Notice bibliographique
Résumé
The quest to find the perfect treatment for male LUTS has consumed urologists for decades. On the medical front, the battle ground has been α-blockers with varying receptor selectivity and tolerability, 5-α-reductase inhibitors which inhibit different isoforms, anticholinergics (which transitioned from contraindication to cutting edge) and, more recently, β3 agonists and phosphodiesterase-5 (PDE5) inhibitors. Similarly, the surgical management of BPH (which may or may not be the cause of male LUTS) has seen numerous procedures and operations investigated and marketed with promises to cut, burn, cook, freeze, enucleate or ablate with a laser, pressure wash, steam, cut off the blood flow, staple open, stent open or surgically remove adenoma, all with the goal of reducing urinary symptoms. Nagasubramanian et al. [1] investigated whether the addition of tadalafil 5 mg to tamsulosin 0.4 mg offers a benefit over tamsulosin 0.4 mg alone. This randomized double-blind placebo-controlled study was carried out in men who were aged 60 years, on average, with moderate symptom scores (IPSS 15–16/35), and who were mostly dissatisfied with urinary quality of life; flow rates were low but reasonably maintained (~ 10 mL/s), and most of the men had post-void residual urine volumes < 100 mL. The addition of daily tadalafil resulted in a 1.7-point improvement in the IPSS, a 0.7-point improvement in urinary quality of life, and an almost 2-mL/s improvement in peak flow (and not surprisingly an improvement in erectile function). The improvement in flow rate is notable as an objective measure of effect, and not something that has been shown consistently with PDE5 inhibitors. A recent systematic review found only three out of nine randomized trials showed a significant improvement in flow rate when PDE5 inhibitors plus α-blockers were compared with α-blockers alone [2]. There are now numerous combinations of medical therapy that can be offered to men with LUTS, and it is useful to look to some of the recent meta-analyses to understand the magnitude of effect these medications may offer, and then consider whether the additional medication is worth the added expense, possible medication interactions and potential side effects. Figure 1 summarizes the changes in the IPSSs from various meta-analyses which studied different combinations of α-blockers and PDE5 inhibitors [2-5], with fairly consistent results: either an α-blocker or a PDE5 inhibitor helps improve LUTS to a similar degree, and the addition of one to the other improves LUTS a little bit more. The challenge is that these improvements are modest, and a smaller proportion of patients are actually ‘responders’ (those with an improvement above the minimally clinically important threshold of the IPSS and perceptible to the patient). With all the combinations of medical therapy, it is becoming increasingly difficult to keep track of the various possibilities. A nice network meta-analysis [6] (although now 6 years old) addressed the question about the various permutations of medical therapy, and their conclusion was that an α-blocker plus a PDE5 inhibitor was best for improving LUTS, which mirrors the conclusion of the present study [1]. A better understanding of male LUTS clusters [7] now needs to be integrated with study of the various medical and surgical treatment options to more accurately tailor specific treatment to the right patient. None declared.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,002 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».