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BACKGROUND: Prior open reduction and internal fixation (ORIF) of tibial plateau fracture (TPF) adds complexity to subsequent total knee arthroplasty (TKA). The purpose of this study was to compare the outcomes of patients undergoing a TKA following prior ORIF of TPF to patients undergoing a primary TKA for osteoarthritis and an aseptic revision TKA. METHODS: There were 52 patients who underwent primary TKA following prior ORIF of TPF between January 2009 and June 2021, who were included and matched in a 1:4 ratio by sex, body mass index, and American Society of Anesthesiologists class to 208 patients undergoing primary TKA. A second 1:1 matched comparison to 52 aseptic revision TKA patients was also included. The Knee injury and Osteoarthritis Outcome Score for Joint Replacement scores were obtained preoperatively and at 2-years postoperatively. Independent t-tests and Chi-square tests were used for statistical comparisons. RESULTS: The TPF patients were significantly younger than both the primary and revision cohorts (55 ± 14.0 versus 63 ± 16.3 versus 64 ± 9.5, P < 0.001). Compared to primary TKA patients, the TPF group had worse KOOS JR scores at 2-years (46.9 ± 18.5 versus 66.2 ± 17.8, P = 0.0152), higher rates of wound complications (15.4 versus 3.9%, P = 0.0020), and increased operative times (140.2 ± 45.3 versus 95.2 ± 25.7, P < 0.0001). No significant differences in these metrics were seen between the TPF group and the revision group. Additionally, TPF patients were more likely to require a manipulation under anesthesia (MUA) than both primary and revision patients (21.2 versus 5.8 versus 5.8%, P = 0.001). CONCLUSION: The TKAs following ORIF of TPF are more like revision TKAs than primary TKAs in terms of patient-reported outcomes, operative times, and wound complications. The rate of MUA was higher than in both matched groups. These findings provide valuable information that can affect preoperative patient education and postoperative management regimens for these patients. They also emphasize the need for a conversion to TKA code due to the increased complexity and complications seen in this more difficult subset of TKAs.
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BACKGROUND: Management of atrial fibrillation is frequently geared toward improving symptoms. Yet, the magnitude of symptom-rhythm discordance is not well known in the setting of monitoring by ambulatory electrocardiography (AECG). OBJECTIVE: We aimed to quantify the symptom-rhythm correlation (SRC) for atrial arrhythmia (atrial tachycardia/atrial fibrillation [AT/AF]) events. METHODS: This was a retrospective cohort analysis of AECG data at a tertiary care center. All AECGs of ≥7 days with at least 1 AT/AF were included. Patient-triggered symptoms included shortness of breath, tiredness, palpitations, dizziness, or passing out with or without concurrent AT/AF. SRC was calculated for each patient. In addition, AT/AF-symptom association was evaluated at the event level by multivariable mixed effects logistic regression. RESULTS: We identified 742 patients with qualifying AECG data; mean age was 64 years, 50% were female, and 22% had heart failure. The mean CHA2DS2-VASc score was 2.5. There were 6289 symptomatic events and 6900 AT/AF episodes. Of symptomatic events, 1013 (16%) had shortness of breath, 839 (13%) tiredness, 2640 (42%) palpitations, 783 (12%) dizziness, and 93 (1%) passing out. Overall SRC was 0.39 (range, 0-1.0), but presence of AT/AF increased odds of symptoms by â¼8.3 times in adjusted analyses (P < .01). In multivariable analysis, prior AF rhythm control treatment and lower heart rate were associated with worse SRC (P < .01). CONCLUSION: Whereas AT/AF events increase the chances of symptoms, there is poor overall correlation between symptomatic events and documented AT/AF. Patient factors and prior treatments influence SRC. An improved understanding of this relationship correlation is needed to optimize clinical outcomes and to improve the rigor of AF research.
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Spontaneous intracerebral hemorrhage (sICH) is associated with significant morbidity and mortality, with subsequent hematoma expansion (HE) linked to worse neurologic outcomes. Accurate, real-time predictions of the risk of HE could enable tailoring management-including blood pressure control or surgery-based on individual patient risk. Although multiple radiographic markers of HE have been proposed based on standard imaging, their clinical utility remains limited by a reliance on subjective interpretation of often ambiguous findings and a poor overall predictive power. Radiomics refers to the quantitative analysis of medical images that can be combined with machine-learning algorithms to identify predictive features for a chosen clinical outcome with a granularity beyond human limitations. Emerging data have supported the potential utility of radiomics in the prediction of HE after sICH. In this review, we discuss the current clinical management of sICH, the impact of HE and standard imaging predictors, and finally, the current data and potential future role of radiomics in HE prediction and management of patients with sICH.