Natural language processing and network analysis in patients withdrawing from life-sustaining treatments: a retrospective cohort study.

BACKGROUND: Providing palliative care to patients who withdraw from life-sustaining treatments is crucial; however, delays or the absence of such services are prevalent. This study used natural language processing and network analysis to identify the role of medications as early palliative care referral triggers. METHODS: We conducted a retrospective observational study of 119 adult patients receiving specialized palliative care after endotracheal tube withdrawal in intensive care units of a Taiwan-based medical center between July 2016 and June 2018. Patients were categorized into early integration and late referral groups based on the median survival time. Using natural language processing, we analyzed free texts from electronic health records. The Palliative trigger index was also calculated for comparison, and network analysis was performed to determine the co-occurrence of terms between the two groups. RESULTS: Broad-spectrum antibiotics, antifungal agents, diuretics, and opioids had high Palliative trigger index. The most common co-occurrences in the early integration group were micafungin and voriconazole (co-correlation = 0.75). However, in the late referral group, piperacillin and penicillin were the most common co-occurrences (co-correlation = 0.843). CONCLUSION: Treatments for severe infections, chronic illnesses, and analgesics are possible triggers for specialized palliative care consultations. The Palliative trigger index and network analysis indicated the need for palliative care in patients withdrawing from life-sustaining treatments. This study recommends establishing a therapeutic control system based on computerized order entry and integrating it into a shared-decision model.

De novo synthesis of a MIL-125(Ti) carrier for thermal- and pH-responsive drug release.

Microporous round cake-like (diameter: 900 ± 100 nm) MIL-125(Ti) carrier with a central metal (Ti) exhibiting bio-affinity and possessing a great potential to be used as drug release platform, has been synthesized in the present study. The thermal and pH responsiveness of drug delivery systems (DDS) are the most important parameters for drug release and can be provided through polymer coating techniques. The Pluronic F127 (F127) and chitosan (CH) monomers were inserted into the crystal lattice of MIL-125(Ti) carrier during the de novo synthesis process, which were subsequently loaded with doxorubicin (DOX). The results reveal particle size changes (ranged between 30 and 50 %) from the original size of the MIL-125(Ti) carrier in response to temperature and pH when the carrier reaches acid environment. The drug release profiles have been completed through self-design device, which provides for the real-time release in the DOX amounts via UV-Vis spectra. The kinetics analysis was used to evaluate the R2 values of first order, Higuchi, Korsmeyer-peppas, and Weibull fitting equations, where the Weibull fitting indicated the best R2. An increase by 59.3 % of DOX released under the acid status (pH = 5.4) was observed, indicating that the CH-MIL-125(Ti) carrier is temperature and pH responsive. Moreover, the lattice explosion resulting from the temperature increase in the range of 25-42 °C caused an increase in F127-MIL-125(Ti) by 30.8-38.3 %. The simulated SAXS/WAXS studies for the microstructures of MIL-125(Ti) based DDS at different temperatures after polymer coating (F127-MIL-125(Ti)) provide the possible mechanism of lattice explosion. As such, the responsive Ti-MOF has a highly potential for use in the applications of cancer treatment.