Variation of adverse drug events in different settings in Africa: a systematic review.

BACKGROUND: Adverse drug events (ADEs) represent challenges affecting Africa's healthcare systems owing to the increased healthcare expenditure and negative health outcomes of ADEs. OBJECTIVES: We aimed to systematically review published studies on ADEs and synthesize the existing evidence of ADE prevalence in Africa. METHODS: Studies reporting on ADE occurrence in African settings and published from Jan 1, 2000 to Oct 1, 2023 were identified by searching PubMed, EBSCO, Science Direct, and Web of Science. Studies that either articulately investigated ADEs caused by clinical condition (such as HIV patients) or ADEs caused by exposure to specific drug(s) (such as antibiotics) were considered specific and the remaining were general. Grouped ADE prevalence rates were described using median and interquartile range (IQR). PROSPERO registration (CRD42022374095). RESULTS: We included 78 observational studies from 15 African countries that investigated the prevalence of ADEs leading to hospital admissions (17 studies), developed during hospitalizations (30 studies), and captured in the outpatient departments (38 studies) or communities (4 studies). Twelve studies included multiple settings. The median prevalence of ADE during hospitalization was 7.8% (IQR: 4.2-21.4%) and 74.2% (IQR: 54.1-90.7%) in general and specific patients, respectively. The ADE-related fatality rate was 0.1% and 1.3% in general and specific patients. The overall median prevalence of ADEs leading to hospital admissions was 6.0% (IQR: 1.5-9.0%); in general, patients and the median prevalence of ADEs in the outpatient and community settings were 22.9% (IQR: 14.6-56.1%) and 32.6% (IQR: 26.0-41.3%), respectively, with a median of 43.5% (IQR: 16.3-59.0%) and 12.4% (IQR: 7.1-28.1%) of ADEs being preventable in general and specific patients, respectively. CONCLUSIONS: The prevalence of ADEs was significant in both hospital and community settings in Africa. A high ADE prevalence was observed in specific patients, emphasizing important areas for improvement, particularly in at-risk patient groups (e.g., pediatrics, HIV, and TB patients) in various settings. Due to limited studies conducted in the community setting, future research in this setting is encouraged.

A NAC nomogram to predict the probability of three-month unfavorable outcome in Chinese acute ischemic stroke patients treated with mechanical thrombectomy.

BACKGROUND AND PURPOSE: Mechanical thrombectomy (MT) is a standard care for most acute ischemic stroke (AIS) patients. For AIS patients underwent MT, predicting the patients at high risk of unfavorable outcome and adjusting therapeutic strategies accordingly can greatly improve patient outcomes. We aimed to develop and validate a nomogram for individualized prediction of Chinese AIS patients underwent MT. METHODS: We conducted a multicenter prospective study including 238 AIS patients who underwent MT from January 2014 to December 2018. The main outcome measure was three-month unfavorable outcome (modified Rankin Scale 3-6). A nomogram was generated based on multivariate logistic model. We assessed the discriminative performance by using the area under the receiver-operating characteristic curve and calibration of risk prediction model by using the Hosmer-Lemeshow test. RESULTS: In NAC nomogram, NIHSS (National Institutes of Health Stroke Scale) score on admission (OR: 1.193, p < 0.0001), Age (OR: 1.025, p = 0.037) and Creatinine (OR: 1.028, p < 0.0001) remained independent predictors of 3-month unfavorable outcome in Chinese AIS patients treated with MT. The NAC nomogram exhibited an area under the curve of 0.816 for predicting functional impairment. Calibration was good (p = 0.560 for the Hosmer-Lemeshow test). CONCLUSIONS: The NAC nomogram is the first nomogram developed and validated in Chinese AIS patients treated with MT and it may be used to predict 3 months unfavorable outcome for these patients.

Corrigendum: A SCANO Nomogram for Individualized Prediction of the Probability of 1-Year Unfavorable Outcomes in Chinese Acute Ischemic Stroke Patients.

[This corrects the article on p. 531 in vol. 11, PMID: 32695060.].

A SCANO Nomogram for Individualized Prediction of the Probability of 1-Year Unfavorable Outcomes in Chinese Acute Ischemic Stroke Patients.

Background and Purpose: Accurate prediction of functional outcomes after stroke would provide evidence for reasonable poststroke management. This study aimed to develop and validate a nomogram for individualized prediction of 1-year unfavorable outcomes in Chinese acute ischemic stroke (AIS) patients. Methods: We gathered AIS patients at the National Advanced Stroke Center of Nanjing First Hospital (China) between August 2014 and May 2017 within 12 h of symptom onset. The outcome measure was 1-year unfavorable outcomes (modified Rankin Scale 3-6). The patients were randomly stratified into the training (66.7%) and testing (33.3%) sets. With the training data, pre-established predictors were entered into a logistic regression model to generate the nomogram. Predictive performance of the nomogram model was evaluated in the testing data by calculating the area under the receiver operating characteristic curve (AUC-ROC), Brier score, and a calibration plot. Results: A total of 807 patients were included into this study, and 262 (32.5%) of them had unfavorable outcomes. Systolic blood pressure, Creatinine, Age, National Institutes of Health Stroke Scale (NIHSS) score on admission, and fasting blood glucose were significantly associated with unfavorable outcomes and entered into the SCANO nomogram. The AUC-ROC of the SCANO nomogram in the testing set was 0.781 (Brier score: 0.166; calibration slope: 0.936; calibration intercept: 0.060). Conclusions: The SCANO nomogram is developed and validated in Chinese AIS patients to firstly predict 1-year unfavorable outcomes, which is simple and convenient for the management of stroke patients.

The association between smoking and unfavorable outcomes in acute ischemic stroke patients with mechanical thrombectomy.

INTRODUCTION: Little is known about the relationship between smoking and clinical outcomes in acute ischemic stroke (AIS) patients undergoing mechanical thrombectomy (MT). The outcomes could depend on different stroke subtypes. The aim of this study was to investigate whether smoking affected differently the outcomes in patients with different stroke subtypes who received MT. METHODS: AIS patients who underwent MT were prospectively enrolled from three hospitals between January 2014 and December 2018. Smokers were defined as current users of cigarettes. The stroke subtypes were classified according to TOAST criteria. Outcome measurements included treatment effects, intracerebral hemorrhage (ICH), and functional outcomes at 3 months. The effects of smoking on outcomes were assessed by logistic regression analysis. RESULTS: A total of 128 AIS patients with MT were enrolled, including 64 smokers and 64 non-smokers. Logistic regression analysis indicated that smoking was related to higher risk of In-hospital ICH (OR=4.31; 95% CI: 1.10-16.96; p=0.036) in patients with cardioembolism subtype. Furthermore, smoking was also associated with lower rates of mild stroke at discharge (OR=0.07; 95% CI: 0.02-0.31; p<0.001) and functional independence (OR=0.13; 95% CI: 0.03-0.56; p=0.006) in patients with cardioembolism subtype. CONCLUSIONS: In AIS patients undergoing MT, smoking could be related to a higher risk of In-hospital ICH and lower rates of mild stroke at discharge and functional independence if their stroke subtype is cardioembolism.

A NADE nomogram to predict the probability of 6-month unfavorable outcome in Chinese patients with ischemic stroke.

BACKGROUND: Early prediction of unfavorable outcome after ischemic stroke is of great significance to the clinical and therapeutic management. A nomogram is a better visual tool than earlier models and prognostic scores to predict clinical outcomes, which incorporates different factors to develop a graphic continuous scoring system and calculates accurately the risk probability of poor outcome entirely based on individual characteristics. However, to date, no nomogram models have been found to predict the probability of 6-month poor outcome after ischemic stroke. We aimed to develop and validate a nomogram for individualized prediction of the probability of 6-month unfavorable outcome in Chinese patients with ischemic stroke. METHODS: Based on the retrospective stroke registry, a single-center study which included 499 patients from May, 2013 to May, 2018 was conducted in Nanjing First Hospital (China) for ischemic stroke within 12 h of symptoms onset. The main outcome measure was 6-month unfavorable outcome (mRS > 2). To generate the nomogram, NIHSS score on admission, Age, previous Diabetes mellitus and crEatinine (NADE) were integrated into the model. We assessed the discriminative performance by using the area under the curve (AUC) of receiver-operating characteristic (ROC) and calibration of risk prediction model by using the Hosmer-Lemeshow test. RESULTS: A visual NADE nomogram was constructed that NIHSS score on admission (OR: 1.190, 95%CI: 1.125-1.258), age (OR: 1.068, 95%CI: 1.045-1.090), previous diabetes mellitus (OR: 1.995, 95%CI: 1.236-3.221) and creatinine (OR: 1.010, 95%CI: 1.002-1.018) were found to be significant predictors of 6-month unfavorable outcome after acute ischemic stroke in Chinese patients. The AUC-ROC of nomogram was 0.791. Calibration was good (p = 0.4982 for the Hosmer-Lemeshow test). CONCLUSION: The NADE is the first nomogram developed and validated in Chinese ischemic stroke patients to provide an individual, visual and precise prediction of the risk probability of 6-month unfavorable outcome.

Safety and Efficacy of Tirofiban Combined With Mechanical Thrombectomy Depend on Ischemic Stroke Etiology.

Background and Purpose: The clinical use of tirofiban for patients with acute ischemic stroke (AIS) who underwent mechanical thrombectomy (MT) remains controversial. We aimed to evaluate the safety and efficacy of tirofiban combined with MT in AIS patients. Methods: Patients with AIS who underwent MT from January 2014 to December 2018 were enrolled in three stroke units in China. Subgroup analyses were performed based on stroke etiology which was classified according to the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) criteria. Safety outcomes were in-hospital intracerebral hemorrhage (ICH), symptomatic intracerebral hemorrhage (sICH) and mortality at 3-month. Efficacy outcomes were favorable functional outcome and functional independence at 3-month and neurological improvement at 24 h, 3 d and discharge. Results: In patients with large artery atherosclerosis (LAA) stroke, multivariate analyses revealed that tirofiban significantly decreased the odds of in-hospital ICH (adjusted OR = 0.382, 95% CI 0.180-0.809) and tended to increase the odds of favorable functional outcome at 3-month (adjusted OR = 3.050, 95% CI 0.969-9.598). By contrast, in patients with cardioembolism (CE) stroke, tirofiban was not associated with higher odds of favorable functional outcome at 3-month (adjusted OR = 0.719, 95% CI 0.107-4.807), but significantly decreased the odds of neurological improvement at 24 h and 3d (adjusted OR = 0.185, 95% CI 0.047-0.726; adjusted OR = 0.268, 95% CI 0.087-0.825). Conclusions: Tirofiban combined with MT appears to be safe and effective in LAA patients, but has no beneficial effect on CE patients.

External Validation of START nomogram to predict 3-Month unfavorable outcome in Chinese acute stroke patients.

BACKGROUND: Recently, the NIHSS STroke Scale score, Age, pre-stroke mRS score, onset-to-treatment Time (START nomogram) predicts 3-month functional outcome after intravenous thrombolysis in ischemic stroke patients. However, this model has not yet been an external validation. We aim to validate the performance of START nomogram. METHODS: Data were derived from the stroke center of the Nanjing First Hospital (China). Patients who lacked the necessary data to calculate the nomogram and missed 3-month modified Ranking scale scores were excluded. Modified Rankin Scale score more than 2 at 3-month was assessed as an unfavorable outcome. We used areas under the receiver operator characteristic curves (AUC-ROC) to quantify the prognostic value. Calibration was assessed by calibration plots and Hosmer-Lemeshow (HL) goodness of fit test. RESULT: The final cohort included 306 eligible patients. For 3-month unfavorable outcome, the AUC-ROC of the START nomogram was .766 (95%CI: .7013-.8304, P < .0001), suggesting good discrimination in the START nomogram. It also showed good calibration (HL goodness of fit test P = .1261) in the external validation sample. CONCLUSION: The START nomogram with good predictive performance is a reliable and simple clinical instrument to predict unfavorable outcome after acute stroke.

A COACHS Nomogram to Predict the Probability of Three-Month Unfavorable Outcome after Acute Ischemic Stroke in Chinese Patients.

BACKGROUND: Accurate prognostication of unfavorable outcome made at the early onset of stroke is important to both the clinician and the patient management. This study was aimed to develop a nomogram based on the integration of parameters to predict the probability of 3-month unfavorable functional outcome in Chinese acute ischemic stroke patients. METHODS: We retrospectively collected patients who underwent acute ischemic stroke at Stroke Center of the Nanjing First Hospital (China) between May 2013 and May 2018. After exclusion, the study population includes 1,025 patients for nomogram development. The main outcome measure was 3-month unfavorable outcome (modified Rankin Scale > 2). Multivariable logistic regression analysis was used to develop the predicting model, and stepwise logistic regression with the Akaike information criterion was utilized to find best-fit nomogram model. We incorporated the creatinine, fast blood glucose, age, previous cerebral hemorrhage, previous valvular heart disease, and NHISS score (COACHS), and these factors were presented with a nomogram. We assessed the discriminative performance by using the area under curve (AUC) of receiver-operating characteristic (ROC) and calibration of risk prediction model by using the Hosmer-Lemeshow test. RESULTS: Multivariate analysis of the 1,025 patients for logistic regression helped identify the independent factors as National Institutes of Health Stroke Scale score on admission, age, previous valvular heart disease, fasting blood glucose, creatinine, and previous cerebral hemorrhage, which were included in the COACHS nomogram. The AUC-ROC of nomogram was 0.799. Calibration was good (p = 0.1376 for the Hosmer-Lemeshow test). CONCLUSIONS: The COACHS nomogram may be used to predict unfavorable outcome at 3 months after acute ischemic stroke in Chinese population. It may be also a reliable tool that is effective in its clinical utilization to risk-stratify acute stroke patients.