plan, with a preference for spinal anaesthesia where appropriate; spinal anaesthesia has been associated with fewer complications than general anaesthesia in lower limb arthroplasty [16], but we did not record or compare anaesthetic technique between groups, so it may be a confounder. This collaborative model aligns with the concept of the multidisciplinary team as the cornerstone of effective perioperative care [8].

It is important to acknowledge the limitations of this study. First, the sequential allocation design, while pragmatic, is not equivalent to randomisation and is vulnerable to temporal bias. Patients operated in the later period may have benefited from general improvements in care, institutional learning, or changes in surgical, anaesthetic or transfusion practice that were independent of the pathway. No adjustment for confounders was made. Second, no sample size calculation was performed, and with 120 patients the study had limited power to detect differences in less frequent outcomes such as surgical site infection and venous thromboembolism; the individual complication comparisons were also not corrected for multiple testing. Third, neither participants nor outcome assessors were blinded. Fourth, we did not measure whether the interventions achieved their physiological targets (HbA1c, haemoglobin at surgery) or how many patients received each intervention, so the mechanism cannot be confirmed. Fifth, the nutritional assessment was limited to BMI and clinical signs, which may miss malnutrition in overweight patients (mean BMI was about 30 kg/m²). Sixth, follow-up was limited to 30 days, which captures most acute perioperative complications but not late periprosthetic joint infection, implant survivorship, or functional outcomes at 6 or 12 months. Seventh, the operating surgeons, implants, anaesthetic technique and transfusion triggers in each period, baseline HbA1c, the number of anaemic patients and serum albumin were not reported, and the anaemia threshold used (haemoglobin below 11 g/dL) was lower than the WHO sex-specific definitions (below 12 g/dL in women and below 13 g/dL in men), so some anaemic patients may not have been treated. Finally, the study was conducted at a single institution, and the findings may not be generalisable to other settings with different patient populations, resource availability, or healthcare infrastructure.

The generalisability of these findings to other resource-limited settings merits consideration. The interventions in this pathway were selected for their feasibility and low cost: oral iron supplementation rather than erythropoietin, structured counselling rather than formal smoking cessation programmes, and a simple chair stand test rather than sophisticated frailty indices. These choices reflect the realities of practice in many public sector hospitals in Pakistan and comparable settings. The pathway did, however, require additional physician, physiotherapist, nurse and anaesthesiologist time, and we did not measure costs. Whether the benefits were achieved without substantial additional expenditure therefore remains to be shown by a formal economic evaluation. If confirmed, the results would suggest that quality improvement in surgical care need not depend solely on technological or pharmaceutical innovation but can also come from systematic process redesign [6].

The findings also resonate with the broader literature on preoperative optimisation while highlighting some nuances. A retrospective cohort study from a single academic centre (Dlott and colleagues) compared 1,548 patients who received preoperative optimisation with 1,200 who received standard care. It found that the programme did not consistently improve outcomes, with no significant benefit in several subgroups defined by race/ethnicity and insurance status and no significant overall change in length of stay [17]. That result differs from ours and underscores the importance of tailored optimisation strategies that address not only clinical risk factors but also social determinants of health. In our cohort, we did not systematically collect data on socioeconomic status, health literacy, or social support, which may have influenced outcomes. Future iterations of the pathway should consider incorporating social work involvement and screening for barriers to discharge planning.

Weight management deserves specific comment. While obesity is a recognised risk factor for adverse outcomes following TKA, recent evidence has challenged the assumption that preoperative weight loss necessarily improves surgical outcomes. A large cohort study by Seward and colleagues found that weight loss before TKA was not associated with reduced postoperative risks [18]. This supports a patient-centred approach that avoids rigid BMI cut-offs and focuses on achievable, sustainable improvements in metabolic health. Our pathway had no weight-loss component and emphasised glycaemic control and overall nutritional status; obesity itself was therefore not specifically addressed [7,18].

The role of prehabilitation, while conceptually appealing, remains incompletely defined in the TKA literature. A recent overview of systematic reviews and meta-analyses of randomised trials has examined the effects of structured prehabilitation on postoperative outcomes after total hip and knee arthroplasty [19]. In our study, the prehabilitation component was limited to a home-based programme for patients identified as having poor functional reserve, and we did not separately analyse its contribution to the overall effect. The association between chair stand performance and outcomes suggests that functional reserve may be a meaningful determinant of recovery, but whether it can be modified by preoperative exercise in the time available before surgery requires further investigation. A randomised trial protocol by Halmenschlager and colleagues is investigating the effects of home-based prehabilitation on biomarkers and hospital outcomes, which may provide valuable insights in this regard [20].

The findings also have implications for the organisation of arthroplasty services in Pakistan. The demand for TKA is likely to increase substantially in the coming years as the population ages and expectations regarding quality of life rise. Meeting this demand will require not only increased surgical capacity but also systems to ensure that patients are adequately prepared for surgery. A preoperative optimisation pathway, even a relatively simple one, can serve as a platform for systematic risk assessment and targeted intervention. The chair stand test is an attractive candidate for routine preoperative assessment in this context, as it requires minimal training and no equipment beyond a standard chair and a timing device.

Future research should include a randomised controlled trial to confirm these findings and eliminate temporal bias, with a pre-specified sample size and outcome assessors blinded to group. Longer follow-up is needed to assess the impact of optimisation on implant survivorship and late complications. The cost-effectiveness of the pathway should be formally evaluated, including the costs of preoperative interventions versus the savings from reduced complications and shorter hospital stays. The chair stand test should be validated prospectively, including its discrimination and the optimal cut-off. Finally, the pathway should be adapted and validated in other centres across Pakistan and in comparable low- and middle-income countries, with attention to local resource availability and patient characteristics.

In this prospective, non-randomised, sequential-allocation study, a structured multidisciplinary preoperative optimisation pathway was associated with fewer perioperative medical complications and a shorter length of hospital stay in patients undergoing primary total knee arthroplasty at a tertiary care hospital in Faisalabad, Pakistan. The lower transfusion rate was of borderline robustness. The 30-second Chair Stand Test, a simple and inexpensive functional screening measure, was associated with longer stay and more complications and merits prospective validation as a risk stratification tool. The pathway appears feasible in a public sector setting, but because of the study design the benefit cannot be attributed to the pathway with certainty, and confirmation in a randomised, adequately powered, multicentre trial with cost analysis is needed.

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