Articles: cations.
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Statistically significant positive results are more likely to be published than negative or insignificant outcomes. This phenomenon, also termed publication bias, can skew the interpretation of meta-analyses. The widespread presence of publication bias in the biomedical literature has led to the development of various statistical approaches, such as the visual inspection of funnel plots, Begg test, and Egger test, to assess and account for it. ⋯ Taken together, these results indicate that publication bias remains largely unaccounted for in neurosurgical meta-analyses.
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Avoiding the Radial Paradox: Neuroendovascular Femoral Access Outcomes After Radial Access Adoption.
Transradial access (TRA) for neuroendovascular procedures is increasing in prevalence. The safety benefits of TRA at a patient level may be offset at a population level by a paradoxical increase in transfemoral access (TFA) vascular access site complications (VASCs), the so-called "radial paradox." ⋯ TFA remains an important access route, despite a predominantly radial paradigm, and is disproportionately used in patients at increased risk for VASCs. TFA proficiency may still be achieved in predominantly radial practices without an increase in femoral complications.
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Isolated traumatic subarachnoid hemorrhage (tSAH) is a common finding in mild traumatic brain injury that often results in transfer to a tertiary center. Patients prescribed blood-thinning medications (BTs) are believed to be at higher risk of clinical or radiographic worsening. ⋯ Neurologically intact patients on BTs with isolated tSAH are not at increased risk of radiographic progression or neurosurgical intervention. The presence of BTs should not influence management decisions for increased surveillance.
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Anasthesiol Intensivmed Notfallmed Schmerzther · Mar 2022
[Artificial Intelligence: Challenges and Applications in Intensive Care Medicine].
The high workload in intensive care medicine arises from the exponential growth of medical knowledge, the flood of data generated by the permanent and intensive monitoring of intensive care patients, and the documentation burden. Artificial intelligence (AI) is predicted to have a great impact on ICU work in the near future as it will be applicable in many areas of critical care medicine. These applications include documentation through speech recognition, predictions for decision support, algorithms for parameter optimisation and the development of personalised intensive care medicine. ⋯ Speech recognition has the potential to reduce this documentation burden. It is not yet precise enough to be usable in the clinic. The application of AI in medicine, with the help of large data sets, promises to identify diagnoses more quickly, develop individualised, precise treatments, support therapeutic decisions, use resources with maximum effectiveness and thus optimise the patient experience in the near future.