Patient controlled analgesia (PCA) is commonly used after TKR. Prolonged use of PCA may however have a negative impact on patients delaying their rehabilitation and therefore discharge. We aimed to evaluate the effect of the duration of PCA on the hospital length of stay (LOS) in patients who undergo TKR. We reviewed the casenotes of all patients who underwent a primary TKR in two South Australian teaching hospitals between 2006 and 2007. After excluding patients whose LOS was determined by placement issues and patients who developed intra-hospital post-operative complications, a number of 345 patients were included in this study. Data collected included: age, gender, ASA grade, regional blocks used, duration of postoperative PCA (< 24 hours, 24-48 hours, > 48 hours) and hospital LOS. Using SAS Version 9.2 statistical analysis software the data was analysed using univariate and multivariate Poisson regression models. Risk ratios, confidence intervals and P values were calculated. Univariate regression models showed that there was a significant difference in length of stay between the three PCA groups (p < 0.0001). Post hoc tests revealed that the length of stay was longer in the 24 to 48 hours and > 48 hours groups compared to the < 24 hours group (p < 0.0001). There was also a significant difference in hospital LOS between males and females (p = 0.0049) with females expected to stay on average 9.7% longer (risk ratio = 1.097, 95% CI 1.028, 1.169). Patients in the ASA categories (1 and 2) recorded shorter lengths of stay than patients in the ASA categories (3 and 4) (p < 0.0001). Also patients treated at one hospital had longer LOS than the patients treated at the other hospital (risk ratio = 1.122, p = 0.0001). There was no evidence for a relationship between the patients' ages, and use or type of regional block used and the hospital LOS. Results from the multivariate regression models showed that each of the four variables found to influence LOS significantly, did so independent of the other variables. Therefore, duration of PCA, gender, ASA and hospital were all independent predictors of hospital LOS after primary TKR. Longer administration of PCA, higher ASA grades and female gender are associated with longer hospital LOS after TKR. Reducing postoperative PCA, as well as improving ASA grading, could reduce LOS in these patients. A multimodal pain management strategy that shortens PCA use could reduce hospital LOS and costs after TKR.
Treatment strategies for the management of proximal humeral fractures are assisted by an understanding of the fracture morphology and, in particular, the viability of the humeral head. Although widely accepted, the AO and Neer classification systems show poor interobserver reproducibility and generally do not provide a basis to guide treatment. The aim of this study was to compare the interobserver and intraobserver reliability of a new classification system with the AO and Neer classifications and review its usefulness as a guide to management. Hertel described a comprehensive binary (Lego) classification system, which defines fracture planes and parts, as well as incorporating calcar length, attachment and angulation. This facilitates predicting humeral head ischemia; however the sequential numerical form of the classification makes it complex and prone to categorisation error. Sandow has extended this to a more descriptive system by naming proximal humeral parts (H-head, G-greater tuberosity, L-lesser tuberosity, S-shaft), recording the fracture plane and optionally incorporating calcar length and head angulation or displacement. 50 proximal humeral fractures in 50 patients treated at the Department of Orthopaedics and Trauma, Royal Adelaide Hospital, were identified from the period of July 2007 to January 2008. All fractures of the proximal humerus were examined using AP, lateral and axial radiographs. Three independent reviewers classified the fractures using the AO, Neer and “HGLS Classification”. The findings were analysed specifically for intra/interobserver correlation and the indications for humeral head viability. The median age of patients was 72 (range 50 to 85). Based on the interobserver correlation analysis, the AO and Neer Classification systems were graded as poor. The ‘HGLS’ Classification showed good interobserver agreement for all three examiners and more consistently provided guidelines for management based on humeral head viability. While the parts system of Neer can still provide a general impression of the fracture form, the “HGLS classification” for proximal humeral fractures provided a more precise description of the fracture pattern which has important prognostic and therapeutic implications. It is quick to apply and easy to use as it does not require memorisation of a numerical classification and can help to understand fracture patterns and thus aid planning of a reduction and fixation strategy. Good interobserver correlation makes it a useful tool for communication between surgeons.
