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Enregistrement W2329071125 · doi:10.1097/qai.0b013e3182718d4c

Prevalence and Risk Factors for Loss of Bone Mineral Density in Male Japanese Patients With HIV

2012· letter· en· W2329071125 sur OpenAlexaboutno aff
Ichiro Koga, Yusuke Yoshino, Takatoshi Kitazawa, Issei Kurahashi, Yasuo Ota

Notice bibliographique

RevueJAIDS Journal of Acquired Immune Deficiency Syndromes · 2012
Typeletter
Langueen
DomaineMedicine
ThématiqueHIV-related health complications and treatments
Établissements canadiensnon disponible
Organismes subventionnairesU.S. Department of Health and Human Services
Mots-clésBone mineralHuman immunodeficiency virus (HIV)MedicineBone densityRisk factorInternal medicineEnvironmental healthDemographyVirologyOsteoporosis

Résumé

récupéré en direct d'OpenAlex

To the Editors: As the mortality of HIV-infected individuals was improved by combination antiretroviral therapy (cART), opportunistic infections were replaced by long-term complications including loss of bone mineral density (BMD).1–9 It was first reported in 1999 and has emerged in the last decade10,11 and has probably placed HIV-infected individuals at higher risk of bone fractures.12,13 The causes are considered to be multifactorial and include HIV infection itself, body mass index (BMI), estimated glomerular filtration rate (eGFR), testosterone level, and hepatitis coinfection.14–17 Some articles link the use of protease inhibitors and the tenofovir (TDF) with lower BMD.18–20 Most of the articles associated with BMD loss in HIV-infected patients have been reported from North America, Europe, and Oceania. Accordingly, the BMD research on HIV-infected Asians is underrepresented. In this work, we focused on male Japanese HIV-infected patients and studied the prevalence and severity of BMD loss among them and attempted to determine clinical factors related to BMD loss. Forty male Japanese HIV-infected individuals aged from 21 to 70 years who visited the Teikyo University Hospital were enrolled in this study. This study was approved by the ethical committee of the Teikyo University School of Medicine, and the patients gave written informed consent. The patients underwent BMD analyses from March 2010 to February 2012 with the same dual energy X-ray absorptiometry scan (Discovery SI, Hologic Inc, Bedford, MA). Thirty-nine patients were analyzed in both the lumbar spines and bilateral femoral necks, whereas 1 patient was limited to the bilateral femoral necks. The BMD data of the lumbar spines and the smaller BMD value of the femoral necks were employed to calculate T-scores that were calculated as comparison with young normal reference value expressed as SD units. Osteopenia was defined as a T-score of between −1 and −2.5SD, and osteoporosis was defined as that of ≥ −2.5 negative score following the World Health Organization classification.21 Clinical factors were collected including age, height, body weight, BMI, smoking status, use of corticosteroid, CD4 cell counts, durations of cART, medication of nucleoside/nucleotide reverse transcriptase inhibitors, serum creatinine, bone alkaline phosphatase (BAP), eGFR, serum, and urine N-terminal telopeptide (NTx). The eGFR for Japanese male patients were calculated by 194 × serum creatinine−1.094 × age−0.287 (mL/min per 1.73 m2).22 To determine the high-risk groups, statistical differences of T-scores were calculated by using Wilcoxon signed ranks or Kruskal–Wallis test with the post hoc comparisons by the Dunnett test. The correlations between T-scores and each variable were examined by a linear regression employing the method of least squares. A multiple regression analysis was conducted by employing these variables with a P value <0.1 to predict BMD loss. All the analyses were performed by JMP version 8.0.1 (SAS Institute Inc, United States). The median age of the patients was 39 years. Their median height and body weight were 169.3 cm and 65.0 kg, respectively. Twenty-three patients were ≤170 cm, and 14 were <60 kg. The median CD4 count was 396/μL. Twenty-seven were on cART, and median duration of cART was 2.9 years. Five have been continued on cART for >10 years. Twelve out of 27 took TDF/emtricitabine (FTC), and 13 took abacavir/lamivudine (3TC). The median and interquartile ranges of BMD and T-scores in the lumbar spines and the femoral necks are summarized in Table 1. The median T-scores in the lumbar spines and the femoral necks were −0.8 and −1.2, respectively. The T-scores of the femoral necks were significantly lower than those of the lumbar spines (P = 0.0461). By employing the T-scores in the lumbar spines, the prevalence of osteopenia and osteoporosis was found to be 43.6% and 5.1%, respectively, and these percentages rose to 47.5% and 7.5%, respectively, if the least T-scores in the femoral necks were used. Moreover, the number (and percentage) of patients with osteopenia and osteoporosis were 21 (52.5%) and 4 (10%), respectively, in at least 1 of the T-score measured in the lumbar spines or in the femoral necks.TABLE 1: The Prevalence of BMD LossSubgroup analyses of patients' baseline characteristics revealed that the group of patients aged 50 years or older was the only group that showed significantly lower T-scores of the lumbar spines. In contrast, high-risk groups that showed significantly lower T-scores of the femoral necks were patients aged 40 years or older, ≤170 cm in height, weighed ≤60 kg, those on cART, particularly those continuing cART for ≥10 years. There were no significant differences between the 2 groups divided based on the medication of nucleotide reverse transcriptase inhibitors or use of corticosteroid. Correlation between BMD loss and clinical factors was analyzed by univariate analyses. Age, height, body weight, and duration of cART showed correlation with T-scores of both the lumbar spines and the femoral necks. In addition, serum creatinine, BAP, and eGFR were related to BMD loss measured in the femoral necks. Urinary phosphate excretion showed a tendency of correlation to T-scores in the lumbar spines (P = 0.0511). Serum NTx, 25-hydroxyvitamin D, cystatin C, free testosterone, urinary NTx, and smoking status were not correlated to BMD loss. Those variables that showed correlation or tendency of correlation were employed in a multiple regression analysis. Age, BAP, and eGFR were determined as independent clinical factors of T-scores of the femoral necks, whereas urinary phosphate excretion was the only independent variable to the T-score of the lumbar spines (Table 2).TABLE 2: Independent Risk Factors of BMD LossOur study revealed that male Japanese HIV-infected patients are highly concomitant with low BMD. More than 60% of individuals were diagnosed with either osteopenia or osteoporosis. This is the first report from Asia, and the prevalence of low BMD in male Japanese HIV-infected patients is as high as that of previous reports from Europe, North America, or Oceania.11 Increased age, short stature, and low body weight indicated from our study are well-known risk factors for BMD loss.23 However, the age of these patients suffering from BMD loss is much younger, and the prevalence of BMD loss is significantly higher than that in the general population. It is reported previously that BMD in both the lumbar spines and the femoral necks decreases almost simultaneously in the general population of Japanese males.24 In our study, the prevalence of osteopenia and osteoporosis diagnosed by the BMD in the femoral necks is higher than that in the lumbar spines. A meta-analysis by Bolland et al25 showed consistent evidence of BMD loss especially among antiretroviral drug naive HIV-infected patients and that larger BMD loss were observed in the femoral necks than the lumbar spines. Osteoblast and osteoclast functions are influenced by a number of factors modulated during HIV infection and HIV itself or with other concomitant factors stimulate the progression of BMD loss.26,27 It is possible that progression of BMD loss accelerated by HIV infection proceeds primarily targeting on cortical bone tissues such as the femoral necks. A multiple regression analysis revealed that age, BAP, and eGFR are indicated as independent risk factors for BMD loss in the femoral necks. Decreased renal function is one of the risk factor for BMD loss among the general population. However, serum creatinine and eGFR remain within the normal range in many of our patients with BMD loss. We employed serum and urine NTx as markers for bone resorption and BAP as a marker for bone formation. Madeddu et al28 reported that Italian HIV-infected patients with BMD loss in the lumbar spines had a higher mean BAP level, although it was not statistically significant in men. BAP might be a predictor of BMD loss in patients with HIV, implying an accelerated bone turnover. Interestingly, urinary phosphate excretion was determined as an independent variable of T-scores of the lumbar spines by a multiple regression analysis (P = 0.0110). Urinary phosphate excretion is mainly regulated by NaPi cotransporters that express in the brush border membrane of proximal tubular epithelia.29 Although the mechanisms are unclear, it is hypothesized that HIV might have some effects on these transporters to stimulate excretion of phosphate. It has been investigated by both cross-sectional and longitudinal studies whether or not cART adds to the burden of metabolic bone disease in HIV infection with mixed conclusions.20 In our study, no significant differences were observed in BMD loss between TDF/FTC group and abacavir/3TC group. In conclusion, this is the first report on BMD loss in Asian HIV-infected patients. More than 60% of the patients are diagnosed as having osteopenia or osteoporosis. A multivariate regression analysis indicated that age, BAP, and eGFR are independent factors of BMD loss in the femoral necks, whereas urinary phosphate excretion is that of BMD loss of the lumbar spines. DXA scan examination not only in the lumbar spines but also in the femoral necks are recommended in patient more than 40 years old or those with increased BAP, decreased eGFR, or decreased urinary phosphate excretion. ACKNOWLEDGMENT The authors thank Dr. Greg J. German, University of Ottawa, for his time and efforts in proofreading this article.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,008

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,014
Tête enseignante GPT0,259
Écart entre enseignants0,245 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2012
Routes d'admission1
Résumé présentoui

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