Analysis of the clinical characteristics of tigecycline-induced hypofibrinogenemia

Development and validation of a risk prediction model for tigecycline-induced hypofibrinogenemia in septic patients: a retrospective cohort study

BACKGROUND

Tigecycline is widely used in China to treat multidrug-resistant bacterial infections, with hypofibrinogenemia being the most common adverse effect due to its impact on coagulation. Although a predictive model for tigecycline-induced hypofibrinogenemia has been developed, it lacks external validation. This study aims to construct a predictive model for the risk of tigecycline-induced hypofibrinogenemia in sepsis patients.

METHODS

This retrospective cohort study analyzed data from sepsis patients treated with tigecycline in the intensive care unit (ICU) of the People's Hospital of Inner Mongolia Autonomous Region between January 2018 and June 2024. Risk factors for tigecycline-induced hypofibrinogenemia were identified through univariate and multivariate logistic regression analyses. A nomogram prediction model was developed and externally validated using the MIMIC-IV database.

RESULTS

A total of 465 patients participated, with 411 in the training set and 54 in the external validation set. Independent risk factors for hypofibrinogenemia included age (OR: 1.02, p = 0.009), duration of tigecycline treatment (OR: 1.33, p < 0.001), baseline fibrinogen level (OR: 0.65, p < 0.001), baseline platelet count (OR: 0.99, p = 0.025), and the presence of tumors (OR: 2.17, p = 0.021). The model demonstrated an AUC of 0.85 (95% CI: 0.81-0.89) in the training cohort and 0.83 (95% CI: 0.71-0.95) in the validation cohort. Calibration curves for both cohorts showed strong agreement between predicted and observed hypofibrinogenemia. Decision curve analysis (DCA) indicated good clinical applicability of the model.

CONCLUSION

The developed predictive model effectively predicts the risk of tigecycline-induced hypofibrinogenemia in sepsis patients, providing valuable information for clinical decision-making.

Pharmacovigilance analysis of drug-induced hypofibrinogenemia using the FDA Adverse Event Reporting System

BACKGROUND

Drug-induced hypofibrinogenemia has received increasing scrutiny; however, the specific drugs involved remain poorly characterized. Hypofibrinogenemia can have significant clinical implications, including increased bleeding risks.

AIM

This study aimed to utilize the FDA Adverse Event Reporting System (FAERS) to identify and analyze drugs frequently implicated in drug-induced hypofibrinogenemia.

METHOD

A disproportionality analysis was conducted using FAERS data from January 2004 to March 2024. Various statistical tools were used, including the Reporting Odds Ratio (ROR), Proportional Reporting Ratio, Medicines and Healthcare Products Regulatory Agency metrics, and Bayesian confidence propagation neural network.

RESULTS

The analysis included 17,627,340 cases involving 52,373,206 adverse events, with 1,661 cases identified as hypofibrinogenemia. The top five drugs associated with hypofibrinogenemia by case number were methotrexate (124 cases), tigecycline (119 cases), tocilizumab (100 cases), pegaspargase (83 cases), and alteplase (57 cases). The drugs ranked by signal strength based on ROR included eravacycline (ROR 2173.84, 95% CI 1208.80-3909.30), tigecycline (ROR 747.34, 95% CI 619.03-902.24), crotalidae polyvalent immune Fab (ROR 407.67, 95% CI 291.07-570.99), pegaspargase (ROR 216.06, 95% CI 173.15-269.61), and asparaginase (ROR 184.93, 95% CI 132.18-258.72).

CONCLUSION

This analysis of FAERS data identified 52 drugs associated with hypofibrinogenemia, most (88.5%) of which do not mention this risk in their prescribing information. These findings demonstrate the need for the monitoring of blood fibrinogen and may serve as a reference for the explore of the characteristics and underlying mechanism of drug-induced hypofibrinogenemia in the real world.

Optimizing Treatment Strategies for Carbapenem-Resistant Acinetobacter Baumannii-Associated Pneumonia: A Multicenter Study in Chinese Hospitals

Purpose

To evaluate the clinical outcomes and safety of tigecycline (TGC) plus cefoperazone/sulbactam (CPS) or TGC monotherapy in patients with hospital-acquired pneumonia (HAP) caused by Carbapenem-Resistant Acinetobacter baumannii (CRAB).

Methods

This was a retrospective analysis of multicenter data from 62 Chinese hospitals with CRAB HAP. Risk factors for receiving TGC with CPS therapy and predictors of mortality were assessed using multivariate logistic and Cox regression analyses, respectively. Propensity score matching (PSM) evaluated the efficacy and safety of antimicrobial regimens.

Results

A total of the 180 patients were included, with 95 receiving TGC monotherapy and 85 receiving combination therapy. Multivariate logistic regression analysis revealed that older age (P = 0.011), and intensive care unit (ICU) admission (P = 0.007) were significant risk factors for combination therapy. Multivariate Cox regression demonstrated that combination therapy was associated with a significantly higher risk of 90-day mortality (P = 0.031). Patients in the standard-dose TGC (SDT) plus CPS subgroup had significantly higher rates of SOFA scores ≥ 7 (P = 0.009) and MV used (P = 0.028), as well as higher 30-/90-day mortality compared to high-dose TGC (HDT) plus CPS group. TGC plus CPS significantly reduced CRP levels (P = 0.009), while the variations in ALT, TBIL, Cr, Hb, and PLT levels did not differ between different antimicrobial regimens after PSM.

Conclusion

HDT and CPS combination therapy was more effective in patients with advanced age and more severe condition. Safety profiles of different antimicrobial regimens were similar with liver, kidneys, and coagulation functions.

Tigecycline and Hypoglycemia, When and How?

Objective: To describe the clinical characteristics of hypoglycemia that develop with tigecycline therapy and to review and summarize the current evidence of this uncommonly occurring metabolic adverse effect of tigecycline therapy. Underlying risk factors and potential mechanisms are also discussed. Data source: A 3-phase literature search was performed. In phase 1, the Cochrane Central Register of Controlled Trials (CENTRAL) Library, MEDLINE, and Embase electronic databases were searched for hypoglycemia and tigecycline, published from inception until August 2023. In phase 2, MEDLINE was searched for tigecycline randomized controlled trials and results were manually screened for hypoglycemia. In phase 3, the US Food and Drug Administration Adverse Event Reporting System public dashboard was searched for reports on tigecycline and hypoglycemia from June 2005 until July 2023. Study selection and data extraction: Relevant English-language citations and those conducted in humans were considered. Relevance to patient care and clinical practice: Hypoglycemia of various causes is an independent mortality risk. This review raises awareness among clinicians about the possibility of hypoglycemia with tigecycline therapy. Conclusion: Data on tigecycline-related hypoglycemia are scarce. Hypoglycemia may occur at any time during tigecycline therapy and can be severe and persist for days after tigecycline cessation. Renal dysfunction or renal replacement therapy may predispose to severe hypoglycemia during tigecycline therapy. Tigecycline-related hypoglycemia may develop in patients with or without diabetes mellitus and appears independent of insulin or antidiabetic agents. Intravenous dextrose showed efficacy in the restoration of euglycemia. Studies are needed to determine whether tigecycline-related hypoglycemia is iatrogenic or spontaneous.