Colitis following the use of immune checkpoint inhibitors: A real-world analysis of spontaneous reports submitted to the FDA adverse event reporting system

BackgroundAlthough colitis has been reported in patients treated with immune checkpoint inhibitors (ICIs), associations between colitis and ICIs had not been thoroughly assessed in real-world studies. Here, we identified and characterized significant colitis-associated with ICIs.MethodsBased on the Food and Drug Administration Adverse Event Reporting System (FAERS) from January 2004 to December 2019, the disproportionality analysis and Bayesian analysis, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN) and the multi-item gamma Poisson shrinker (MGPS) algorithms were adopted to data mining of the suspected adverse events of colitis after ICIs administrating. Clinical characteristics of patients with ICIs-associated colitis and the time to onset of colitis following different ICI regimens were collected.ResultsA total of 3786 reports of colitis adverse events were identified with ICIs. Seven ICI monotherapies were associated with the reporting of colitis. Statistically significant ROR, PRR, information component (IC), and empirical Bayesian geometric mean (EBGM) emerged for all ICI monotherapies and combination therapies. ICIs-associated colitis affected mostly male (53.51%), with a wide mean age range (60.65 to 72 years). Colitis adverse events were commonly reported in patients with melanoma and lung cancer. Adverse outcomes of colitis concerning ICI were mainly outcomes of hospitalization-initiated or prolonged and other serious. Among colitis cases, 17.43% cases of colitis concerning ICI lead to death. The adverse event of colitis occurred earliest in ipilimumab monotherapy with a median time to onset of 64.21 days (IQR: 27–69 days) among all monotherapies.ConclusionsICI may lead to severe and disabling ICIs-associated colitis during therapy. Analysis of FAERS data identified signals for adverse events of colitis with ICI regimens. Practitioners should consider the factors that may increase the likelihood of colitis. The findings support a continued surveillance and risk factor identification studies.     

Risk factors for complications and in-hospital mortality: An analysis of 19,834 open pelvic ring fractures

BackgroundOpen pelvic fractures are rare injuries, associated with high patient morbidity and mortality. Few studies have investigated the impact of patient demographics, comorbidities, and injury related factors on complication and mortality rates. The purpose of this study was to: (1) identify the overall incidence of complications and mortality after open pelvic fractures, (2) compare patient factors between those who did and did not develop complications, (3) identify perioperative independent risk factors for complications and mortality.MethodsA query was performed for patients with open pelvic fractures between 2007 and 2017 using the American College of Surgeons National Trauma Data Bank. Patient and injury specific variables were collected and complications were identified using International Classification of Disease Ninth and Tenth edition Codes. Patient demographic and perioperative data was compared using Fisher’s exact test and chi-square test for categorical variables, and Welch’s t-test for continuous variables. Using pooled data from multiple imputations, logistic regressions were used to calculate odds ratios and confidence intervals of independent risk factors for complications.ResultsA total of 19,834 open pelvic fracture cases were identified, with 9622 patients (48.5%) developing at least one complication. Patients who developed complications were older (35.0 vs 38.1 years), and had higher Injury Severity Scores (17.7 vs 26.5), lower Glasgow Coma Scores (14.2 vs 11.7), and a larger proportion presenting with hypotension (21% vs 6.9%). After pooled regression involving 19 factors, these were the strongest independent predictors of inpatient complication and mortality.ConclusionWe report a mortality rate of 14%, with an inclusive complication rate of 48.5%. Evaluating risk factors for morbidity and mortality for this devastating orthopaedic injury provides knowledge of an inherently sparse population.Level of EvidenceLevel II, Retrospective study.     

¿Quién decide qué datos deben constar en la historia clínica en relación con el origen biológico?

There is an increasing request by patients or their representatives not to have some data registered in their clinical history or if such data exists to be deleted. Without doubt, this is so because such clinical data is accessed by various professionals who in most cases are not directly involved in caring for such patients. On the other hand, such data is copied and iteratively and unnecessary reproduced in various discharge reports and others forms. The problem arises when such controversial data refer to particularly sensitive clinical aspects such as assisted reproduction techniques, which invades personal and family privacy. Therefore, the question is who determines what data should be recorded in the medical records and according to what criteria should be taken that decision?     

Hearing Loss: Why Does It Matter for Nursing Homes?

Over the past decade, hearing loss has emerged as a key issue for aging and health. We describe why hearing loss may be especially disabling in nursing home settings and provide an estimate of prevalence using the Minimum Data Set (MDS v.3.0). We outline steps to mitigate hearing loss. Many solutions are inexpensive and low-tech, but require significant awareness and institutional commitment.     

Standard Operating Procedures for Chinese Medicine Data Monitoring Committees of Clinical Studies

Although there is guidance from different regulatory agencies, there are opportunities to bring greater consistency and stronger applicability to address the practical issues of establishing and operating a data monitoring committee (DMC) for clinical studies of Chinese medicine. We names it as a Chinese Medicine Data Monitoring Committee (CMDMC). A panel composed of clinical and statistical experts shared their experience and thoughts on the important aspects of CMDMCs. Subsequently, a community standard on CMDMCs (T/CACM 1323-2019) was issued by the China Association of Chinese Medicine on September 12, 2019. This paper summarizes the key content of this standard to help the sponsors of clinical studies establish and operate CMDMCs, which will further develop the scientific integrity and quality of clinical studies.