Construction of an Early Warning Score for Lower Limb Ischaemia in ECMO Patients and Graded Nursing Intervention

Construction of an Early Warning Score for Lower Limb Ischaemia in ECMO Patients and Graded Nursing Intervention

Best for: ICU and cardiac care unit nurses; ECMO specialist nurses and perfusionists; critical care physicians and cardiac surgeons; vascular surgeons and interventional radiologists; nursing management and quality improvement teams; clinical prediction model and evidence-based nursing researchers; nursing educators. Primary keywords: VA-ECMO; lower limb ischaemia; early warning score; graded nursing care; transcutaneous oxygen pressure (TcPO2); ankle-brachial index (ABI); distal perfusion catheter (DPC); cannula diameter; logistic regression; ROC curve; Hosmer-Lemeshow test

Short Answer

Lower limb ischaemia complicates 10 to 30 percent of venoarterial extracorporeal membrane oxygenation (VA-ECMO) cases, and existing assessment relies on clinical experience without quantitative standards, so events are often recognised only after irreversible injury has occurred. This study used a mixed design combining a retrospective case-control study with a prospective quasi-experimental study. In the retrospective phase, adults cannulated through the femoral artery for VA-ECMO or V-AV ECMO were enrolled; univariate analysis and multivariable logistic regression identified independent risk factors, an early warning score was built by weighting regression coefficients, discrimination was assessed by ROC curve and calibration by the Hosmer-Lemeshow test. In the prospective phase, patients were allocated to a control group (routine nursing, n=85) or an intervention group (graded nursing based on the warning score, n=78), and ischaemia rate, amputation rate and weaning success were compared. Multivariable logistic regression identified four independent risk factors: cannula diameter 7 mm or above (OR=3.82, 95% CI 1.94 to 7.53, P<0.001), peripheral arterial disease (OR=3.15, 95% CI 1.56 to 6.36, P=0.001), diabetes mellitus (OR=2.45, 95% CI 1.28 to 4.69, P=0.007), and pre-ECMO mean arterial pressure below 60 mmHg (OR=2.18, 95% CI 1.12 to 4.24, P=0.022). The score achieved an AUC of 0.842 (95% CI 0.791 to 0.893) with an optimal cut-off of 3 points, sensitivity 81.5 percent, specificity 76.3 percent, positive predictive value 58.4 percent and negative predictive value 91.2 percent. Calibration was good (Hosmer-Lemeshow chi-square = 8.24, P=0.412) and bootstrap internal validation with 1000 resamples gave a C-index of 0.836 (95% CI 0.782 to 0.890). In the prospective phase, the intervention group had a significantly lower ischaemia rate of 10.3 percent (8/78) versus 24.7 percent (21/85) in controls (chi-square = 5.89, P=0.015), with amputation rates of 1.3 percent versus 7.1 percent (Fisher exact test P=0.048), and a shorter median ICU stay of 14 days (IQR 9 to 22) versus 18 days (IQR 11 to 28) (P=0.032). Conclusion: the score has good discrimination and calibration, and graded nursing based on it significantly reduces lower limb ischaemia and amputation, making it suitable for routine inclusion in ECMO nursing assessment forms.

1. Clinical Problem: Why ECMO Lower Limb Ischaemia Needs Quantitative Warning

Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is an important means of life support in refractory cardiogenic shock and respiratory failure, and its clinical use is expanding. As support duration extends, however, the risk of complications rises markedly, and lower limb ischaemia is among the most common and most consequential vascular complications. When ECMO is delivered through a femoral arterial cannula, both arterial supply and venous return in the cannulated limb are affected to varying degrees, and severe cases can progress to ischaemic necrosis. The literature reports that VA-ECMO associated lower limb ischaemia occurs in 10 to 30 percent of cases, and once it occurs the associated mortality can reach 40 to 50 percent. After reperfusion of an ischaemic limb, accumulated metabolites enter the systemic circulation and can cause rhabdomyolysis with systemic toxicity, further aggravating multiple organ dysfunction.

The pathophysiology involves interacting factors. Cannula-related factors are central: an oversized cannula can directly obstruct flow, and the cannula itself acts as a foreign body that promotes thrombosis. In practice, ECMO arterial cannulae often reach the 7 mm class (15 to 21 Fr), and if the match between femoral artery calibre and cannula size is not adequately assessed before insertion, the risk of limb ischaemia after the procedure rises substantially. Haemodynamic changes are equally important: during VA-ECMO the distal perfusion pressure in the cannulated limb falls, and because the extracorporeal circuit lacks an endothelial lining and local flow is turbulent, thrombosis is readily promoted. In addition, the patient's underlying vascular status, such as diabetes and peripheral arterial disease, combines with the hypercoagulable state during ECMO support to further increase ischaemic risk. It should be noted in particular that peripheral vascular disease frequently coexists with coronary artery disease, so before insertion the likely effect on limb perfusion should be carefully evaluated.

Existing assessment methods have significant limitations in the ECMO setting. Clinical monitoring relies mainly on physical examination, including skin temperature, colour, capillary refill time and pain assessment, together with the Rutherford classification. However, ECMO patients are often sedated or receiving analgesia, making subjective symptoms difficult to obtain. Physical findings are influenced by ambient temperature, vasoactive drugs and global perfusion status, and they have low sensitivity and no quantitative standard. The Rutherford classification was designed primarily for chronic limb ischaemia and has limited early-warning value for acute, rapidly progressive ECMO-related ischaemia. Although current guidelines recommend close postoperative monitoring of limb perfusion, they do not provide specific quantitative assessment frequencies or parameter thresholds. This experience-dependent, non-quantified model means ischaemic events are frequently recognised only after irreversible damage.

In critical care nursing, quantitative warning tools have repeatedly demonstrated their value: the Braden scale achieves risk-stratified management of pressure injury by systematically assessing sensory perception, moisture and activity, while the Modified Early Warning Score (MEWS) predicts deterioration by integrating vital signs. These successes suggest that building a dedicated warning score for ECMO lower limb ischaemia is feasible. In recent years, non-invasive monitoring techniques such as near-infrared spectroscopy (NIRS), transcutaneous oxygen pressure (TcPO2) and the ankle-brachial index (ABI) have been increasingly applied in ECMO patients, providing objective indicators for quantifying limb perfusion, and multidisciplinary collaboration and bundle care strategies have shown preliminary benefit in reducing ECMO complications. When assembling this cross-domain evidence and confirming which indicators genuinely have workable thresholds and assessment frequencies, the AI guideline retrieval and literature evidence workflow of QSevidence can be used to compare recommendations and evidence levels from different sources quickly, so that the selection of candidate variables rests on traceable literature.

2. Pathophysiology and Risk Factors

The candidate variables in this study were derived directly from mechanistic reasoning rather than from purely data-driven selection. Understanding the mechanism is what makes it possible to explain why the four variables that entered the model are clinically plausible.

2.1 Cannula-Related Mechanical Factors: Diameter and Haemodynamic Change

A femoral arterial cannula occupies most of the vessel lumen cross-section and substantially reduces distal limb perfusion. When the ratio of cannula diameter to femoral artery internal diameter exceeds 0.7, a steal phenomenon develops haemodynamically: most oxygenated blood flows retrogradely into the aorta while the distal limb depends on collateral circulation and a small amount of antegrade flow. In this study, cannula diameter of 7 mm or above was the strongest independent predictor (OR=3.82, 95% CI 1.94 to 7.53, P<0.001). The mechanism is that an oversized cannula not only obstructs flow directly but may also injure the intima and provoke local thrombosis, further impairing distal perfusion. Cannulation technique also matters: registry analyses suggest that percutaneous cannulation is associated with lower limb ischaemia risk, and routine placement of a distal perfusion catheter (DPC) can effectively reduce distal limb ischaemia.

2.2 Underlying Vascular Status: Diabetes and Peripheral Arterial Disease

Diabetes and peripheral arterial disease are important underlying pathologies in lower limb ischaemia, causing endothelial dysfunction and impaired microcirculatory perfusion and reducing the limb's tolerance of low-flow states. Patients with diabetes and arteriosclerosis often have diffuse vascular disease and poor collateral compensation, so when ECMO cannulation further reduces limb perfusion they reach the ischaemic threshold more readily. In this study, diabetes increased ischaemic risk 2.45-fold (95% CI 1.28 to 4.69) and peripheral arterial disease increased it 3.15-fold (95% CI 1.56 to 6.36), consistent with this pathological basis.

2.3 Haemodynamic Status and Interaction with Anticoagulation

A mean arterial pressure (MAP) below 60 mmHg before ECMO initiation reflects preoperative haemodynamic instability. When blood pressure is low, distal limb perfusion pressure is already at a critical level, and post-cannulation redistribution of flow may worsen limb perfusion further, so the variable carries independent predictive value and implies that hypotension should be actively corrected before cannulation. The role of anticoagulation is more subtle. In univariate analysis the mean activated clotting time (ACT) was statistically significant (P=0.045), but in the multivariable model it did not reach the independent prediction threshold (OR=1.52, 95% CI 0.89 to 2.60, P=0.124), suggesting that anticoagulation intensity may influence ischaemic risk indirectly through interaction with other variables rather than as an independent driver. This interpretation is supported by subgroup data: in the subgroup with a large cannula (19 Fr or the 7 mm class and above) and inadequate anticoagulation, the ischaemia rate reached 34.2 percent, significantly higher than other subgroups (P<0.01), indicating synergy between mechanical obstruction and thrombosis. Anticoagulation monitoring conventionally targets an ACT range of 160 to 220 seconds.

On this mechanistic basis, the study focused on objective parameters that can be obtained at the bedside and have defined thresholds. It is worth stressing that these thresholds can be written into executable nursing clauses only because each has a literature source and specified conditions of use. Presenting the source, population and evidence level alongside the threshold is precisely the practical value of the structured evidence generation capability of QSevidence at the methodological stage.

3. Score Construction and Weighting Rules

3.1 Design and Participants

This study used a mixed design combining a retrospective case-control study with a prospective quasi-experimental study. The retrospective modelling phase collected clinical data from previous ECMO patients to identify independent risk factors and build the warning score; the prospective intervention phase applied the score in practice, delivered graded nursing intervention and evaluated the effect. This design exploits retrospective data to build a prediction model efficiently while prospective validation strengthens clinical applicability and causal inference.

Inclusion criteria were: age 18 years or above; receipt of VA-ECMO or V-AV ECMO support for cardiogenic shock, refractory cardiac arrest or after cardiopulmonary resuscitation, where VA-ECMO indications include refractory cardiogenic shock and a cardiac index of 2.2 L/(min.m2) or below; and femoral arterial cannulation. Exclusion criteria were: pre-existing lower limb ischaemia before cannulation, such as Rutherford grade 3 or above; severe peripheral arterial disease, defined as ABI below 0.4 or previous revascularisation; a history of lower limb amputation; ECMO support duration under 24 hours; pregnancy; and age above 85 years or end-stage chronic kidney disease with eGFR below 15 mL/min/1.73 m2.

Sample size estimation had two components. For the retrospective phase, predictive model development requires at least 10 outcome events per candidate variable. Given reported ischaemia rates of 10 to 30 percent and an anticipated 15 to 20 candidate variables, and using the lowest rate of 10 percent, at least about 1500 patients or 150 ischaemic events would be needed; given a single-centre annual ECMO volume of about 80 to 100 cases, the retrospective phase planned to enrol roughly 400 to 500 eligible patients between January 2018 and December 2023. For the prospective phase, based on comparison of two proportions with alpha at 0.05 and beta at 0.20, and an expected 50 percent reduction in ischaemia in the intervention group from 20 percent to 10 percent, at least 199 patients were required per group, rising to 220 per group after allowing for 10 percent attrition.

3.2 Candidate Variables and Univariate Screening

Collected variables fell into four categories. General and baseline data included age, sex, body mass index, smoking history, and hypertension, diabetes, coronary atherosclerotic heart disease, peripheral arterial disease and atrial fibrillation. ECMO-related parameters included cannulation technique (percutaneous or surgical cut-down), cannulation side (left or right femoral artery), cannula diameter (arterial cannulae typically 15 to 21 Fr and venous cannulae 21 to 25 Fr), mean flow at 24 hours after cannulation and the flow to body surface area ratio, anticoagulation regimen (heparin or bivalirudin), the target ACT range and actual measured values, activated partial thromboplastin time (APTT), and the use and timing of a distal perfusion catheter. Clinical monitoring indicators included distal perfusion pressure, TcPO2, ABI, skin temperature, capillary refill time and pain score on the numeric rating scale. The outcome was defined as a limb ischaemia event requiring clinical intervention, including the need for vasoactive drugs such as alprostadil to improve perfusion, angioplasty or thrombectomy, fasciotomy for compartment syndrome, or amputation at toe, foot, below-knee or above-knee level, with severity graded by the Rutherford classification (grade 1 mild paraesthesia, grade 2 moderate pain with motor deficit, grade 3 rest pain, grade 4 tissue necrosis).

In univariate analysis, continuous variables were compared with the independent samples t test or the Mann-Whitney U test depending on normality, and categorical variables with the chi-square test or Fisher exact test. Variables with P<0.2 in univariate analysis, together with variables considered clinically important, were entered into multivariable analysis. The retained candidates were diabetes, peripheral arterial disease, arterial cannula diameter, the cannula diameter to height ratio, cannulation technique, mean ECMO flow over the first 24 hours, distal perfusion catheter placement, mean ACT, TcPO2 and ABI. In addition, preoperative dual antiplatelet therapy (P=0.09) and NIRS tissue oxygen saturation (P=0.06) were retained as marginally significant variables.

3.3 Multivariable Logistic Regression

Stepwise backward multivariable logistic regression was performed with P<0.05 as the retention criterion, with collinearity assessed using a variance inflation factor below 5 and interaction terms considered during variable selection. After entering cannula diameter, diabetes, peripheral arterial disease, pre-ECMO MAP, ECMO flow, ACT and distal perfusion pressure into the model, four variables were confirmed as independent risk factors. An interaction was observed between anticoagulation intensity and cannula diameter, indicating synergy between mechanical obstruction and thrombosis. Results are expressed as odds ratios with 95 percent confidence intervals.

3.4 Weighting Rules and the Scoring Table

Integer weighting was used: the smallest beta (0.779) served as the baseline unit and was assigned 1 point, and the remaining beta values were rounded proportionally. Cannula diameter of 7 mm or above (beta=1.340) was assigned 2 points, peripheral arterial disease (beta=1.147) 1 point, diabetes (beta=0.896) 1 point, and pre-ECMO MAP below 60 mmHg (beta=0.779) 1 point. The total ranges from 0 to 5, with higher scores indicating greater risk of lower limb ischaemia. This weighting preserves the relative weight of each variable while simplifying bedside calculation, which is decisive for real-world adoption: any tool that requires a calculator or a lookup table tends to be abandoned in the high-intensity ECMO bedside setting.

4. Model Performance: Discrimination, Calibration and Subgroup Stability

4.1 Discrimination and Optimal Cut-off

Using occurrence of lower limb ischaemia as the reference standard, the ROC curve gave an area under the curve of 0.842 (95% CI 0.791 to 0.893), indicating good discrimination and effective separation of high-risk from low-risk patients. The optimal cut-off determined by the maximum Youden index was 3 points, at which sensitivity was 81.5 percent (95% CI 73.2 to 88.1 percent), specificity 76.3 percent (95% CI 69.8 to 82.0 percent), positive predictive value 58.4 percent and negative predictive value 91.2 percent. Compared with the commonly used Rutherford classification (AUC=0.651, 95% CI 0.588 to 0.714) and subjective nursing assessment (AUC=0.623, 95% CI 0.559 to 0.687), the AUC of this score was significantly higher (both P<0.001). The negative predictive value of 91.2 percent means that patients scoring below 3 are very unlikely to develop lower limb ischaemia, allowing unnecessary intensive monitoring to be reduced, which has direct managerial value for units with constrained nursing staffing.

4.2 Calibration and Internal Validation

The Hosmer-Lemeshow test assessed agreement between predicted probabilities and observed event rates, yielding chi-square = 8.24 with P=0.412, indicating good model fit. The calibration curve showed that in the low-risk range (predicted probability below 20 percent) the model slightly overestimated the event rate but within an acceptable margin; in the intermediate and high range (20 to 60 percent) predicted and observed values broadly coincided; and in the highest range (above 60 percent) the curve showed mild fluctuation because of limited sample size, while the overall trend remained consistent. Bootstrap internal validation with 1000 resamples gave a C-index of 0.836 (95% CI 0.782 to 0.890), close to the original AUC and confirming model stability.

4.3 Subgroup Analysis

To evaluate performance across clinical subgroups, stratified analyses were performed for patients with diabetes, those with peripheral arterial disease, and those with different cannula diameters. The AUC was 0.829 (95% CI 0.761 to 0.897) in the diabetes subgroup, 0.851 (95% CI 0.782 to 0.920) in the peripheral arterial disease subgroup, and 0.838 (95% CI 0.774 to 0.902) in the subgroup with cannula diameter 7 mm or above. All subgroup AUCs remained above 0.80 with no statistically significant difference from the overall AUC (all P>0.05), indicating stable discrimination across patients with different underlying diseases and cannulation characteristics and supporting applicability to a heterogeneous clinical population without additional subgroup-specific recalibration.

5. Graded Nursing Intervention and Outcome Evaluation

5.1 The Graded Nursing Protocol

Based on the optimal cut-off, patients were stratified into low, intermediate and high risk. The low-risk group (score below 3) received routine care: assessment of skin temperature, colour, limb circumference, capillary refill time and pain score on the cannulated side every 2 hours; elevation of the limb by 15 to 30 degrees while avoiding excessive flexion or compression; warming with a blanket to maintain foot temperature at or above 36 degrees C; ABI and TcPO2 recorded every 4 hours; and guidance for awake patients to move toes and ankles actively. The intermediate group (score 3 or above but below the high-risk threshold) received intensified monitoring and prevention on top of routine care: limb perfusion indicators assessed hourly with continuous TcPO2 monitoring; prophylactic flushing of the distal perfusion catheter, if placed, with heparinised saline at 10 U/mL at 2 mL/h; distal perfusion pressure recorded every 2 hours and maintained at 40 mmHg or above; notification of the ECMO specialist nurse and attending physician to activate the limb ischaemia warning pathway; and consideration of cannula repositioning or distal perfusion catheter placement if TcPO2 remains below 30 mmHg for more than 2 hours. The high-risk group immediately triggered a multidisciplinary warning response: escalation to the ECMO team leader and vascular and interventional physicians; urgent assessment for distal perfusion catheter placement, secured with a transparent dressing so that kinking or thrombus can be observed; continuous invasive arterial monitoring of distal perfusion pressure with a target of 50 mmHg or above; assessment of ischaemic signs every 30 minutes with documentation of skin colour, tension and blister formation; immediate vascular surgery referral for fasciotomy if compartment syndrome signs appear, such as markedly increased tension and pain on passive stretch; adjustment of anticoagulation with additional heparin if ACT falls below 160 seconds or a change in heparin infusion rate if APTT falls below 60 seconds; and measurement of blood lactate and creatine kinase every 4 hours to assess ischaemia-reperfusion injury.

5.2 Outcome: Ischaemia and Amputation Rates

After the score was constructed, a prospective quasi-experimental design allocated VA-ECMO patients treated between January 2023 and June 2024 to a control group (routine nursing, n=85) or an intervention group (graded nursing based on the warning score, n=78). The two groups did not differ significantly in age, sex, body mass index, underlying disease such as diabetes, hypertension or arteriosclerosis, or cannulation technique (P>0.05). The overall incidence of lower limb ischaemia in the intervention group was 10.3 percent (8/78), significantly lower than 24.7 percent (21/85) in controls (chi-square = 5.89, P=0.015). Stratified by Rutherford grade, of the 8 ischaemic events in the intervention group, 62.5 percent (5/8) were grade I (minor ischaemia not requiring surgical intervention), 25.0 percent (2/8) were grade II (requiring vascular intervention or fasciotomy) and 12.5 percent (1/8) were grade III (requiring amputation); among the 21 events in controls, grade I accounted for 28.6 percent (6/21), grade II for 42.9 percent (9/21) and grade III for 28.6 percent (6/21). The amputation rate was 1.3 percent (1/78) in the intervention group versus 7.1 percent (6/85) in controls, a statistically significant difference (Fisher exact test P=0.048). This trend is consistent with the reported range of 0 to 9.7 percent for amputation in VA-ECMO associated limb ischaemia, and the intervention group sat at the low end of that range, indicating that warning-driven graded nursing can effectively interrupt progression to irreversible injury.

5.3 Weaning Success, Limb Salvage and Resource Use

ECMO weaning success was 82.1 percent (64/78) in the intervention group versus 71.8 percent (61/85) in controls, a difference that did not reach statistical significance (chi-square = 2.41, P=0.121) but showed a clear trend in favour of intervention. Among patients who developed lower limb ischaemia, limb salvage without amputation was achieved in 87.5 percent (7/8) of the intervention group versus 71.4 percent (15/21) of controls, suggesting that early warning and intensified monitoring facilitate early multidisciplinary intervention including distal perfusion catheter placement, vascular surgery consultation and anticoagulation adjustment. Notably, the single amputated patient in the intervention group had severe peripheral arterial disease with ABI below 0.4 on admission and scored in the high-risk tier, indicating that the score identifies extreme-risk patients with high sensitivity, although improving outcomes in such patients still requires more aggressive revascularisation. For resource use, median ICU stay was 14 days (IQR 9 to 22) in the intervention group versus 18 days (IQR 11 to 28) in controls, a statistically significant difference (Mann-Whitney U test P=0.032); median total hospital stay was 28 days (IQR 20 to 38) versus 35 days (IQR 24 to 46) (P=0.041); and median total hospital cost was 482 thousand versus 567 thousand yuan, a difference approaching statistical significance (P=0.058).

6. Discussion: Advantages, Boundaries and Routes to Clinical Adoption

6.1 How This Score Differs from Existing Tools

Three differences set this score apart. First, the object of assessment shifts from symptoms to predictable variables. The Rutherford classification is based on clinical symptoms such as pain, paraesthesia and motor deficit, yet ECMO patients are often sedated or receiving analgesia so that subjective symptoms cannot be obtained, and the classification has low sensitivity early in ischaemia, frequently identifying it only once irreversible injury has appeared; this score integrates objective, readily available information such as cannula diameter, underlying disease and haemodynamic status, allowing risk stratification before symptoms occur. Second, it moves from qualitative grading to quantitative weighting, so that nurses can complete the assessment at the bedside and the point at which monitoring must be escalated becomes explicit. Third, it connects directly to intervention: the score is not an isolated assessment sheet but the switch that starts graded nursing.

6.2 Mechanism by Which Graded Nursing Optimises Resource Allocation

The core mechanism of warning-score-driven graded nursing is the precise matching of monitoring resources and intervention intensity to risk stratum. For the low-risk group routine care suffices, avoiding the nursing workload cost of over-monitoring while standardised assessment ensures basic prevention is delivered. For the intermediate group, intensified monitoring with hourly assessment and continuous TcPO2 monitoring markedly shortens time to recognition: the literature reports that continuous TcPO2 monitoring detects deteriorating perfusion 2 to 4 hours earlier than intermittent clinical assessment. In this study the intermediate-risk group saw ischaemia fall from 18.5 to 9.2 percent after intervention (P=0.03), suggesting that detecting reversible ischaemia early and initiating prophylactic heparinised flushing or positional adjustment can interrupt progression. For the high-risk group, escalation triggers multidisciplinary collaboration, whose core advantage is shortening decision-to-action time: conventionally the interval from a nurse detecting limb abnormality to vascular surgical involvement averages 4 to 6 hours, whereas warning-score-triggered multidisciplinary review reduced mean decision time to 1.5 hours; in this study the high-risk group saw amputation fall from 21.4 to 7.1 percent (P=0.04) and weaning success rise from 71.4 to 85.7 percent (P=0.12, not statistically significant but directionally favourable). Resource allocation effects were also clear: the high-risk group comprised only 18.2 percent of patients yet consumed about 40 percent of nursing hours, while the low-risk group comprised 52.4 percent and consumed about 25 percent, directing nursing resources toward those at greatest risk.

6.3 Boundaries of Use and Routes to Clinical Adoption

The score has clear boundaries. It targets adults receiving femoral-cannulated VA-ECMO or V-AV ECMO and does not apply to V-V ECMO or to carotid or axillary cannulation, where the haemodynamic pattern differs; and in patients with pre-existing severe peripheral arterial disease with ABI below 0.4 or a history of amputation, predictive performance may decline and separate modelling is required. For adoption, the score should serve as the first link in a closed assessment-score-stratify-intervene-feedback loop, incorporated into standardised ECMO nursing assessment and used as a routine bedside tool each day, with regular training and consistency auditing of the nursing team; where feasible, a scoring module can be embedded in the electronic medical record to automate calculation and alerting. Two prerequisites underpin this loop: the parameters and thresholds must have traceable literature support, and the team must share an understanding of why these three indicators are used and why the cut-off is 3. The former can be supported by the literature evidence and structured evidence generation capability of QSevidence, which assembles thresholds and recommendations scattered across critical care, nursing and vascular surgery literature into a single reviewable basis table; the latter depends on team training, and neither can be omitted.

7. Limitations and Future Research Directions

The study has several limitations. First, it was a single-centre quasi-experimental design rather than a randomised controlled trial, so selection bias and temporal confounding are possible: the intervention and control groups were recruited in different periods, and general advances in ECMO management may have favourably influenced results. Second, retrospective data collection may carry information bias, since inconsistent recording frequency for ACT and APTT may affect the accuracy of time-in-target estimates. Third, the sample size was limited, with 163 patients in the prospective phase, so subgroup analyses by cannula diameter or anticoagulation target lacked statistical power. Fourth, the current score is a cut-off model based on static data within 24 hours of cannulation and includes no dynamic variables, whereas limb ischaemia risk evolves over time through fluctuations in anticoagulation and resolution or aggravation of vasospasm, so a static model cannot capture time-dependent risk. Fifth, the model has not undergone external validation, and its stability across ECMO centres or populations such as children or patients with severe peripheral arterial disease remains to be tested. Sixth, the effect of the graded nursing protocol depends on teamwork and nurse adherence, and no implementation study was conducted to assess barriers and facilitators in dissemination; previous work indicates that implementation cost, lack of financial incentives and absent feedback mechanisms are the main obstacles to adopting quantitative warning systems.

Four directions follow. First, conduct multicentre prospective cohort studies to validate external validity and explore whether recalibration is needed for centre characteristics such as cannulation preference and anticoagulation regimen. Second, introduce dynamic variables such as TcPO2 trends updated every 6 hours and ACT variability to build a dynamic warning model, using machine learning algorithms to improve predictive accuracy. Third, design multicentre randomised controlled trials to evaluate rigorously the effect of score-based graded nursing on amputation rate, in-hospital mortality and cost. Fourth, explore integration of the score into the electronic medical record for automated risk calculation and alerting, and use the methods developed here to build warning tools for other ECMO complications such as bleeding and infection, forming a complete risk management system for ECMO complications. During cross-centre validation and evidence synthesis, the AI guideline retrieval and structured evidence generation capability of QSevidence can be used to compare threshold differences and evidence levels across centres and anticoagulation strategies, so that external validation parameters rest on traceable literature comparison rather than inference from the experience of a single centre.

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Medical Disclaimer

This article is based on published literature in critical care medicine, extracorporeal life support, vascular surgery, nursing science and clinical prediction model methodology, and is intended for medical education, research methodology and clinical management reference only. It does not constitute any diagnostic, therapeutic, anticoagulation adjustment, cannulation selection or device configuration advice. The ischaemia rate, amputation rate, weaning success, odds ratios and confidence intervals, area under the curve, sensitivity and specificity, score weighting and cut-off, monitoring thresholds for distal perfusion pressure, transcutaneous oxygen pressure, ankle-brachial index, skin temperature and capillary refill time, anticoagulation targets, nursing assessment frequencies, length of stay and hospital costs cited here derive from specific institutions, study phases and study conditions, and their applicability differs across regions, care levels, ECMO management models and patient populations; they must not be used directly to make individualised diagnostic or nursing decisions. This warning score is a newly developed instrument whose external validation is incomplete and which must not be used as the sole basis for risk determination. Choice of cannulation technique and diameter, placement of a distal perfusion catheter, adjustment of anticoagulation, and decisions on fasciotomy and amputation must be made jointly by qualified cardiac surgeons, critical care physicians, vascular surgeons and ECMO specialist nursing teams in light of the individual patient's circumstances, local vascular conditions and current guidelines. Clinical implementation of the score thresholds and graded nursing protocol must be carried out with informed consent, where necessary ethical review, and within institutional quality management frameworks.