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Orthopaedic Proceedings
Vol. 94-B, Issue SUPP_III | Pages 1 - 1
1 Feb 2012
Al-Arabi Y Deo S Prada S
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Aims

To devise a simple clinical risk classification system for patients undergoing primary total knee arthroplasty (PTKR) to facilitate risk and cost estimation, and aid pre-operative planning.

Methods

We retrospectively reviewed a series of consecutive PTKRs performed by the senior author. A classification system was devised to take account of principal risk factors in PTKR. Four groups were devised: 1) Non complex PTKR (CP0): no local or systemic complicating factors; 2) CPI: Locally complex: Severe or fixed deformity and/or bone loss, previous bony surgery or trauma, or ligamentous instability; 3) CPII Systemic complicating factors: Medical co-morbidity, steroid or immunosuppressant therapy, High BMI, (equivalent to ASA of III or more); 3) CPIII: Combination of local and systemic complicating factors (CPI+CPII). The patients were grouped accordingly and the following were compared: 1) length of stay, 2) post-operative complications, and 3) early post-discharge follow-up assessment. The complications were divided into local (wound problems, DVT, sepsis) and systemic (cardiopulmonary, metabolic, and systemic thromboembolic) complications.


Orthopaedic Proceedings
Vol. 92-B, Issue SUPP_IV | Pages 497 - 498
1 Oct 2010
Nordin L Al-Arabi Y Deo S Vargas-Prada S
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Introduction: Many papers present results and outcomes of patients undergoing TKR or THR, these are often available to the general population and health care community and health care commissioners. These results are used as a standard to be expected by the interested parties. Patients undergoing lower limb arthroplasty fall into groups that can be broadly divided into standard and complex. Complexity can be further subdivided into local site of surgery problems, general co-morbidity problems or both.

We have come up with a 4-part stratification based on the patient’s primary condition and comorbidities and have evaluated this for a single-surgeon cohort of TKR patients and a multi-surgeon group of THR patients. We present the results and the implications of the findings and highlight the usability of the system.

Methods: Retrospective review of patient’s notes and radiographs recording lenght of stay, early post operative complications, demographic data, medical co-morbidities and local site of surgery issues. This information was used to stratify patients into 4 groups. Complex Primary 0 -standard joint replacement in a fit patient with simple pattern arthritis, Complex Primary I -a fit patient with locally complex arthritis, Complex Primary II -medically unfit patient with simple arthritis and Complex Primary III -medically unfit patient with complex pattern arthritis. We evaluated this for a single-surgeon cohort of TKR patients and a multi-surgeon group of THR patients, a total of 250 patients.

Results: The complication rates between the four groups were analyzed using logistic regression analysis and this revealed a highly significant trend among the four groups (p< 0.0001). Lenght of stay data was analyzed using non-parametric analysis of variance. This revealed a significantly increased lenght of stay in the CI and CII groups compared to the C0 group. Compared to CP0 patients, we found a 3-fold increase in cumulative complication risk in the CPII group, a 4-fold increase in the CPIII group. There were similar trends between CP0 and CPI and between CPI and CPII.

Discussion and Conclusion: This classification system correlates and quantifies increasing primary joint replacement complexity with increasing postoperative complication rates and length of stay. It is of use in stratifying patients for preoperative planning, risk counselling, and surgeon selection. These noted increases mean that this system can identify patient groups likely to incur greater cost during their treatment. It is potentially reproducible and usable for other types of surgery and can be applied to larger patient groups via institutional or national joint registries.


Orthopaedic Proceedings
Vol. 90-B, Issue SUPP_III | Pages 573 - 573
1 Aug 2008
Deo S Al-Arabi Y Vargas-Prada S
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We have previously noted that patients undergoing primary knee arthroplasty can be broadly divided into standard and complex. Complexity can be further subdivided into local site of surgery issues, general co-morbidity problems or both.

On this basis, we devised a simple to apply four-part classification system for patients undergoing primary total knee replacecments (PTKR) to facilitate cumulative risk estimation:

Complex 0 (C0): “Standard” knee replacement in a fit patient with a simple pattern of arthritis.

Complex I (CI): A fit patient with a locally complex arthritis pattern.

Complex II (CII): Medically unfit patient with a simple pattern of arthritis.

Complex III (CIII): Medically unfit patient with a complex arthritis pattern.

When a series of consecutive PTKR’s performed by the senior author was grouped according to our classification, all early postoperative complications and length of stay were evaluated and compared.

Compared to “standard C0 PTKR patients, we found a 3-fold increase in the cumulative complication risk in the CII group (p< 0.001), a 4-fold increase in the CIII group (p< 0.001) and an increased length of stay in the CIII group (p< 0.001). There were similar trends between C0 and other groups.

Further local studies to quantify the cost differentials of treating complex patients and their longer term outcomes and satisfaction are underway.

The senior author would like to discuss with the attending members of this BASK meeting the desirability of adopting such a system regionally or nationally, with the potential benefits for individual patients, surgeons, departments, Trusts and the healthcare system as a whole, and whether minor changes could and should be made to the National Joint Registry forms to accommodate this.