MétaCan
Menu
Retour à la cohorte
Enregistrement W4247899321 · doi:10.1002/ebch.1927

Procalcitonin to initiate or discontinue antibiotics in acute respiratory tract infections

2013· review· en· W4247899321 sur OpenAlexaff
Philipp Schüetz, Beat P. Müller‐Stich, Mirjam Christ‐Crain, Daiana Stolz, Michael Tamm, Lila Bouadma, Charles Edouard Luyt, Michel Wolff, Jean Chastre, Florence Tubach, Kristina B Kristoffersen, Olaf Burkhardt, Tobias Welte, Stefan Schröder, Vandack Nobre, Wei Long, Neera Bhatnagar, Heiner C. Bucher, Matthias Briel

Notice bibliographique

RevueEvidence-Based Child Health A Cochrane Review Journal · 2013
Typereview
Langueen
DomaineMedicine
ThématiqueSepsis Diagnosis and Treatment
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésProcalcitoninMedicineAntibioticsIntensive care medicineRespiratory tract infectionsRespiratory tractRespiratory systemInternal medicineSepsisMicrobiologyBiology

Résumé

récupéré en direct d'OpenAlex

Abstract Background Acute respiratory infections (ARIs) comprise a large and heterogeneous group of infections including bacterial, viral and other aetiologies. In recent years, procalcitonin ‐ the prohormone of calcitonin ‐ has emerged as a promising marker for the diagnosis of bacterial infections and for improving decisions about antibiotic therapy. Several randomised controlled trials (RCTs) have demonstrated the feasibility of using procalcitonin for starting and stopping antibiotics in different patient populations with acute respiratory infections and different settings ranging from primary care to emergency departments (EDs), hospital wards and intensive care units (ICUs). Objectives The aim of this systematic review based on individual patient data was to assess the safety and efficacy of using procalcitonin for starting or stopping antibiotics over a large range of patients with varying severity of ARIs and from different clinical settings. Search methods We searched the Cochrane Central Register of Controlled Trials (CENTRAL 2011, Issue 2) which contains the Acute Respiratory Infections Group's Specialised Register, MEDLINE (1966 to May 2011) and EMBASE (1974 to May 2011) to identify suitable trials. Selection criteria We included RCTs of adult participants with ARIs who received an antibiotic treatment either based on a procalcitonin algorithm or usual care/guidelines. Trials were excluded if they exclusively focused on paediatric patients or if they used procalcitonin for another purpose than to guide initiation and duration of antibiotic treatment. Data collection and analysis Two teams of review authors independently evaluated the methodology and extracted data from primary studies. The primary endpoints were all‐cause mortality and treatment failure at 30 days. For the primary care setting, treatment failure was defined as death, hospitalisation, ARI‐specific complications, recurrent or worsening infection, and patients reporting any symptoms of an ongoing respiratory infection at follow‐up. For the ED setting, treatment failure was defined as death, ICU admission, re‐hospitalisation after index hospital discharge, ARI‐associated complications, and recurrent or worsening infection within 30 days of follow‐up. For the ICU setting, treatment failure was defined as death within 30 days of follow‐up. Secondary endpoints were antibiotic use (initiation of antibiotics, duration of antibiotics and total exposure to antibiotics (total amount of antibiotic days divided by total number of patients)), length of hospital stay for hospitalised patients, length of ICU stay for critically ill patients, and number of days with restricted activities within 14 days after randomisation for primary care patients. For the two co‐primary endpoints of all‐cause mortality and treatment failure, we calculated odds ratios (ORs) and 95% confidence intervals (CIs) using multivariable hierarchical logistic regression. The hierarchical regression model was adjusted for age and clinical diagnosis as fixed‐effect. The different trials were added as random‐effects into the model. We fitted corresponding linear regression models for antibiotic use. We conducted sensitivity analyses stratified by clinical setting and ARI diagnosis to assess the consistency of our results. Main results We included 14 trials with 4221 participants. There were 118 deaths in 2085 patients (5.7%) assigned to procalcitonin groups compared to 134 deaths in 2126 control patients (6.3%) (adjusted OR 0.94, 95% CI 0.71 to 1.23). Treatment failure occurred in 398 procalcitonin group patients (19.1%) and in 466 control patients (21.9%). Procalcitonin guidance was not associated with increased mortality or treatment failure in any clinical setting, or ARI diagnosis. These results proved robust in various sensitivity analyses. Total antibiotic exposure was significantly reduced overall (median (interquartile range) from 8 (5 to 12) to 4 (0 to 8) days; adjusted difference in days, ‐3.47, 95% CI ‐3.78 to ‐3.17, and across all the different clinical settings and diagnoses. Authors' conclusions Use of procalcitonin to guide initiation and duration of antibiotic treatment in patients with ARI was not associated with higher mortality rates or treatment failure. Antibiotic consumption was significantly reduced across different clinical settings and ARI diagnoses. Further high‐quality research is needed to confirm the safety of this approach for non‐European countries and patients in intensive care. Moreover, future studies should also establish cost‐effectiveness by considering country‐specific costs of procalcitonin measurement and potential savings in consumption of antibiotics and other healthcare resources, as well as secondary cost savings due to lower risk of side effects and reduced antimicrobial resistance. Procalcitonin testing to initiate or discontinue antibiotics in acute respiratory tract infections Unnecessary antibiotic use significantly contributes to increasing bacterial resistance, medical costs and the risk of drug‐related adverse events. The blood marker procalcitonin increases in bacterial infections and decreases when patients recover from the infection. Hence, procalcitonin may be used to support clinical decision making for the initiation and discontinuation of antibiotic therapy in patients with a clinical suspicion of infection. Randomised controlled trials have demonstrated that such a strategy works, particularly in patients with an infection of the respiratory tract. However, most of these individual studies did not include enough patients to allow for a conclusive assessment about safety (low statistical power). Thus, the risk for mortality and severe complications associated with procalcitonin‐guided decision making remained unclear. This systematic review included individual patient data from 14 randomised controlled trials with a total of 4211 participants. When looking at these combined data, we found no increased risk for all‐cause mortality or treatment failure when procalcitonin was used to guide initiation and duration of antibiotic treatment in participants with acute respiratory infections compared to control participants. However, we found a consistent reduction of antibiotic use, mainly due to lower prescription rates in primary care and lower duration of antibiotic courses in emergency department and intensive care unit patients. This analysis is limited to adult patients with respiratory infections excluding patients who were immuno‐compromised (i.e. HIV positive, those receiving immuno‐suppressive therapies or chemotherapy). Most trials were conducted in Europe and China and similar studies in other countries including the United States are warranted.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,806
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,003
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0070,002
Bibliométrie0,0010,002
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,003
Charge utile insuffisante (le modèle a refusé de juger)0,0010,001

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 Opus0,289
Tête enseignante GPT0,512
Écart entre enseignants0,223 · 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 tête enseignante, pas un consensus.

Devis d'étudeAutre devis
Domainenon disponible
GenreSynthèse

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

En bref

Citations109
Publié2013
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueEvidence-Based Child Health A Cochrane Review JournalMême sujetSepsis Diagnosis and TreatmentTravaux en français237 207