Predicting factors related with uncured hypertension after retroperitoneal laparoscopic adrenalectomy for unilateral primary aldosteronism

A Prospective Observational Study of Factors Affecting the Change in Quality of Life in Patients With Primary Aldosteronism After Treatment

OBJECTIVE

To explore the changes in the health-related quality of life (HRQoL) in patients with primary aldosteronism (PA) after standardized treatment and determine the effects of different variables on the change in the HRQoL of patients.

METHODS

A total of 116 patients with PA were prospectively included from November 2020 to March 2022. Data were collected at their initial diagnosis and the follow-up after 12 months of treatment, including demographic and clinical data and the scores of the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). The scores of each dimension of SF-36 of patients before and after treatment were compared, and the factors affecting their change in the quality of life were analyzed using multiple linear regression.

RESULTS

After standardized treatment, the aldosterone-to-renin ratio (Z = -4.967, P < .001), systolic blood pressure (t = 8.985, P < .001), and diastolic blood pressure (t = 7.233, P < .001) of patients with PA decreased compared with baseline, and hypokalemia was effectively corrected (χ2 = 69.014, P < .001). In terms of quality of life, 6 of 8 dimensions of SF-36 and the total score of SF-36 significantly improved at 1-year follow-up compared with baseline (all P < .05). The results of multiple linear regression showed that the improvement in the HRQoL in patients with PA after standardized treatment was correlated with the change in the blood potassium level (P = .007) and systolic blood pressure (P = .003).

CONCLUSION

Correction of hypokalemia and control of diastolic blood pressure are essential factors contributing to the improvement in the HRQoL in patients with PA regardless of the standardized treatment received.

Development and validation of machine-learning models for the difficulty of retroperitoneal laparoscopic adrenalectomy based on radiomics

Objective

The aim is to construct machine learning (ML) prediction models for the difficulty of retroperitoneal laparoscopic adrenalectomy (RPLA) based on clinical and radiomic characteristics and to validate the models.

Methods

Patients who had undergone RPLA at Shanxi Bethune Hospital between August 2014 and December 2020 were retrospectively gathered. They were then randomly split into a training set and a validation set, maintaining a ratio of 7:3. The model was constructed using the training set and validated using the validation set. Furthermore, a total of 117 patients were gathered between January and December 2021 to form a prospective set for validation. Radiomic features were extracted by drawing the region of interest using the 3D slicer image computing platform and Python. Key features were selected through LASSO, and the radiomics score (Rad-score) was calculated. Various ML models were constructed by combining Rad-score with clinical characteristics. The optimal models were selected based on precision, recall, the area under the curve, F1 score, calibration curve, receiver operating characteristic curve, and decision curve analysis in the training, validation, and prospective sets. Shapley Additive exPlanations (SHAP) was used to demonstrate the impact of each variable in the respective models.

Results

After comparing the performance of 7 ML models in the training, validation, and prospective sets, it was found that the RF model had a more stable predictive performance, while xGBoost can significantly benefit patients. According to SHAP, the variable importance of the two models is similar, and both can reflect that the Rad-score has the most significant impact. At the same time, clinical characteristics such as hemoglobin, age, body mass index, gender, and diabetes mellitus also influenced the difficulty.

Conclusion

This study constructed ML models for predicting the difficulty of RPLA by combining clinical and radiomic characteristics. The models can help surgeons evaluate surgical difficulty, reduce risks, and improve patient benefits.

Development and validation of nomograms to predict survival of primary adrenal lymphoma: a population-based retrospective study

While it is known that accurate evaluation of overall survival (OS) and disease-specific survival (DSS) for patients with primary adrenal lymphoma (PAL) can affect their prognosis, no stable and effective prediction model exists. This study aimed to develop prediction models to evaluate survival. This study enrolled 5448 patients with adrenal masses from the SEER Program. The influencing factors were selected using the least absolute shrinkage and selection operator regression model (LASSO) and Fine and Gray model (FGM). In addition, nomograms were constructed. Receiver operating characteristic curves and bootstrap self-sampling methods were used to verify the discrimination and consistency of the nomograms. The independent influencing factors for PAL survival were selected by LASSO and FGM, and three models were built: the OS, DSS, and FGS (DSS analysis by FGM) model. The areas under the curve and decision curve analyses indicated that the models were valid. This study developed survival prediction models to predict OS and DSS of patients with PAL. The FGS model was more accurate than the DSS model in the short term. Above all, these models should offer benefits to patients with PAL in terms of the treatment modality choice and survival evaluation.

A nomogram for evaluation and analysis of difficulty in retroperitoneal laparoscopic adrenalectomy: A single-center study with prospective validation using LASSO-logistic regression

BACKGROUND

While it is known that inaccurate evaluation for retroperitoneal laparoscopic adrenalectomy (RPLA) can affect the surgical results of patients, no stable and effective prediction model for the procedure exists. In this study, we aimed to develop a computed tomography (CT) -based radiological-clinical prediction model for evaluating the surgical difficulty of RPLA.

METHOD

Data from 398 patients with adrenal tumors treated by RPLA in a single center from August 2014 to December 2020 were retrospectively analyzed and divided into sets. The influencing factors were selected by least absolute shrinkage and selection operator regression model (LASSO). Additionally, the nomogram was constructed. A receiver operating characteristic curve was used to analyze the prediction efficiency of the nomogram. The C-index and bootstrap self-sampling methods were used to verify the discrimination and consistency of the nomogram.

RESULT

The following 11 independent influencing factors were selected by LASSO: body mass index, diabetes mellitus, scoliosis, hyperlipidemia, history of operation, tumor diameter, distance from adrenal tumor to upper pole of kidney, retro renal fat area, hyperaldosteronism, pheochromocytoma and paraganglioma, and myelolipoma. The area under the curve (AUC) of the training set was 0.787, and 0.844 in the internal validation set. Decision curve analyses indicated the model to be useful. An additional 117 patients were recruited for prospective validation, and AUC was 0.848.

CONCLUSION

This study developed a radiological-clinical prediction model proposed for predicting the difficulty of RPLA procedures. This model was suitable, accessible, and helpful for individualized surgical preparation and reduced operational risk. Thus, this model could contribute to more patients' benefit in circumventing surgical difficulties because of accurate predictive abilities.

Predictive factors of clinical success after adrenalectomy in primary aldosteronism: A systematic review and meta-analysis

BACKGROUND

Unilateral adrenalectomy is the mainstay treatment for unilateral primary aldosteronism (PA). This meta-analysis aimed to systematically analyse predictors of clinical success after unilateral adrenalectomy in PA.

METHODS

A search was performed using PubMed/Medline, Scopus, Embase and Web of Science from their inception to February 2022. Observational studies in adult PA patients which reported predictors of clinical success after unilateral adrenalectomy were included. A random-effects model was employed to pool the fully adjusted odds ratio (OR) or standardized mean difference (SMD) with 95% confidence interval (95% CI).

RESULTS

Thirty-two studies involving 5,601 patients were included. Females had a higher clinical success rate (OR 2.81; 95% CI 2.06-3.83). Older patients, patients with a longer duration of hypertension and those taking a higher number of antihypertensive medications had lower clinical success rates (OR 0.97; 95% CI 0.94-0.99, OR 0.92; 95% CI 0.88-0.96 and OR 0.44; 95% CI 0.29-0.67, respectively). Compared to non-clinical success cases, patients with clinical success had a lower body mass index (SMD -0.49 kg/m²; 95% CI -0.58,-0.39), lower systolic (SMD -0.37 mmHg; 95% CI -0.56,-0.18) and diastolic blood pressure (SMD -0.19 mmHg; 95% CI -0.33,-0.06), lower serum potassium (SMD -0.16 mEq/L; 95% CI -0.28,-0.04), higher eGFR (SMD 0.51 mL/min/1.73m²; 95% CI 0.16,0.87), a lower incidence of dyslipidemia (OR 0.29; 95% CI 0.15-0.58) and a lower incidence of diabetes mellitus (OR 0.36; 95% CI 0.22-0.59).

CONCLUSIONS

Multiple predictors of clinical success after unilateral adrenalectomy in PA were identified which can help improve the quality of care for PA patients. Systematic Review Registration: INPLASY, identifier 202240129.

Treatment of primary hyperaldosteronism

Primary aldosteronism is associated with higher cardiovascular and renal morbidity and mortality than essential hypertension in age- and sex-matched patients with the same degree of blood pressure elevation. Therefore, it is essential to establish a specific treatment to avoid the deleterious effects of aldosterone excess. Although adrenalectomy is generally considered the treatment of choice in cases of primary aldosteronism due to unilateral disease, several aspects and circumstances should be taken into account that may make medical treatment more appropriate. Among them, in this review we mention the limited experience and efficacy, and the potential risks of adrenal vein sampling; the risks and low efficacy of adrenalectomy; the high safety and efficacy of medical treatment and some special situations such as primary aldosteronism during pregnancy, in patients of advanced age or hereditary forms of primary aldosteronism, in which medical treatment is considered especially indicated as the first line therapy. The main studies comparing medical and surgical treatment in primary aldosteronism are also discussed.