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[This corrects the article DOI: 10.1371/journal.pone.0152871.].

Patients with CKD have a 4–fivefold higher rate of fractures. The incidence of fractures increases with deterioration of kidney function. The process of skeletal changes in CKD patients is characterized by compromised bone strength because of deterioration of bone quantity and/or quality. The fractures lead to a deleterious effect on the quality of life and higher mortality in patients with CKD. The pathogenesis of bone loss and fracture is complex and multi-factorial. Renal osteodystrophy, uremic milieu, drugs, and systemic diseases that lead to renal failure all contribute to bone damage in CKD patients. There is no consensus on the optimal diagnostic method of compromised bone assessment in patients with CKD. Bone quantity and mass can be assessed by dual-energy x-ray absorptiometry (DXA) or quantitative computed tomography (QCT). Bone quality on the other side can be assessed by non-invasive methods such as trabecular bone score (TBS), high-resolution bone imaging methods, and invasive bone biopsy. Bone turnover markers can reflect bone remodeling, but some of them are retained by kidneys. Understanding the mechanism of bone loss is pivotal in preventing fracture in patients with CKD. Several non-pharmacological and therapeutic interventions have been reported to improve bone health. Controlling laboratory abnormalities of CKD-MBD is crucial. Anti-resorptive therapies are effective in improving BMD and reducing fracture risk, but there are uncertainties about safety and efficacy especially in advanced CKD patients. Accepting the prevalent of low bone turnover in patients with advanced CKD, the osteo-anabolics are possibly promising. Parathyroidectomy should be considered a last resort for intractable cases of renal hyperparathyroidism. There is a wide unacceptable gap in osteoporosis management in patients with CKD. This article is focusing on the updated management of CKD-MBD and osteoporosis in CKD patients.Mini AbstractChronic kidney disease deteriorates bone quality and quantity. The mechanism of bone loss mainly determines pharmacological treatment. DXA and QCT provide information about bone quantity, but assessing bone quality, by TBS, high-resolution bone imaging, invasive bone biopsy, and bone turnover markers, can guide us about the mechanism of bone loss.

Renal osteodystrophy (ROD) starts early and progresses with further loss of kidney function in patients with chronic kidney disease (CKD). There are four distinct types of ROD based on undecalcified bone biopsy results. Adynamic bone disease and osteomalacia are the predominant forms of low bone turnover, while hyperparathyroid bone disease and mixed uremic osteodystrophy (MUO) are typically associated with high bone turnover. MUO is a prevalent but poorly described pathology that demonstrates evidence of osteomalacia on top of the high bone formation/resorption. The prevalence of MUO ranges from 5 to 63% among different studies. The pathogenesis of MUO is multi-factorial. Altered phosphate homeostasis, hypocalcemia, vitamin D deficiency, increased FGF-23, interleukins 1 and 6, TNF-α, amyloid, and heavy metal accumulation are the main inducers of MUO. The clinical findings of MUO are usually non-specific. The use of non-invasive testing such as bone turnover markers and imaging techniques might help to suspect MUO. However, it is usually impossible to precisely diagnose this condition without performing bone biopsy. The principal management of MUO is to control the maladaptive hyperparathyroidism along with correcting any nutritional mineral deficiencies that may induce mineralization defect. MUO is a common but still poorly understood bone pathology category; it demonstrates the complexity and difficulty in understanding ROD. A large prospective bone biopsy-based studies are needed for better identification as proper diagnosis and management would improve the outcome of patients with MUO.

Patients with chronic kidney disease (CKD) are more likely to experience falls and fractures due to renal osteodystrophy and the high prevalence of risk factors for falls. However, it is not well established how great the risk is for falls and fractures for the different stages of CKD compared to the general population. The objective of this systematic review and meta-analysis was to assess whether, and in which degree, CKD was associated with falls and fractures in adults. A systematic search in PubMed, Embase, CINAHL, and The Cochrane Library was performed on 7 September 2018. All retrospective, cross-sectional, and longitudinal studies of adults (18 years of older) that studied the association between CKD, fractures, and falls were included. Additional studies were identified by cross-referencing. A total of 39 publications were included, of which two publications assessed three types of outcome and four publications assessed two types of outcome. Ten studies focused on accidental falling; seventeen studies focused on hip, femur, and pelvis fractures; seven studies focused on vertebral fractures; and thirteen studies focused on any type of fracture without further specification. Generally, the risk of fractures increased when kidney function worsened, with the highest risks in the patients with stage 5 CKD or dialysis. This effect was most pronounced for hip fractures and any type of fractures. Furthermore, results on the association between CKD and accidental falling were contradictory. Compared to the general population, fractures are highly prevalent in patients with CKD. Besides more awareness of timely fracture risk assessment, there also should be more focus on fall prevention.

Abstract Purpose Secondary hyperparathyroidism (SHPT) frequently affects patients with end-stage renal disease. Hungry bone syndrome (HBS) is a common complication among patients who undergo parathyroidectomy for SHPT and may cause prolonged hospitalization or require intensive care. The objective of this study is to develop a scoring system to stratify patients according to their risk of developing HBS. Methods A retrospective cohort study was performed using the US Renal Data System (2010-2021). Univariable and multivariable logistic regression models were developed and weighted β-coefficients from the multivariable model were used to construct a risk score for the development of HBS. Positive and negative predictive values were assessed. Results Of 17 074 patients who underwent parathyroidectomy for SHPT, 19.4% developed HBS. Intensive care unit admission was more common in patients who developed HBS (33.5% vs 24.6%, P < .001). On multivariable logistic regression analysis, younger age, renal osteodystrophy, longer duration of dialysis, longer duration of kidney transplant, and higher Elixhauser score were significantly associated with HBS. A risk score based on these clinical factors was developed, with a total of 6 possible points. Rates of HBS ranged from 8% in patients with 0 points to 44% in patients with 6 points. The risk score had a poor positive predictive value (20.3%) but excellent negative predictive value (89.3%) for HBS. Conclusion We developed a weighted risk score that effectively stratifies patients by risk for developing HBS after parathyroidectomy. This tool can be used to counsel patients and to identify patients who may not require postoperative hospitalization.

Abnormal bone metabolism is an integral part of the chronic kidney disease-mineral bone disorder (CKD-MBD). For several reasons, the difficult bone compartment was neglected for some time, but there has been renewed interest as a result of the conception of bone as a new endocrine organ, the increasing recognition of the cross-talk between bone and vessels, and, especially, the very high risk of osteoporotic fractures (and associated mortality) demonstrated in patients with CKD. Therefore, it has been acknowledged in different guidelines that action is needed in respect of fracture risk assessment and the diagnosis and treatment of osteoporosis in the context of CKD and CKD-MBD, even beyond renal osteodystrophy. These updated guidelines clearly underline the need to improve a non-invasive approach to these bone disorders in order to guide treatment decisions aimed at not only controlling CKD-MBD but also decreasing the risk of fracture. In this report, we review the current role of the most often clinically used or promising biochemical circulating biomarkers such as parathyroid hormone, alkaline phosphatases, and other biochemical markers of bone activity as alternatives to some aspects of bone histomorphometry. We also mention the potential role of classic and new imaging techniques for CKD patients. Information on many aspects is still scarce and heterogeneous, but many of us consider that it is indeed time for action, recognizing our definitely limited ability to base certain treatment decisions only on our current non-comprehensive knowledge.

The prevalence of aluminum (Al) intoxication has declined over the past 3 decades. However, different groups still report on the diagnosis of Al in bone. Prolonged and low-intensity exposures to Al may not be captured by serum Al measurements, preventing its proper diagnosis. We hypothesize that bone Al accumulation may be related to bone and cardiovascular events in the current Era. To detect the diagnosis of bone Al accumulation; to explore bone and cardiovascular consequences of Al accumulation. This is a sub-analysis of The Brazilian Registry of Bone Biopsy, a prospective, multicentre cohort, with a mean follow-up of 3.4 years, including patients with CKD undergoing bone biopsy; bone fracture and major cardiovascular events (MACE) were adjudicated; Al accumulation was identified by solochrome-azurine staining; history of previous Al accumulation was registered based on information provided by the nephrologist who performed the bone biopsy; bone histomorphometry parameters, clinical data, and general biochemistry were registered. 275 individuals were considered; 96 (35%) patients have diagnosed with bone Al accumulation and were younger [50 (41-56) vs. 55 (43-61) years; p = 0.026], had lower body mass index [23.5 (21.6-25.5) vs. 24.3 (22.1-27.8) kg/m2; p = 0.017], higher dialysis vintage [108 (48-183) vs. 71 (28-132) months; p = 0.002], presented pruritus [23 (24%) vs. 20 (11%); p = 0.005], tendon rupture [7 (7%) vs. 3 (2%); p = 0.03) and bone pain [2 (0-3) vs. 0 (0-3) units; p = 0.02]. Logistic regression reveals that prior bone Al accumulation [OR: 4.517 (CI: 1.176-17.353); p = 0.03] and dialysis vintage [OR: 1.003 (CI: 1.000-1.007); p = 0.046] as independent determinants of bone Al accumulation; minor perturbations in dynamic bone parameters and no differences in bone fractures rate were noted; MACE was more prevalent in patients with bone Al accumulation [21 (34%) vs. 23 (18%) events; p = 0.016]. Cox regression shows the actual/prior diagnosis of bone Al accumulation and diabetes mellitus as independent predictors for MACE: [HR = 3.129 (CI: 1.439-6.804; p = 0.004) and HR = 2.785 (CI: 1.120-6.928; p = 0.028]. An elevated proportion of patients have bone Al accumulation, associated with a greater prevalence of bone pain, tendon rupture, and pruritus; bone Al accumulation was associated with minor perturbations in renal osteodystrophy; actual/prior diagnosis of bone Al accumulation and diabetes mellitus were independent predictors for MACE.

The health and productivity of animals, as well as farmers’ financial well-being, can be significantly impacted by cattle illnesses. Accurate and timely diagnosis is therefore essential for effective disease management and control. In this study, we consider the development of models and algorithms for diagnosing diseases in cattle based on Sugeno’s fuzzy inference. To achieve this goal, an analytical review of mathematical methods for diagnosing animal diseases and soft computing methods for solving classification problems was performed. Based on the clinical signs of diseases, an algorithm was proposed to build a knowledge base to diagnose diseases in cattle. This algorithm serves to increase the reliability of informative features. Based on the proposed algorithm, a program for diagnosing diseases in cattle was developed. Afterward, a computational experiment was performed. The results of the computational experiment are additional tools for decision-making on the diagnosis of a disease in cattle. Using the developed program, a Sugeno fuzzy logic model was built for diagnosing diseases in cattle. The analysis of the adequacy of the results obtained from the Sugeno fuzzy logic model was performed. The processes of solving several existing (model) classification and evaluation problems and comparing the results with several existing algorithms are considered. The results obtained enable it to be possible to promptly diagnose and perform certain therapeutic measures as well as reduce the time of data analysis and increase the efficiency of diagnosing cattle. The scientific novelty of this study is the creation of an algorithm for building a knowledge base and improving the algorithm for constructing the Sugeno fuzzy logic model for diagnosing diseases in cattle. The findings of this study can be widely used in veterinary medicine in solving the problems of diagnosing diseases in cattle and substantiating decision-making in intelligent systems.

Bone biopsy is the gold standard for characterization of renal osteodystrophy (ROD). However, the classification of the subtypes of ROD based on histomorphometric parameters is not unambiguous and the range of normal values for turnover differ in different publications. 18F-Sodium Fluoride positron emission tomography (18F-NaF PET) is a dynamic imaging technique that measures turnover. 18F-NaF PET has previously been shown to correlate with histomorphometric parameters. In this cross-sectional study, 26 patients on dialysis underwent a 18F-NaF PET and a bone biopsy. Bone turnover-based classification was assessed using Malluche’s historical reference values for normal bone turnover. In unified turnover-mineralization-volume (TMV)-based classification, the whole histopathological picture was evaluated and the range for normal turnover was set accordingly. Fluoride activity was measured in the lumbar spine (L1–L4) and at the anterior iliac crest. On the basis of turnover-based classification of ROD, 12% had high turnover and 61% had low turnover bone disease. On the basis of unified TMV-based classification of ROD, 42% had high turnover/hyperparathyroid bone disease and 23% had low turnover/adynamic bone disease. When using unified TMV-based classification of ROD, 18F-NaF PET had an AUC of 0.86 to discriminate hyperparathyroid bone disease from other types of ROD and an AUC of 0.87, for discriminating adynamic bone disease. There was a disproportion between turnover-based classification and unified TMV-based classification. More research is needed to establish normal range of bone turnover in patients with CKD and to establish the role of PET imaging in ROD.

Background:Renal Osteodystrophy (ROD) in chronic kidney disease (CKD) patients is diagnosed by bone biopsy and histomorphometric analysis. Whether the subtype of ROD contributes to fracture risk in CKD is not currently known since bone biopsies are not commonly performed. Fracture Risk Assessment (FRAX®) predicts 10-year fracture risk, but it can underestimate fracture risk in CKD and some adjustments may be needed [1].Objectives:To evaluate the fracture risk and the incidence of fractures in patients with predialysis CKD. To estimate the accuracy of FRAX® in this population and the relationship of ROD subtypes with fracture risk and occurrence of fractures.Methods:This is a retrospective study that enrolled 54 patients (40-89 years old) followed in a predialysis clinic between 2014-2023. Blood tests, bone biopsies and histomorphometric analysis were performed at the beginning of follow-up. Data from dual x-ray absorptiometry (DXA) scan were collected if available. FRAX® without bone mineral density (BMD) was calculated with the web-based FRAX® tool (portuguese version). Information regarding clinical evident fractures was recorded from clinical registries. Radiographies of the thoracic and/or lumbar spine were evaluated to detect asymptomatic vertebral fractures.Results:Median follow-up time was 7,5±3 years. Mean age at the time of bone biopsy was 65,4±9,8 years old and the majority had CKD stage 4 (53,7%). During follow-up, 20 (37%) patients progressed to kidney replacement therapy and 5 (9,3%) died. DXA scan was performed in 26 patients (48,1%) and 5 had osteoporosis (T-score ≤-2,5). Median FRAX® was 3,2% (1,9-5,1) for major fracture risk and 0,9% (0,4-1,9) for hip fracture. When including CKD as secondary osteoporosis, median FRAX® was 4,6% (2,7-7,6) for major fracture risk and 1,5% (0,6-3,4) for hip fracture. A total of 14 (25,9%) patients achieved the intervention threshold (FRAX® major fracture risk ≥11% and/or hip fracture risk ≥3%) when including CKD as secondary osteoporosis but only 3 (5,6%) patients were in the high-risk group with FRAX® without adjustments. Two patients sustained clinical evident fractures. Radiographies of 51 patients were reviewed and asymptomatic vertebral fractures were identified in 3 (5,9%). High-fracture risk calculated by FRAX® was more prevalent in the group who sustained fractures, but this difference was only statistically significant when considering CKD as secondary osteoporosis (80% vs 22,7%, p=0,019). DXA scan results were similar between the two groups (Table 1). Area under the curve (AUC) for FRAX® without adjustments was 0,886 (CI 95% 0,781-0,992) and 0,882 (CI 95% 0,777-0,987) with CKD as secondary osteoporosis (Table 2). The histomorphometric analysis showed that 40,7% (n=22) patients had normal bone histology, 37% (n=20) low bone turnover (BT) with normal mineralization (adynamic bone disease) and 22,3% (n=12) high BT with normal mineralization (hyperparathyroid bone disease). The histomorphometric subtypes did not correlate with the incidence of fractures nor had significant differences in the fracture risk calculated by FRAX® and BMD evaluated by DXA.Conclusion:In our study, there were no differences in the fracture risk or occurrence of fractures in the subtypes of ROD. This is in agreement with previous series including bone biopsies and can corroborate that some associations of high fracture risk with PTH levels <100ng/mL may be driven by other factors that influence PTH levels besides adynamic bone disease alone [2]. FRAX® showed an overall good diagnostic accuracy for predicting fractures in predialysis CKD. However, considering CKD a cause of secondary osteoporosis improved the sensibility of FRAX® in this population. Further studies with a larger population are needed to validate these conclusions.REFERENCES:[1] Evenepoel, P., et al., European Consensus Statement on the diagnosis and management of osteoporosis in chronic kidney disease stages G4-G5D. Nephrol Dial Transplant, 2021. 36(1): p. 42-59.[2] Haarhaus, M., et al., Differentiating the causes of adynamic bone in advanced chronic kidney disease informs osteoporosis treatment. Kidney Int, 2021. 100(3): p. 546-558.Acknowledgements:NIL.Disclosure of Interests:None declared.