Antibiotics and Resistant Bacteria in Hospital Wastewater: A Review ofTheir Presence and Implemented Removal Measures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Currently, antibiotics and resistant bacteria have been included among emerging microcontaminants that generate global concern.Due to prolonged exposure in the environment, they cause harmful effects on human health and aquatic ecosystems.Additionally, there is no standardized global regulation that governs their final disposal in hospital effluents and wastewater, leading to the indiscriminate discharge of antimicrobials into these effluents, which then reach wastewater treatment plants.This increases selective pressure on bacteria, resulting in the development of resistant bacteria and posing a risk to human health.This review explores antibiotics and resistant bacteria isolated from hospital effluents.It also provides information on methodologies used for isolating and identifying these bacteria, antibiotic resistance genes, and in situ methodologies for their removal.For this purpose, publications registered between 2021 and 2024 in the Scopus database were analyzed.As a result, it was found that no studies conduct a combined search for antibiotics and resistant bacteria in hospital effluents.Most studies focus on searching for bacteria and antibiotic resistance genes.Additionally, the methodologies presented for the removal of these microcontaminants show promising results and are proposed as a solution to be implemented within hospitals.In conclusion, there is an increase in the presence of bacteria resistant to antimicrobials due to the lack of regulatory standards, which increases the risk to human health and ecosystems.However, future prospects for their treatment are promising thanks to the use of biotechnology.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it