Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 41991344

Published Database Resources for Traditional, Complementary, and Integrative Medicine: Update of a Systematic Review.

Christa K Raak·David D Martin·Katja Boehm·Daniela Hacke·Sebastian Unger·Thomas Ostermann
View original source ↗Export metadata ↓

Abstract

BACKGROUND: Traditional, Complementary, and Integrative Medicine (TCIM) has been established in the academic context of universities. In recent years, strategies have been developed worldwide to strengthen the role of TCIM in supporting the health of the population. Online databases are a common way for obtaining evidence-based information. This article is an update of a former systematic review from 2010 on published databases resources for TCIM. METHODS: The databases CINAHL, CAMbase, Web of Science, MEDLINE/PubMed, and Google Scholar search engine were searched for databases related to TCIM published in peer-reviewed journals between 2010 and November 2024. All included databases were visited online, and information on the origin, content, and scope of the database was extracted. RESULTS: A total of 6579 articles were identified through the literature search. After exclusion of irrelevant articles, full-text screening of 127 articles yielded 37 new databases. Together with 16 still available old databases, these mainly contained information on herbal therapies (n = 15) and Traditional Chinese Medicine (n = 11) from 18 different countries. Newly identified medicinal plant databases offer various scientific resources such as crude drugs, indigenous plants, and structures for natural and phytochemical components with molecular biological content. CONCLUSIONS: This literature review illustrates the dynamic development in the database landscape over the last 15 years. While the number of bibliographic databases is shrinking, databases in the field of medical plants/herbal therapy content are on the rise, which might be due to advances in plant genomics and molecular biology.

Explore related subjects

HumansComplementary TherapiesDatabases, FactualIntegrative MedicinePlants, Medicinalbibliographical datacomplementary medicinedatabasesevidence-based medicineintegrative medicineJournal ArticleSystematic Review

Keep this discovery

BibTeXRIS

Christa K Raak, David D Martin, Katja Boehm, Daniela Hacke, Sebastian Unger, Thomas Ostermann. 2026-04-16. Published Database Resources for Traditional, Complementary, and Integrative Medicine: Update of a Systematic Review.. https://doi.org/10.1177/27683605261441386

Cite the original work for its findings. Save a collection to share your selection of sources.

Discover connections

Journal Article; Systematic Review resourceDatabases, Factual subjectEvidence-Based Medicine subjectHumans subjectJournal Article subjectSystematic reviews study

Connections use source metadata and explicit phrase matches, not verified experimental comparisons.

KEEP EXPLORING

Related citations

PubMed2026

Association between SGLT2 inhibitors and reporting of phimosis/paraphimosis: a comparative pharmacovigilance analysis of the WHO database.

PURPOSE: Recent data have discussed occurrence of phimosis with Sodium-glucose co-transporter-2 (SGLT2) inhibitors. However, the potential risk among the different SGLT2 inhibitors is unknown. METHODS: Using Individual Case Safety Reports (ICSRs) registered in the WHO pharmacovigilance database (01/01/2000-30/06/2025), comparisons between the different SGLT2 inhibitors and versus other drugs used in diabetes (DUD) were performed. Results are shown as Reporting Odds Ratios (ROR). RESULTS: Among 11 342 810 ICSRs, 227 were phimosis/paraphimosis with SGLT2 inhibitors, mainly between 45 and 64 years. The higher ROR value was found with empagliflozin followed by dapagliflozin and canagliflozin. ROR for SGLT2 inhibitors was higher that of all other DUD [34.72 (25.86-46.62)]. The reporting risk of phimosis/paraphimosis with SGLT2 inhibitors was also higher than that of each pharmacological class of DUD. CONCLUSION: The results suggest an association between SGLT2 inhibitors use and phimosis ICSRs. Empagliflozin had the higher reporting risk.

Humans↗
PubMed2026

Metformin Adherence and Risk of Polyneuropathy in Type 2 Diabetes Mellitus: An International Matched Cohort Study with Independent Validation.

BACKGROUND: Metformin is a popular first-line glucose-lowering medication for type 2 diabetes mellitus (T2DM). Although metformin reduces the risks of various complications of diabetes, its potential to cause polyneuropathy by depleting vitamin B12 levels is concerning. This study investigated whether the adherence or discontinuation of metformin after adding-on a second-line antiglycemic agent increases the risk of polyneuropathy in patients with T2DM. METHODS: Data from TriNetX were obtained, and patients with T2DM who were receiving second-line antiglycemic agents were divided into metformin-adherent and metformin-nonadherent groups based on prescription claims data. Neuropathy incidence was evaluated using diagnostic claims and nerve conduction examinations. For independent confirmation and external validation of the primary findings, we used data from the National Health Insurance Research Database (NHIRD) of Taiwan. RESULTS: After matching, 58,027 patients were included in each group. Compared with metformin adherent patients, metformin nonadherent patients had a higher risk of polyneuropathy (adjusted hazard ratios [aHR] 1.26; 95% confidence interval [CI] 1.23-1.29; P < 0.001). Risks of diabetic foot ulcer, amputation, neuropathy-related medication use, and bone fracture were also higher among nonadherent patients. Sensitivity analyses confirmed the robustness of findings. In the validation NHIRD cohort (31,384 matched pairs), metformin nonadherence remained associated with increased polyneuropathy risk (aHR 1.25; 95% CI 1.10-1.42; P < 0.001). CONCLUSIONS: Metformin adherence in patients with T2DM who require second-line treatment may reduce the risk of polyneuropathy; vitamin B supplementation may enhance this benefit.

Humans↗
PubMed2026

Development and validation of a comprehensive prognostic model for 28-day ICU mortality in non-traumatic subarachnoid hemorrhage: an analysis based on the MIMIC-IV database.

BACKGROUND: Due to the complex pathophysiology of non-traumatic subarachnoid hemorrhage (SAH), accurate risk prediction remains a challenge. Our aim is to develop and validate a comprehensive prognostic model that integrates demographic characteristics, vital signs, laboratory parameters, and more, to provide clinical decision-making support in real-world practice. METHODS: We conducted a retrospective cohort study of 785 Non-traumatic subarachnoid hemorrhage patients. The cohort was randomly divided into a training set (n&#xa0;=&#xa0;549) and a validation set (n&#xa0;=&#xa0;236). Feature selection was performed using LASSO regression, followed by backward stepwise Cox regression for optimization. A nomogram was constructed based on independent predictive factors, and model performance was assessed using discrimination, calibration, and decision curve analysis. To prevent immortal-time bias, all predictors were anchored to a fixed early (first-24-hour) measurement window, treatment variables were modelled as binary indicators rather than cumulative exposures, and a five-model sensitivity analysis with baseline-severity adjustment was performed. RESULTS: The development of our model followed a systematic approach: first, 15 potential predictive factors were selected via LASSO regression, which were then refined to 12 independent predictors using backward stepwise Cox regression. The final predictive factors included: Ventilation, AHT, Nimodipine 60&#xa0;mg, Age, SAPS.II, Input amount, Calcium total, Platelet count, White blood cells, Anion gap, pH, and Chloride. The integrated model demonstrated excellent predictive ability for 7-day, 14-day, and 21-day mortality in both the training set (AUC: 0.972, 0.934, 0.898) and the validation set (AUC: 0.968, 0.948, 0.911). Calibration curves and decision curve analysis confirmed the model's reliability and clinical utility across different time points. We constructed a nomogram for individualized risk prediction. Univariate Kaplan-Meier survival analysis demonstrated significant stratification of survival outcomes by each predictor, while restricted cubic spline analysis revealed non-linear relationships between continuous variables and mortality risk. Random survival forest analysis identified the top three predictive factors (Nimodipine 60&#xa0;mg, Ventilation, AHT) and compared them with our full 12-variable model, confirming superior performance of the integrated model at all time points. At the 28-day primary endpoint, the model achieved a time-dependent AUC of 0.898 (training) and 0.904 (validation); after restricting predictors to the early baseline window, the leakage-controlled model retained good discrimination (validation C-index 0.803). CONCLUSIONS: Our ICU 28-day mortality prognosis model demonstrated robust performance in predicting ICU 28-day mortality in non-traumatic subarachnoid hemorrhage. The model, through the nomogram, provides individualized risk assessment, aiding clinical decision-making and patient stratification.

Humans↗