A Literature Review on the Efficacy of Injectable Neuroleptics in the Treatment of Schizophrenia
Bibliographic record
Abstract
Introduction: Schizophrenia is a chronic brain disorder of which the cause is unknown. This disorder affects less than one percent of the population and involves symptoms such as hallucinations, delusions, disorganization, and negative symptoms. Treatment for schizophrenia is mainly used to alleviate symptoms of schizophrenia, therefore improving their quality of life. Injectable neuroleptics are frequently used in patients with schizophrenia to prevent relapses attributed to nonadherence. This literature review will examine the current and potential future uses of injectable neuroleptics as a treatment for individuals with schizophrenia. Methods: This literature review was assembled using the PubMed, Google Scholar, and Science Direct databases to evaluate the efficacy of injectable neuroleptics for individuals with schizophrenia. Keywords for the search include: “neuroleptics”, “schizophrenia”, “risperidone”, “aripiprazole,” “clozapine”, “long-acting injections”, “treatment”, “clinical trial” as well as additional related keywords. Results: In all of the RCTs identified in the reviewed studies, clozapine was considered the most effective in alleviating symptoms associated with schizophrenia although it did not affect the progression of the disorder. Discussion: The literature discussing various injection neuroleptics has been shown to be safe and effective in treating symptoms of schizophrenia but has not been proven to be effective in the slowing of the progression of schizophrenia. As such, future research in this area would be beneficial to the scientific community. Given the limited number of studies, additional research is needed to assess the efficacy of long-acting injectable antipsychotics in slowing the progression of the disorder. One possible research avenue would involve the examination of a combination therapy of both injectable and oral neuroleptic treatments. Conclusion: Long-acting injectable antipsychotics have been shown to be effective in alleviating many of the debilitating symptoms for individuals with schizophrenia. Further studies are needed to evaluate the most effective method of treating the progression of this disorder, such as combination therapy using both injectable as well as oral antipsychotics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".