Predictive Models of Long-Term Outcome in Patients with Moderate to Severe Traumatic Brain Injury are Biased Toward Mortality Prediction.

BACKGROUND: The prognostication of long-term functional outcomes remains challenging in patients with traumatic brain injury (TBI). Our aim was to demonstrate that intensive care unit (ICU) variables are not efficient to predict 6-month functional outcome in survivors with moderate to severe TBI (msTBI) but are mostly associated with mortality, which leads to a mortality bias for models predicting a composite outcome of mortality and severe disability. METHODS: We analyzed the data from the multicenter randomized controlled Continuous Hyperosmolar Therapy in Traumatic Brain-Injured Patients trial and developed predictive models using machine learning methods and baseline characteristics and predictors collected during ICU stay. We compared our models' predictions of 6-month binary Glasgow Outcome Scale extended (GOS-E) score in all patients with msTBI (unfavorable GOS-E 1-4 vs. favorable GOS-E 5-8) with mortality (GOS-E 1 vs. GOS-E 2-8) and binary functional outcome in survivors with msTBI (severe disability GOS-E 2-4 vs. moderate to no disability GOS-E 5-8). We investigated the link between ICU variables and long-term functional outcomes in survivors with msTBI using predictive modeling and factor analysis of mixed data and validated our hypotheses on the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) model. RESULTS: Based on data from 370 patients with msTBI and classically used ICU variables, the prediction of the 6-month outcome in survivors was inefficient (mean area under the receiver operating characteristic 0.52). Using factor analysis of mixed data graph, we demonstrated that high-variance ICU variables were not associated with outcome in survivors with msTBI (p = 0.15 for dimension 1, p = 0.53 for dimension 2) but mostly with mortality (p < 0.001 for dimension 1), leading to a mortality bias for models predicting a composite outcome of mortality and severe disability. We finally identified this mortality bias in the IMPACT model. CONCLUSIONS: We demonstrated using machine learning-based predictive models that classically used ICU variables are strongly associated with mortality but not with 6-month outcome in survivors with msTBI, leading to a mortality bias when predicting a composite outcome of mortality and severe disability.

Discovery of a Myeloid Cell Leukemia 1 (Mcl-1) Inhibitor That Demonstrates Potent In Vivo Activities in Mouse Models of Hematological and Solid Tumors.

Myeloid cell leukemia 1 (Mcl-1) is a key regulator of the intrinsic apoptosis pathway. Overexpression of Mcl-1 is correlated with high tumor grade, poor survival, and both intrinsic and acquired resistance to cancer therapies. Herein, we disclose the structure-guided design of a small molecule Mcl-1 inhibitor, compound 26, that binds to Mcl-1 with subnanomolar affinity, inhibits growth in cell culture assays, and possesses low clearance in mouse and dog pharmacokinetic (PK) experiments. Evaluation of 26 as a single agent in Mcl-1 sensitive hematological and solid tumor xenograft models resulted in regressions. Co-treatment of Mcl-1-sensitive and Mcl-1 insensitive lung cancer derived xenografts with 26 and docetaxel or topotecan, respectively, resulted in an enhanced tumor response. These findings support the premise that pro-apoptotic priming of tumor cells by other therapies in combination with Mcl-1 inhibition may significantly expand the subset of cancers in which Mcl-1 inhibitors may prove beneficial.

Nicotine flux and pharmacokinetics-based considerations for early assessment of nicotine delivery systems.

In the past few years, technological advancements enabled the development of novel electronic nicotine delivery systems (ENDS). Several empirical measures such as "nicotine flux" are being proposed to evaluate the abuse liability potential of these products. We explored the applicability of nicotine flux for clinical nicotine pharmacokinetics (PK) and 52-week quit success from cigarettes for a wide range of existing nicotine delivery systems. We found that the differences in nicotine flux for various nicotine delivery systems are not related to changes in PK, as nicotine flux does not capture key physiological properties such as nicotine absorption rate. Further, the 52-week quit success and abuse liability potential of nicotine nasal sprays (high nicotine flux product), and nicotine inhalers (nicotine flux similar to ENDS) are low, suggesting that nicotine flux is a poor metric for the assessment of nicotine delivery systems. PK indices are more dependable for characterizing nicotine delivery systems, and a nicotine plasma C max T max > 1 could improve 52-week quit success from cigarettes. However, a single metric may be inadequate to fully assess the abuse liability potential of nicotine delivery systems and needs to be further studied. A combination of in vitro and in silico approaches could potentially address the factors influencing the inhaled aerosol dosimetry and resulting PK of nicotine to provide early insights for ENDS assessments. Further research is required to understand nicotine dosimetry and PK for ad libitum product use, and abuse liability indicators of nicotine delivery systems. This commentary is intended to (1) highlight the need to think beyond a single empirical metric such as nicotine flux, (2) suggest potential PK-based metrics, (3) suggest the use of in vitro and in silico tools to obtain early insights into inhaled aerosol dosimetry for ENDS, and (4) emphasize the importance of considering comprehensive clinical pharmacology outcomes to evaluate nicotine delivery systems.

Sepsis-trained macrophages promote antitumoral tissue-resident T cells.

Sepsis induces immune alterations, which last for months after the resolution of illness. The effect of this immunological reprogramming on the risk of developing cancer is unclear. Here we use a national claims database to show that sepsis survivors had a lower cumulative incidence of cancers than matched nonsevere infection survivors. We identify a chemokine network released from sepsis-trained resident macrophages that triggers tissue residency of T cells via CCR2 and CXCR6 stimulations as the immune mechanism responsible for this decreased risk of de novo tumor development after sepsis cure. While nonseptic inflammation does not provoke this network, laminarin injection could therapeutically reproduce the protective sepsis effect. This chemokine network and CXCR6 tissue-resident T cell accumulation were detected in humans with sepsis and were associated with prolonged survival in humans with cancer. These findings identify a therapeutically relevant antitumor consequence of sepsis-induced trained immunity.

Simulated pharmacokinetics of inhaled caffeine and melatonin from existing products indicate the lack of dosimetric considerations.

Numerous commercially available inhalable products claim to improve sleep-wake cycle-related target indications by delivering a wide variety of chemicals like caffeine and melatonin. The resulting exposure-responses from inhaling different doses are unknown and obtaining early understanding of resulting pharmacokinetics is beneficial. This study applied a physiologically based pharmacokinetic modeling approach to predict the inhalation pharmacokinetics of caffeine and melatonin for different target indications related to the sleep-wake cycle. The model predicted rapid systemic delivery of caffeine and melatonin based on airway regional deposition of inhaled aerosol. A low inhaled dose of 1 mg of caffeine resulted in a 72.3-times lower plasma maximal concentration and was predicted to not improve cognitive performance task outcomes compared to oral consumption of coffee containing 80 mg of caffeine. Conversely, 2-mg oral and inhaled doses of melatonin under recommended directions of use result in more than 25.1- and 645-times higher plasma concentrations compared to endogenous melatonin, respectively. The recommended doses for inhalation products for potential improvement in the target indications vary widely. Additional research is needed to evaluate the human pharmacokinetics, efficacy, and safety of inhaled products. Given the lack of assessments, inhaled caffeine and melatonin must be consumed with caution as the toxicological concerns are not known and could outweigh the potential beneficial effects.

Quantitative modeling of in vitro data using an adverse outcome pathway for the risk assessment of decreased lung function in humans.

In the absence of epidemiological data, there is a need to develop computational models that convert in vitro findings to human disease risk predictions following toxicant exposure. In such efforts, in vitro data can be evaluated in the context of adverse outcome pathways (AOPs) that organize mechanistic knowledge based on empirical evidence into a sequence of molecular-, cellular-, tissue-, and organ-level key events that precede an adverse outcome (AO). Here we combined data from advanced in vitro organotypic airway models exposed to combustible cigarette (CC) smoke or Tobacco Heating System (THS) aerosol with an AOP for increased oxidative stress leads to decreased lung function. The mathematical modeling predicted reduced risk of decreased ciliary beating frequency (CBF) based on oxidative stress measurements and reduced risk of decreased mucociliary clearance (MCC) based on CBF measurements in THS aerosol- compared with CC smoke-exposed cultures. To extend the predictions to the AO of decreased lung function, we leveraged human MCC data from current smokers, nonsmokers, former smokers, and users of heated tobacco products. This approach provided a plausible prediction of diminished reduction in lung function in response to THS use compared with continued smoking. The current approach may also present a basis for an integrated approach to testing and assessment of tobacco products for future regulatory decision-making.

Unplanned 30-day readmission rate after ophthalmological surgery as a quality-of-care indicator.

BACKGROUND: The 30-day readmission rate provides a standardised quantitative evaluation of some postoperative complications. It is widely used worldwide in many medical and surgical specialities, and the World Health Organization recommends its use for monitoring healthcare system performance. In ophthalmology, its measurement is biased by the frequent and close planned surgery on one eye and then the other, particularly in the case of cataract surgery. This study measures the 30-day unplanned readmission rate in ophthalmology, globally and by surgery subtype, and describes the causes of readmission. METHODS: All patients readmitted within 30 days of ophthalmic surgery at Nantes University Hospital between January 2017 and December 2020 were identified in the Medical Information System. An ophthalmologist examined each medical record and collected the following data: the reason for readmission, comorbidities, the pathology treated, surgery type, surgery duration, the surgeon's experience, anaesthesia type, severity and readmission morbidity. RESULTS: For the 8522 ophthalmic surgeries performed in the four-year study period, 282 30-day unplanned readmissions were identified. The overall 30-day unplanned readmission rate was 2.07% for elective surgery, with a high variability depending on the surgery type: 0.95% for phacoemulsification, 4.95% for vitreoretinal surgery (3.42% for non-elective vitreoretinal surgery, 5.44% for retinal detachment surgery), 5.66% for deep lamellar keratoplasty and 11.90% for trabeculectomy. The unplanned 30-day readmission rate for ocular trauma surgery (emergency care) was 11.0%. Seven percent of all unplanned 30-day readmissions were not associated with an ophthalmological problem. CONCLUSIONS: This study is the first to report 30-day unplanned readmission in ophthalmology, globally and by surgical subtype, for elective and urgent procedures. This indicator can be used longitudinally to detect an increase in risk or transversely to compare the quality of care between different public or private hospitals.