The achievement of pre-operative expectations in patients undergoing knee arthroplasty: a cohort study evaluating unique patient goals.

BACKGROUND: Total knee arthroplasty (TKA) is a common procedure employed to treat end-stage osteoarthritis. While TKA is generally believed to have acceptable outcomes, many patients report pain or functional deficits not in line with their expectation following the procedure. It has been postulated that patient's pre-operative expectations regarding post-operative treatment outcomes play a significant role in satisfaction. It is therefore important to assess if the outcomes of surgery truly align with patient's individual expectations. Thus, the purpose of this study was to determine the degree to which patient expectations of TKA are achieved and the contribution of TKA to achieving patient goals one year after surgery. METHODS: A consecutive sample of 110 patients booked for total knee arthroplasty were asked to identify their most important goals to inform the Direct Questioning of Objectives Index (DQO Index, range 0 to 1) and identify their surgical goals and grade their expectation that a knee arthroplasty would achieve each goal on an 11-point scale. One year after surgery, the DQO Index was repeated to assess their current ability to achieve each pre-operative goal, and asked to estimate the contribution of their knee arthroplasty in achieving each goal. Mean differences between baseline and one year follow-up were calculated regarding the DQO Index and expected achievement of pre-operative goals. RESULTS: According to the DQO Index at one year, patients improved from a poor quality of life pre-operatively (mean ± standard deviation: 0.20 ± 0.18) to moderately high quality of life (mean ± standard deviation: 0.71 ± 0.21) reflecting a large improvement in ability to achieve each goal. Although achievement improved, for each goal, the patient estimates of the extent to which the knee arthroplasty had contributed to achieving the goal was lower than their initial expectation provided pre-operatively (mean difference range: 0.6 to 1.9 on an 11-point scale). CONCLUSION: Patients undergoing TKA have high expectations that their surgery will address their primary goals. Despite surgery largely achieving these goals (improved pain and function), the extent to which the goals were achieved was lower than patients had expected pre-operatively.

Development and validation of a preoperative CT­based radiomics nomogram to differentiate tuberculosis granulomas from lung adenocarcinomas: an external validation study.

BACKGROUND: An accurate and non-invasive approach is urgently needed to distinguish tuberculosis granulomas from lung adenocarcinomas. This study aimed to develop and validate a nomogram based on contrast enhanced-compute tomography (CE-CT) to preoperatively differentiate tuberculosis granuloma from lung adenocarcinoma appearing as solitary pulmonary solid nodules (SPSN). METHODS: This retrospective study analyzed 143 patients with lung adenocarcinoma (mean age: 62.4 ± 6.5 years; 54.5% female) and 137 patients with tuberculosis granulomas (mean age: 54.7 ± 8.2 years; 29.2% female) from two centers between March 2015 and June 2020. The training and internal validation cohorts included 161 and 69 patients (7:3 ratio) from center No.1, respectively. The external testing cohort included 50 patients from center No.2. Clinical factors and conventional radiological characteristics were analyzed to build independent predictors. Radiomics features were extracted from each CT-volume of interest (VOI). Feature selection was performed using univariate and multivariate logistic regression analysis, as well as the least absolute shrinkage and selection operator (LASSO) method. A clinical model was constructed with clinical factors and radiological findings. Individualized radiomics nomograms incorporating clinical data and radiomics signature were established to validate the clinical usefulness. The diagnostic performance was assessed using the receiver operating characteristic (ROC) curve analysis with the area under the receiver operating characteristic curve (AUC). RESULTS: One clinical factor (CA125), one radiological characteristic (enhanced-CT value) and nine radiomics features were found to be independent predictors, which were used to establish the radiomics nomogram. The nomogram demonstrated better diagnostic efficacy than any single model, with respective AUC, accuracy, sensitivity, and specificity of 0.903, 0.857, 0.901, and 0.807 in the training cohort; 0.933, 0.884, 0.893, and 0.892 in the internal validation cohort; 0.914, 0.800, 0.937, and 0.735 in the external test cohort. The calibration curve showed a good agreement between prediction probability and actual clinical findings. CONCLUSION: The nomogram incorporating clinical factors, radiological characteristics and radiomics signature provides additional value in distinguishing tuberculosis granuloma from lung adenocarcinoma in patients with a SPSN, potentially serving as a robust diagnostic strategy in clinical practice.

Deep learning-based risk stratification of preoperative breast biopsies using digital whole slide images.

BACKGROUND: Nottingham histological grade (NHG) is a well established prognostic factor in breast cancer histopathology but has a high inter-assessor variability with many tumours being classified as intermediate grade, NHG2. Here, we evaluate if DeepGrade, a previously developed model for risk stratification of resected tumour specimens, could be applied to risk-stratify tumour biopsy specimens. METHODS: A total of 11,955,755 tiles from 1169 whole slide images of preoperative biopsies from 896 patients diagnosed with breast cancer in Stockholm, Sweden, were included. DeepGrade, a deep convolutional neural network model, was applied for the prediction of low- and high-risk tumours. It was evaluated against clinically assigned grades NHG1 and NHG3 on the biopsy specimen but also against the grades assigned to the corresponding resection specimen using area under the operating curve (AUC). The prognostic value of the DeepGrade model in the biopsy setting was evaluated using time-to-event analysis. RESULTS: Based on preoperative biopsy images, the DeepGrade model predicted resected tumour cases of clinical grades NHG1 and NHG3 with an AUC of 0.908 (95% CI: 0.88; 0.93). Furthermore, out of the 432 resected clinically-assigned NHG2 tumours, 281 (65%) were classified as DeepGrade-low and 151 (35%) as DeepGrade-high. Using a multivariable Cox proportional hazards model the hazard ratio between DeepGrade low- and high-risk groups was estimated as 2.01 (95% CI: 1.06; 3.79). CONCLUSIONS: DeepGrade provided prediction of tumour grades NHG1 and NHG3 on the resection specimen using only the biopsy specimen. The results demonstrate that the DeepGrade model can provide decision support to identify high-risk tumours based on preoperative biopsies, thus improving early treatment decisions.

Association between preoperative albumin and length of hospital stay in non-cardiac surgery patients with pulmonary hypertension: A secondary retrospective analysis.

To explore the risk factors affecting the length of hospital stay (LOS) as well as to examine the relationship between preoperative serum albumin levels and LOS following non-cardiac, non-obstetric surgery in patients with pulmonary hypertension (PHTN). This study represents a secondary retrospective analysis based on 287 non-cardiac, non-obstetric procedures performed on 195 PTHN patients at a single institution in the USA between 2007 and 2013. The primary outcome was the LOS. We conducted a multiple logistic regression analysis to compare the LOS between the 2 groups, divided at a serum albumin level of 3.5 g/dL. After adjusting for multiple covariates, the ORs for the long length of stay (LOS > 7 days) for the high group(albumin > 3.5 g/dL) compared with the low group (albumin ≤ 3.5 g/dL) were 0.35 (95%CI: 0.21~0.6), 0.41 (95%CI: 0.22 ~0.76), 0.41 (95%CI: 0.18~0.94) from model 2 to model 4. The stratified analysis results indicate that these findings are stable (p for trend > 0.05). In this study, it was observed that low levels of preoperative albumin were associated with an increased risk of prolonged hospital stay after non-cardiac, non-obstetric surgery in patients with PHTN. This implies that optimizing preoperative nutrition could potentially reduce the LOS for non-cardiac, non-obstetric surgery in patients with PHTN.

Preoperative smoking and robot-assisted radical cystectomy outcomes & complications in multicenter KORARC database.

To investigate the influence of preoperative smoking history on the survival outcomes and complications in a cohort from a large multicenter database. Many patients who undergo radical cystectomy (RC) have a history of smoking; however, the direct association between preoperative smoking history and survival outcomes and complications in patients with muscle-invasive bladder cancer (MIBC) who undergo robot-assisted radical cystectomy (RARC) remains unexplored. We conducted a retrospective analysis using data from 749 patients in the Korean Robot-Assisted Radical Cystectomy Study Group (KORARC) database, with an average follow-up duration of 30.8 months. The cohort was divided into two groups: smokers (n = 351) and non-smokers (n = 398). Propensity score matching was employed to address differences in sample size and baseline demographics between the two groups (n = 274, each). Comparative analyses included assessments of oncological outcomes and complications. After matching, smoking did not significantly affect the overall complication rate (p = 0.121). Preoperative smoking did not significantly increase the occurrence of complications based on complication type (p = 0.322), nor did it increase the readmission rate (p = 0.076). There were no perioperative death in either group. Furthermore, preoperative smoking history showed no significant impact on overall survival (OS) [hazard ratio (HR) = 0.87, interquartile range (IQR): 0.54-1.42; p = 0.589] and recurrence-free survival (RFS) (HR = 1.12, IQR: 0.83-1.53; p = 0.458) following RARC for MIBC. The extent of preoperative smoking (≤ 10, 10-30, and ≥ 30 pack-years) had no significant influence on OS and RFS in any of the categories (all p > 0.05). Preoperative smoking history did not significantly affect OS, RFS, or complications in patients with MIBC undergoing RARC.

Preoperative three-dimensional lung volumetry predicts respiratory complications in patients undergoing major liver resection for colorectal metastases.

Colorectal liver metastases (CRLM) are the predominant factor limiting survival in patients with colorectal cancer and liver resection with complete tumor removal is the best treatment option for these patients. This study examines the predictive ability of three-dimensional lung volumetry (3DLV) based on preoperative computerized tomography (CT), to predict postoperative pulmonary complications in patients undergoing major liver resection for CRLM. Patients undergoing major curative liver resection for CRLM between 2010 and 2021 with a preoperative CT scan of the thorax within 6 weeks of surgery, were included. Total lung volume (TLV) was calculated using volumetry software 3D-Slicer version 4.11.20210226 including Chest Imaging Platform extension ( http://www.slicer.org ). The area under the curve (AUC) of a receiver-operating characteristic analysis was used to define a cut-off value of TLV, for predicting the occurrence of postoperative respiratory complications. Differences between patients with TLV below and above the cut-off were examined with Chi-square or Fisher's exact test and Mann-Whitney U tests and logistic regression was used to determine independent risk factors for the development of respiratory complications. A total of 123 patients were included, of which 35 (29%) developed respiratory complications. A predictive ability of TLV regarding respiratory complications was shown (AUC 0.62, p = 0.036) and a cut-off value of 4500 cm3 was defined. Patients with TLV < 4500 cm3 were shown to suffer from significantly higher rates of respiratory complications (44% vs. 21%, p = 0.007) compared to the rest. Logistic regression analysis identified TLV < 4500 cm3 as an independent predictor for the occurrence of respiratory complications (odds ratio 3.777, 95% confidence intervals 1.488-9.588, p = 0.005). Preoperative 3DLV is a viable technique for prediction of postoperative pulmonary complications in patients undergoing major liver resection for CRLM. More studies in larger cohorts are necessary to further evaluate this technique.

Preoperative peripheral inflammatory markers are predictors of postoperative central diabetes insipidus in craniopharyngioma patients: a retrospective study.

BACKGROUND: Postoperative central diabetes insipidus (CDI) is commonly observed in craniopharyngioma (CP) patients, and the inflammatory response plays an important role in CPs. We aimed to evaluate the predictive value of preoperative peripheral inflammatory markers and their combinations regarding CDI occurrence in CPs. METHODS: The clinical data including preoperative peripheral inflammatory markers of 208 CP patients who underwent surgical treatment were retrospectively collected and analyzed. The preoperative peripheral white blood cells (WBC), neutrophils, lymphocytes, monocytes, platelet (PLT), neutrophil-to-lymphocyte ratio (NLR), derived-NLR (dNLR), monocyte-to-lymphocyte ratio (MLR) and PLT-to-lymphocyte ratio (PLR) were assessed in total 208 CP patients and different age and surgical approach CP patient subgroups. Their predictive values were evaluated by the receiver operator characteristic curve analysis. RESULTS: Preoperative peripheral WBC, neutrophils, NLR, dNLR, MLR, and PLR were positively correlated and lymphocyte was negatively associated with postoperative CDI occurrence in CP patients, especially when WBC ≥ 6.66 × 109/L or lymphocyte ≤ 1.86 × 109/L. Meanwhile, multiple logistic regression analysis showed that WBC > 6.39 × 109/L in the > 18 yrs age patients, WBC > 6.88 × 109/L or lymphocytes ≤ 1.85 × 109/L in the transcranial approach patients were closely associated with the elevated incidence of postoperative CDI. Furthermore, the area under the curve obtained from the receiver operator characteristic curve analysis showed that the best predictors of inflammatory markers were the NLR in total CP patients, the MLR in the ≤ 18 yrs age group and the transsphenoidal group, the NLR in the > 18 yrs age group and the dNLR in the transcranial group. Notably, the combination index NLR + dNLR demonstrated the most valuable predictor in all groups. CONCLUSIONS: Preoperative peripheral inflammatory markers, especially WBC, lymphocytes and NLR + dNLR, are promising predictors of postoperative CDI in CPs.

Preoperative prediction model for risk of readmission after total joint replacement surgery: a random forest approach leveraging NLP and unfairness mitigation for improved patient care and cost-effectiveness.

BACKGROUND: The Center for Medicare and Medicaid Services (CMS) imposes payment penalties for readmissions following total joint replacement surgeries. This study focuses on total hip, knee, and shoulder arthroplasty procedures as they account for most joint replacement surgeries. Apart from being a burden to healthcare systems, readmissions are also troublesome for patients. There are several studies which only utilized structured data from Electronic Health Records (EHR) without considering any gender and payor bias adjustments. METHODS: For this study, dataset of 38,581 total knee, hip, and shoulder replacement surgeries performed from 2015 to 2021 at Novant Health was gathered. This data was used to train a random forest machine learning model to predict the combined endpoint of emergency department (ED) visit or unplanned readmissions within 30 days of discharge or discharge to Skilled Nursing Facility (SNF) following the surgery. 98 features of laboratory results, diagnoses, vitals, medications, and utilization history were extracted. A natural language processing (NLP) model finetuned from Clinical BERT was used to generate an NLP risk score feature for each patient based on their clinical notes. To address societal biases, a feature bias analysis was performed in conjunction with propensity score matching. A threshold optimization algorithm from the Fairlearn toolkit was used to mitigate gender and payor biases to promote fairness in predictions. RESULTS: The model achieved an Area Under the Receiver Operating characteristic Curve (AUROC) of 0.738 (95% confidence interval, 0.724 to 0.754) and an Area Under the Precision-Recall Curve (AUPRC) of 0.406 (95% confidence interval, 0.384 to 0.433). Considering an outcome prevalence of 16%, these metrics indicate the model's ability to accurately discriminate between readmission and non-readmission cases within the context of total arthroplasty surgeries while adjusting patient scores in the model to mitigate bias based on patient gender and payor. CONCLUSION: This work culminated in a model that identifies the most predictive and protective features associated with the combined endpoint. This model serves as a tool to empower healthcare providers to proactively intervene based on these influential factors without introducing bias towards protected patient classes, effectively mitigating the risk of negative outcomes and ultimately improving quality of care regardless of socioeconomic factors.

Prognostic significance of preoperative lymphocytes, albumin, and neutrophils (LANR) index in resectable pancreatic ductal adenocarcinoma.

PURPOSE: The index composed of preoperative lymphocytes, albumin, and neutrophils (LANR), a new composite score based on inflammatory response and nutritional status, has been reported to be associated with the prognosis of multiple types of cancer, but the role of LANR in the prognosis of resectable pancreatic ductal adenocarcinoma (PDAC) has not yet been elucidated. PATIENTS AND METHODS: The data of 142 patients with PDAC who underwent radical resection in the Affiliated Hospital of Jiangnan University from January 2015 to December 2018 were retrospectively analyzed. Receiver Operating Characteristic (ROC) curves were generated to determine the optimal cut-off values for these parameters, as well as the sensitivity and specificity of LANR in predicting survival. The Kaplan-Meier method was used to draw the survival curves. Log rank test was used for univariate analysis, and Cox proportional hazards regression model was used for multivariate analysis.  RESULTS: The optimal cut-off value of LANR was 18.145, and a low preoperative LANR was significantly correlated with the location of the tumor (p = 0.047). Multivariate analysis showed that tumor differentiation degree (HR:2.357, 95%CI:1.388-4.003,p = 0.002), lymph node metastasis (HR:1.755, 95%CI: 1.115-2.763, p = 0.015), TNM stage (HR:4.686, 95%CI: 2.958-7.425, p < 0.001), preoperative cancer antigen 19 - 9 levels (HR:1.001, 95%CI: 1.000-1.001, p < 0.001) and preoperative LANR (HR:0.221, 95%CI: 0.111-0.441, p < 0.001) were independent risk factors for a poor prognosis in patients undergoing radical resection of PDAC. CONCLUSION: This study found that preoperative LANR can be used to assess the prognosis of radical resection in patients with PDAC; those with low preoperative LANR had a worse outcome.

Preoperative prediction of perineural invasion of rectal cancer based on a magnetic resonance imaging radiomics model: A dual-center study.

BACKGROUND: Perineural invasion (PNI) has been used as an important pathological indicator and independent prognostic factor for patients with rectal cancer (RC). Preoperative prediction of PNI status is helpful for individualized treatment of RC. Recently, several radiomics studies have been used to predict the PNI status in RC, demonstrating a good predictive effect, but the results lacked generalizability. The preoperative prediction of PNI status is still challenging and needs further study. AIM: To establish and validate an optimal radiomics model for predicting PNI status preoperatively in RC patients. METHODS: This retrospective study enrolled 244 postoperative patients with pathologically confirmed RC from two independent centers. The patients underwent pre-operative high-resolution magnetic resonance imaging (MRI) between May 2019 and August 2022. Quantitative radiomics features were extracted and selected from oblique axial T2-weighted imaging (T2WI) and contrast-enhanced T1WI (T1CE) sequences. The radiomics signatures were constructed using logistic regression analysis and the predictive potential of various sequences was compared (T2WI, T1CE and T2WI + T1CE fusion sequences). A clinical-radiomics (CR) model was established by combining the radiomics features and clinical risk factors. The internal and external validation groups were used to validate the proposed models. The area under the receiver operating characteristic curve (AUC), DeLong test, net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration curve, and decision curve analysis (DCA) were used to evaluate the model performance. RESULTS: Among the radiomics models, the T2WI + T1CE fusion sequences model showed the best predictive performance, in the training and internal validation groups, the AUCs of the fusion sequence model were 0.839 [95% confidence interval (CI): 0.757-0.921] and 0.787 (95%CI: 0.650-0.923), which were higher than those of the T2WI and T1CE sequence models. The CR model constructed by combining clinical risk factors had the best predictive performance. In the training and internal and external validation groups, the AUCs of the CR model were 0.889 (95%CI: 0.824-0.954), 0.889 (95%CI: 0.803-0.976) and 0.894 (95%CI: 0.814-0.974). Delong test, NRI, and IDI showed that the CR model had significant differences from other models (P < 0.05). Calibration curves demonstrated good agreement, and DCA revealed significant benefits of the CR model. CONCLUSION: The CR model based on preoperative MRI radiomics features and clinical risk factors can preoperatively predict the PNI status of RC noninvasively, which facilitates individualized treatment of RC patients.

Abnormal coagulation after hepatectomy in patients with normal preoperative coagulation function.

BACKGROUND: To explore the risk factors for postoperative abnormal coagulation (PAC) and establish a predictive model for patients with normal preoperative coagulation function who underwent hepatectomy. MATERIALS AND METHODS: A total of 661 patients with normal preoperative coagulation function who underwent hepatectomy between January 2015 and December 2021 at the First Affiliated Hospital of Sun Yat-sen University were divided into two groups: the postoperative abnormal coagulation group (PAC group, n = 362) and the normal coagulation group (non-PAC group, n = 299). Univariate and multivariate logistic analyses were used to identify the risk factors for PAC. RESULTS: The incidence of PAC in 661 patients who underwent hepatectomy was 54.8% (362/661). The least absolute shrinkage and selection operator (LASSO) method was used for multivariate logistic regression analysis. The preoperative international normalized ratio (INR), intraoperative succinyl gelatin infusion and major hepatectomy were found to be independent risk factors for PAC. A nomogram for predicting the PAC after hepatectomy was constructed. The model presented a receiver operating characteristic (ROC) curve of 0.742 (95% confidence interval (CI): 0.697-0.786) in the training cohort. The validation set demonstrated a promising ROC of 0.711 (95% CI: 0.639-0.783), and the calibration curve closely approximated the true incidence. Decision curve analysis (DCA) was performed to assess the clinical usefulness of the predictive model. The risk of PAC increased when the preoperative international normalized ratio (INR) was greater than 1.025 and the volume of intraoperative succinyl gelatin infusion was greater than 1500 ml. CONCLUSION: The PAC is closely related to the preoperative INR, intraoperative succinyl gelatin infusion and major hepatectomy. A three-factor prediction model was successfully established for predicting the PAC after hepatectomy.

Association of Preoperative Subchondral Bone Marrow Oedema with Outcomes after Lateral Unicompartmental Knee Arthroplasty.

OBJECTIVE: To determine whether the presence of preoperative subchondral bone marrow oedema (SBME) is associated with inferior outcomes after lateral unicompartmental knee arthroplasty (LUKA). STUDY DESIGN: Descriptive study. Place and Duration of the Study: Department of Orthopaedic Surgery, Chongqing Orthopaedic Hospital of Traditional Chinese Medicine, Chongqing, China, from January 2019 to June 2022. METHODOLOGY: Data on patients treated with LUKA were obtained from the Medical Registry Database. Two groups were made based on the presence and absence of SBME on preoperative magnetic resonance imaging (MRI). The visual analogue scale (VAS), American Knee Society Scores (AKSS), and rate of patient satisfaction were compared between the two groups. RESULTS: A total of 20 patients treated with LUKA were reviewed. The SBME was present in 9 cases and absent in 11 cases. Patients with SBME had inferior scores at preoperative evaluation and at 1, 3, and 6 months postoperatively. However, there was no significant difference between the groups at the 12-month follow-up. Eight (88.9%) patients with SBME were satisfied with the LUKA surgery versus 9 (81.8%) patients without SBME, showing no significant differences between groups. CONCLUSION: Presence of preoperative SBME is associated with inferior functional outcomes after LUKA within six months of follow-up. KEY WORDS: Bone marrow, Oedema, Knee, Arthroplasty, Outcome, Patient satisfaction.

Functional Physical Analysis and Quality of Life in the Preoperative and Early Postoperative Periods of Cardiac Surgery and 30 Days After Hospital Discharge.

INTRODUCTION: The analysis of patients submitted to heart surgery at three assessment times has been insufficiently described in the literature. OBJECTIVE: To analyze chest expansion, maximum inspiratory pressure (MIP), maximum expiratory pressure (MEP), distance traveled on the six-minute walk test (6MWT), and quality of life in the preoperative period, fourth postoperative day (4th PO), and 30th day after hospital discharge (30th-day HD) in individuals submitted to elective heart surgery. METHODS: A descriptive, analytical, cross-sectional study was conducted with 15 individuals submitted to elective heart surgery between 2016 and 2020 who did not undergo any type of physiotherapeutic intervention in Phase II of cardiac rehabilitation. The outcome variables were difference in chest expansion (axillary, nipple, and xiphoid), MIP, MEP, distance on 6MWT, and quality of life. The assessment times were preoperative period, 4th PO, and 30th-day HD. RESULTS: Chest expansion diminished between the preoperative period and 4th PO, followed by an increase at 30th-day HD. MIP, MEP, and distance traveled on the 6MWT diminished between the preoperative period and 4th PO, with a return to preoperative values at 30th-day HD. General quality of life improved between the preoperative period and 4th PO and 30th-day HD. An improvement was found in the social domain between the preoperative period and the 30th-day HD. CONCLUSION: Heart surgery causes immediate physical deficit, but physical functioning can be recovered 30 days after hospital discharge, resulting in an improvement in quality of life one month after surgery.

Effects of Preoperative Nutritional Status and Lymphocyte Count on the Development of Early-term Atrial Fibrillation After Coronary Artery Bypass Grafting: A Retrospective Study.

INTRODUCTION: Although there are publications in the literature stating that parameters related to the nutritional status of patients are associated with the clinical outcomes of those with coronary artery disease, it is also stated that there is insufficient data on the relationship between nutritional indices and long-term outcomes and major adverse cardiovascular events in patients undergoing isolated coronary artery bypass grafting. METHODS: This retrospective study was conducted with patients who underwent isolated elective on-pump coronary artery bypass grafting in our hospital. Patients who underwent emergency coronary artery bypass grafting or those with known atrial fibrillation in the preoperative period were excluded. Patients were analyzed and compared in two groups according to the development of postoperative atrial fibrillation. RESULTS: The data of 93 coronary artery bypass grafting patients (71 [76%] males) with a mean age of 62.86 ± 9.53 years included in the study were evaluated. Both groups had similar preoperative ejection fraction value, hemoglobin level, age, number of distal bypasses, and postoperative mortality rates. Although the mean cardiopulmonary bypass and aortic cross-clamping times were higher in Group 1, they were not statistically significant. In our study, the mean prognostic nutrition index value was 51.76 ± 3002. CONCLUSION: According to our study results, there was no statistically significant difference between prognostic nutrition index values and the development of atrial fibrillation after coronary artery bypass grafting, which is similar to some publications in the literature. We think that it would be beneficial to conduct randomized studies involving more patients on this subject.

Preoperatively predicting the lymph node metastasis and prognosis for gastric cancer patients.

The preoperative distinguishment of lymph nodes (LN) with metastasis plays a pivotal role in guiding the surgical extension for gastric cancer (GC). We aim to identify the preparative risk factors for LN metastasis in GC patients. We retrospectively reviewed 424 patients who underwent radical GC resection in our medical center between Jan 2011 and Dec 2018. Multivariate logistic regression was employed to identify risk factors for LN metastasis, while multivariate COX regression was utilized to evaluate prognostic factors. The median overall survival of patients with or without LN metastases was 31 and 58 months, respectively. In multivariate analysis, lower albumin (OR = 0.512; P = 0.004) and prealbumin (OR = 0.367, P = 0.001) and higher CEA (OR = 3.178, P < 0.001), CA199 (OR = 2.278, P = 0.002) and platelets (OR = 1.697, P = 0.017) were found to be significantly associated with LN metastasis. In survival analysis, older age (HR = 1.712), larger tumors (HR = 1.082), higher D-dimer (HR = 1.561) and CA199 (HR = 1.553), advanced staging (stage II, HR = 3.446; stage III-IV, HR = 11.089), lower prealbumin levels (lower level for reference, HR = 0.63), and absence of adjuvant chemotherapy (HR = 0.396) was discovered to be associated with poorer overall survival (all P < 0.05). In conclusion, our results demonstrated that preoperative prealbumin-bound tumor markers can effectively predict LN metastasis. Additionally, prealbumin was found to possess prognostic value as well.

The role of preoperative FPR and FAR in prognostic evaluation of stages II and III radical colorectal cancer: A single-center retrospective study.

The inflammatory and nutritional states of body are 2 important causes associated with the initiation and progression of colorectal cancer (CRC). The aim of this study is to investigate the prognostic evaluation value of preoperative fibrinogen-to-prealbumin ratio (FPR) and preoperative fibrinogen-to-albumin ratio (FAR) in CRC. The clinical data of 350 stages II and III patients with CRC who received radical resection were retrospectively analyzed. All patients were followed up for 5 years to observe the overall survival and disease-free survival of 5 years and analyze the relationship between preoperative FPR and FAR and prognosis of all enrolled patients. In addition, we analyzed the diagnostic and application value of combined biomarkers. This study showed high-level preoperative FPR and FAR were significantly associated with poor overall survival and disease-free survival of stages II and III patients with CRC. The elevated preoperative FPR and FAR level was significantly related to age, tumor differentiation level, TNM stage, vascular infiltration, carcinoembryonic antigen, carbohydrate antigen199, etc. The combination of FPR, FAR, neutrophil-to-lymphocyte ratio, and carbohydrate antigen199 had the maximum area under curve (AUC = 0.856, 95% CI: 0.814-0.897, Sen = 78.20%, Spe = 82.49%, P < .05) under the receiver-operating characteristics curve. The preoperative FPR and FAR have important prognostic value and they can be used as independent prognostic marker for patients with stages II and III CRC undergoing radical resection. Moreover, the combination of biomarkers could further enhance the diagnostic and prognostic efficacy of CRC.

Development and external validation of preoperative clinical prediction models for postoperative outcomes including preoperative aerobic fitness in patients approaching elective colorectal cancer surgery.

INTRODUCTION: Preoperative aerobic fitness is associated with postoperative outcomes after elective colorectal cancer (CRC) surgery. This study aimed to develop and externally validate two clinical prediction models incorporating a practical test to assess preoperative aerobic fitness to distinguish between patients with and without an increased risk for 1) postoperative complications and 2) a prolonged time to in-hospital recovery of physical functioning after elective colorectal cancer (CRC) surgery. MATERIALS AND METHODS: Models were developed using prospective data from 256 patients and externally validated using prospective data of 291 patients. Postoperative complications were classified according to Clavien-Dindo. The modified Iowa level of assistance scale (mILAS) was used to determine time to postoperative in-hospital physical recovery. Aerobic fitness, age, sex, body mass index, American Society of Anesthesiologists (ASA) classification, neoadjuvant treatment, surgical approach, tumour location, and preoperative haemoglobin level were potential predictors. Areas under the curve (AUC), calibration plots, and Hosmer-Lemeshow tests evaluated predictive performance. RESULTS: Aerobic fitness, sex, age, ASA, tumour location, and surgical approach were included in the final models. External validation of the model for complications and postoperative recovery presented moderate to fair discrimination (AUC 0.666 (0.598-0.733) and 0.722 (0.651-0.794), respectively) and good calibration. High sensitivity and high negative predictive values were observed in the lower predicted risk categories (<40 %). CONCLUSION: Both models identify patients with and without an increased risk of complications or a prolonged time to in-hospital physical recovery. They might be used for improving patient-tailored preoperative risk assessment and targeted and cost-effective application of prehabilitation interventions.

The association of preoperative hematologic parameters with short-term clinical outcomes in rectal cancer: A feature importance analysis.

BACKGROUND: Various hematologic parameters have been proposed as prognostic factors in rectal cancer management, but data are conflicting and unclear. This study is designed to investigate the prognostic factor capability of preoperative hematologic parameters with postoperative morbidities and mortality in rectal cancer patients undergoing curative resection. METHODS: All 200 consecutive rectal cancer patients diagnosed at Ghaem University Hospital from 2017 to 2022 were retrospectively evaluated. The receiver operating characteristic (ROC) curves and machine learning (ML) algorithms of Random Forest, Recursive Feature Elimination, simulated annealing, Support Vector Machine, Decision Tree, and eXtreme Gradient Boosting were administered to investigate the role of preoperative hematologic parameters accompanied by baseline characteristics on three clinical outcomes including surgical infectious complications, recurrence, and death. RESULTS: The frequency of infectious complications was correlated with the surgical procedure, while tumor recurrence was significantly influenced by T stage and N stage. In terms of mortality, alongside T and N stage, the status of resection margin involvement was significantly correlated. Based on the ROC analysis, the NLR >2.69, MPV ≤9 fL, and PDW ≤10.5 fL were more classified patients to mortality status. Likewise, the PLT >220 109/L, MPV ≤9 fL, PDW ≤10.4 fL, and PLR >13.6 were correlated with recurrence. However, all factors examined in this study were not significant classifiers for the outcome of surgical infectious complications. The results of ML algorithms were also in line with ROC analysis. CONCLUSION: According to the results of both ROC analysis and ML models, preoperative hematologic parameters are considerable prognostic factors of postoperative outcomes in rectal cancer patients, and are recommended to be monitored by clinicians to prevent unfavorable outcomes.

A combinatorial MRI sequence-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer.

This study aimed to develop an optimal radiomics model for preoperatively predicting microsatellite instability (MSI) in patients with rectal cancer (RC) based on multiparametric magnetic resonance imaging. The retrospective study included 308 RC patients who did not receive preoperative antitumor therapy, among whom 51 had MSI. Radiomics features were extracted and dimensionally reduced from T2-weighted imaging (T2WI), T1-weighted imaging (T1WI), diffusion-weighted imaging (DWI), and T1-weighted contrast enhanced (T1CE) images for each patient, and the features of each sequence were combined. Multifactor logistic regression was used to screen the optimal feature set for each combination. Different machine learning methods were applied to construct predictive MSI status models. Relative standard deviation values were determined to evaluate model performance and select the optimal model. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analyses were performed to evaluate model performance. The model constructed using the k-nearest neighbor (KNN) method combined with T2WI and T1CE images performed best. The area under the curve values for prediction of MSI with this model were 0.849 (0.804-0.887), with a sensitivity of 0.784 and specificity of 0.805. The Delong test showed no significant difference in diagnostic efficacy between the KNN-derived model and the traditional logistic regression model constructed using T1WI + DWI + T1CE and T2WI + T1WI + DWI + T1CE data (P > 0.05) and the diagnostic efficiency of the KNN-derived model was slightly better than that of the traditional model. From ROC curve analysis, the KNN-derived model significantly distinguished patients at low- and high-risk of MSI with the optimal threshold of 0.2, supporting the clinical applicability of the model. The model constructed using the KNN method can be applied to noninvasively predict MSI status in RC patients before surgery based on radiomics features from T2WI and T1CE images. Thus, this method may provide a convenient and practical tool for formulating treatment strategies and optimizing individual clinical decision-making for patients with RC.

Preoperative Dehydration Is an Underrecognized Modifiable Risk Factor in Total Hip Arthroplasty.

Dehydration is an overlooked modifiable risk factor that should be optimized prior to elective total hip arthroplasty (THA) to reduce postoperative complications and inpatient costs. All primary THA from 2005 - 2019 were queried from the National Surgical Quality Improvement Program database, and patients were compared based on dehydration status: blood urea nitrogen (BUN): creatinine ratio (Cr) (BUN/Cr) < 20 (nondehydrated), 20 ≤ BUN/Cr ≤ 25 (moderately dehydrated), 25 < BUN/Cr (severely dehydrated). A subgroup analysis involving only elderly patients > 65 years and normalized gender-adjusted Cr values was also performed. The analysis included 212,452 patients who underwent THA. Adjusted multivariate logistic regression analysis showed that the severely dehydrated cohort had a greater risk of overall complications, postoperative anemia requiring transfusion, nonhome discharge, and increased length of stay (all p < 0.01). Among the elderly, dehydrated patients had a greater risk of postoperative transfusion, cardiac complications, and nonhome discharge (all p < 0.01). BUN/Cr > 20 is an important preoperative diagnostic tool to identify at-risk dehydrated patients. Providers should optimize dehydration to prevent complications, decrease costs, and improve discharge planning. (Journal of Surgical Orthopaedic Advances 33(1):017-025, 2024).