scholarly journals Bile reflux gastropathy: Prevalence and risk factors after therapeutic biliary interventions: A retrospective cohort study

2021 ◽  
Vol 72 ◽  
pp. 103168
Author(s):  
Amira A.A. Othman ◽  
Amal A.Z. Dwedar ◽  
Hany M. ElSadek ◽  
Hesham R. AbdElAziz ◽  
Abeer A.F. Abdelrahman
2018 ◽  
Vol 69 (9) ◽  
pp. 2465-2466
Author(s):  
Iustin Olariu ◽  
Roxana Radu ◽  
Teodora Olariu ◽  
Andrada Christine Serafim ◽  
Ramona Amina Popovici ◽  
...  

Osseointegration of a dental implant may encounter a variety of problems caused by various factors, as prior health-related problems, patients� habits and the technique of the implant inserting. Retrospective cohort study of 70 patients who received implants between January 2011- April 2016 in one dental unit, with Kaplan-Meier method to calculate the probability of implants�s survival at 60 months. The analysis included demographic data, age, gender, medical history, behavior risk factors, type and location of the implant. For this cohort the implants�survival for the first 6 months was 92.86% compared to the number of patients and 97.56% compared to the number of total implants performed, with a cumulative failure rate of 2.43% after 60 months. Failures were focused exclusively on posterior mandible implants, on the percentage of 6.17%, odds ratio (OR) for these failures being 16.76 (P = 0.05) compared with other localisations of implants, exclusively in men with median age of 42 years.


2021 ◽  
Vol 49 (6) ◽  
pp. 030006052110251
Author(s):  
Minqiang Huang ◽  
Ming Han ◽  
Wei Han ◽  
Lei Kuang

Objective We aimed to compare the efficacy and risks of proton pump inhibitor (PPI) versus histamine-2 receptor blocker (H2B) use for stress ulcer prophylaxis (SUP) in critically ill patients with sepsis and risk factors for gastrointestinal bleeding (GIB). Methods In this retrospective cohort study, we used the Medical Information Mart for Intensive Care III Clinical Database to identify critically ill adult patients with sepsis who had at least one risk factor for GIB and received either an H2B or PPI for ≥48 hours. Propensity score matching (PSM) was conducted to balance baseline characteristics. The primary outcome was in-hospital mortality. Results After 1:1 PSM, 1056 patients were included in the H2B and PPI groups. The PPI group had higher in-hospital mortality (23.8% vs. 17.5%), GIB (8.9% vs. 1.6%), and pneumonia (49.6% vs. 41.6%) rates than the H2B group. After adjusting for risk factors of GIB and pneumonia, PPI use was associated with a 1.28-times increased risk of in-hospital mortality, 5.89-times increased risk of GIB, and 1.32-times increased risk of pneumonia. Conclusions Among critically ill adult patients with sepsis at risk for GIB, SUP with PPIs was associated with higher in-hospital mortality and higher risk of GIB and pneumonia than H2Bs.


Antibiotics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 446
Author(s):  
Laura Soldevila-Boixader ◽  
Bernat Villanueva ◽  
Marta Ulldemolins ◽  
Eva Benavent ◽  
Ariadna Padulles ◽  
...  

Background: Daptomycin-induced eosinophilic pneumonia (DEP) is a rare but severe adverse effect and the risk factors are unknown. The aim of this study was to determine risk factors for DEP. Methods: A retrospective cohort study was performed at the Bone and Joint Infection Unit of the Hospital Universitari Bellvitge (January 2014–December 2018). To identify risk factors for DEP, cases were divided into two groups: those who developed DEP and those without DEP. Results: Among the whole cohort (n = 229) we identified 11 DEP cases (4.8%) and this percentage almost doubled in the subgroup of patients ≥70 years (8.1%). The risk factors for DEP were age ≥70 years (HR 10.19, 95%CI 1.28–80.93), therapy >14 days (7.71, 1.98–30.09) and total cumulative dose of daptomycin ≥10 g (5.30, 1.14–24.66). Conclusions: Clinicians should monitor cumulative daptomycin dosage to minimize DEP risk, and be cautious particularly in older patients when the total dose of daptomycin exceeds 10 g.


BMJ Open ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. e049089
Author(s):  
Marcia C Castro ◽  
Susie Gurzenda ◽  
Eduardo Marques Macário ◽  
Giovanny Vinícius A França

ObjectiveTo provide a comprehensive description of demographic, clinical and radiographic characteristics; treatment and case outcomes; and risk factors associated with in-hospital death of patients hospitalised with COVID-19 in Brazil.DesignRetrospective cohort study of hospitalised patients diagnosed with COVID-19.SettingData from all hospitals across Brazil.Participants522 167 hospitalised patients in Brazil by 14 December 2020 with severe acute respiratory illness, and a confirmed diagnosis for COVID-19.Primary and secondary outcome measuresPrevalence of symptoms and comorbidities was compared by clinical outcomes and intensive care unit (ICU) admission status. Survival was assessed using Kaplan Meier survival estimates. Risk factors associated with in-hospital death were evaluated with multivariable Cox proportional hazards regression.ResultsOf the 522 167 patients included in this study, 56.7% were discharged, 0.002% died of other causes, 30.7% died of causes associated with COVID-19 and 10.2% remained hospitalised. The median age of patients was 61 years (IQR, 47–73), and of non-survivors 71 years (IQR, 60–80); 292 570 patients (56.0%) were men. At least one comorbidity was present in 64.5% of patients and in 76.8% of non-survivors. From illness onset, the median times to hospital and ICU admission were 6 days (IQR, 3–9) and 7 days (IQR, 3–10), respectively; 15 days (IQR, 9–24) to death and 15 days (IQR, 11–20) to hospital discharge. Risk factors for in-hospital death included old age, Black/Brown ethnoracial self-classification, ICU admission, being male, living in the North and Northeast regions and various comorbidities. Age had the highest HRs of 5.51 (95% CI: 4.91 to 6.18) for patients≥80, compared with those ≤20.ConclusionsCharacteristics of patients and risk factors for in-hospital mortality highlight inequities of COVID-19 outcomes in Brazil. As the pandemic continues to unfold, targeted policies that address those inequities are needed to mitigate the unequal burden of COVID-19.


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