Hypoalbuminemia and Elevated CRP are Risk Factors for Deep Infections and Urinary Tract Infections After Lumbar Spine Surgery in a Large Retrospective Patient Population

Common hematological and biochemical parameters for predicting urinary tract infections in geriatric patients with hip fractures

Background

This study aims to discern the significance of common hematological and biochemical parameters for predicting urinary tract infections in geriatric patients with hip fractures.

Methods

Multivariable logistic regression and propensity score-matched analyses were conducted to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for UTIs. The abilities of these parameters to predict UTIs were evaluated by receiver operating characteristic (ROC) curves. Dose-response relationships were assessed by categorizing hematological and biochemical parameters into quartiles. Subgroup analyses were further explored to investigate the relationship between these parameters and urinary tract infections.

Results

Out of the 1,231 participants, 23.2% were diagnosed with UTIs. Hyperglycemia, hypoproteinemia and hyperglobulinemia were risk factors for UTIs in multivariate analysis. After propensity score matching, hyperglycemia (OR 2.14, 95% CI 1.50-3.05, p < 0.001), hypoproteinemia (OR 1.75, 95% CI 1.18-2.63, p = 0.006), and hyperglobulinemia (OR 1.38, 95% CI 0.97-1.97, p = 0.074) remained significantly associated with increased odds of urinary tract infections. ROC curve analyses showed moderate predictive accuracy of blood glucose, albumin and globulin for UTIs, with areas under the curves of 0.714, 0.633, and 0.596, respectively. Significant dose-response relationships were observed between these parameters and UTIs. The associations were consistent in subgroup analyses.

Conclusion

Blood glucose, albumin and globulin levels can facilitate early identification of geriatric hip fracture patients at high risk of UTIs. These easily obtainable hematological and biochemical parameters provide a practical clinical prediction tool for individualized UTI prevention in this population.

Preoperative Albumin and Postoperative CRP/Albumin Ratio (CARS) are Independent Predictive Factors in Estimating 1-Year Mortality in Patients Operated for Proximal Femoral Metastasis with Endoprosthesis

Background

Proximal femur resection and prosthetic reconstruction are preferred in patients with extensive bone destruction, pathological fractures, tumours resistant to radiation therapy, and patients with more proximal metastatic lesions. There is increasing evidence that the CRP/albumin ratio (CAR) is an independent marker of inflammation in various primary organ cancers and maybe a more accurate prognostic factor. We aimed to evaluate whether preoperative and postoperative CAR values could be a factor in predicting mortality in these patients. We hypothesized that CAR could predict these patients' postoperative 90-day and 1-year mortality.

Methods

The patient's age and gender, primary tumour, number of bone metastases, and presence of visceral metastases were recorded using imaging techniques such as computed tomography and bone scan or positron emission tomography. The following laboratory data were analyzed before and after surgery.

Results

The mean age of the patients was 62.67 ± 14.8; 56.9% were female (n:29), and 43.1% were male (n:22). When the results of the ROC analysis of the parameters in predicting 1-year mortality were examined, and the cut-off value for preoperative albumin was taken as ≤ 3.75, the AUC value was found to be statistically significant as 0.745 (p:0.003). When the cut-off value for postoperative CAR was taken as ≥ 87.32, the AUC value was found to be 0.7 statistically significant (p:0.015).

Conclusion

Length of stay, preoperative albumin and postoperative CAR values can be used as independent predictive values in predicting 1-year mortality in patients undergoing endoprosthesis due to proximal femur metastasis.

Post-operative C-reactive protein and white blood cells changes pattern following spinal deformity surgery and its clinical correlation

OBJECTIVE

Following the changing pattern of post-operative CRP and WBC counts and compare them to the patient's clinical condition to find which one is better for early detection of early infection.

METHODS

A total of 50 patients who underwent spinal deformity correction surgery without clinical signs of infection such as fever, wound redness, or discharge were enrolled in this prospective study. The C-reactive protein (CRP) and white blood cell (WBC) counts were measured the 2nd and 7th post-operative days. We try to detect the type of correlation between both CRP and WBCs level and clinical condition of patient regarding wound local condition.

RESULTS

All cases showed high CRP by the 2nd day post-operative which decreased significantly but not reaching normal levels even by the 7th day. All cases showed elevated WBCs count by the 2nd day which decreased to normal levels by the 3rd day in 86% of patients, and by the 7th day, 94% of cases showed normal levels. In addition, WBCs in the 2nd day post-operative significantly positive correlated with fusion level and operative time. There was no significant correlation between WBCs and blood transfusion or age. No significant correlation between CRP and number of fusion levels, blood transfusion nor operative time.

CONCLUSION

WBCs count returned earlier to normal levels than CRP in our cases, so monitoring early changes in the 1st week in WBCs count pattern is more indicative of an ongoing infectious process.

Clinical explainable machine learning models for early identification of patients at risk of hospital-acquired urinary tract infection

BACKGROUND

Machine learning (ML) models for early identification of patients at risk of hospital-acquired urinary tract infections (HA-UTI) may enable timely and targeted preventive and therapeutic strategies. However, clinicians are often challenged in the interpretation of the predictive outcomes provided by the ML models, which often reach different performances.

AIM

To train ML models for predicting patients at risk of HA-UTI using available data from electronic health records at the time of hospital admission. We focused on the performance of different ML models and clinical explainability.

METHODS

This retrospective study investigated patient data representing 138.560 hospital admissions in the North Denmark Region from 01.01.2017 to 31.12.2018. We extracted 51 health socio-demographic and clinical features in a full dataset and used the χ² test in addition to expert knowledge for feature selection, resulting in two reduced datasets. Seven different ML models were trained and compared between the three datasets. We applied the SHapley Additive exPlanation (SHAP) method to support population- and patient-level explainability.

FINDINGS

The best-performing ML model was a neural network based on the full dataset, reaching an area under the curve (AUC) of 0.758. The neural network was also the best-performing ML model based on the reduced datasets, reaching an AUC of 0.746. Clinical explainability was demonstrated with a SHAP summary- and forceplot.

CONCLUSION

Within 24h of hospital admission, the ML models were able to identify patients at risk of developing HA-UTI, providing new opportunities to develop efficient strategies for the prevention of HA-UTI. Using SHAP, we demonstrate how risk predictions can be explained at individual patient level and for the patient population in general.

Association between hypoalbuminemia and complications after degenerative and deformity-correcting spinal surgeries: A systematic review and meta-analysis

Objective

The current review was designed to explore if hypoalbuminemia is associated with increased complications in patients undergoing spinal degenerative and deformities surgeries.

Methods

The search for eligible studies was conducted on the databases of PubMed, Embase, Web of Science, and CENTRAL up to 20th June 2022. Complication rates were pooled to obtain odds ratio (OR) and 95% confidence intervals.

Results

Thirteen studies were included. We found that hypoalbuminemia was significantly associated with increased risk of all complications (OR: 2.72 95% CI: 2.04, 3.63 I ²= 58% p < 0.00001), mortality (OR: 7.73 95% CI: 3.81, 15.72 I ²= 0% p < 0.00001), revision surgery (OR: 3.15 95% CI: 1.53, 6.48 I ²= 87% p = 0.002), readmissions (OR: 1.96 95% CI: 1.29, 2.98 I ²= 23% p = 0.02), surgical site infections (OR: 2.97 95% CI: 1.90, 4.63 I ²= 38% p < 0.00001), wound complications (OR: 2.31 95% CI: 1.17, 4.56 I ²= 48% p = 0.02), pulmonary complications (OR: 3.74 95% CI: 2.66, 5.26 I ²= 0% p < 0.00001), renal complications (OR: 3.04 95% CI: 1.22, 7.54 I ²= 0% p = 0.02), cardiac complications (OR: 4.33 95% CI: 2.14, 8.77 I ²= 0% p < 0.0001), urinary tract infections (OR: 2.08 95% CI: 1.80, 2.41 I ²= 0% p < 0.00001), and sepsis (OR: 4.95 95% CI: 1.87, 13.08 I ²= 64% p = 0.01) as compared to those with normal albumin.

Conclusion

Hypoalbuminemia is a significant risk factor for complications after spinal degenerative and deformity surgeries. Research is also needed on the role of nutritional support in improving outcomes after spinal degenerative and deformity surgeries.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, identifier: CRD42022340024.