Effect of granulocytes infusion in pediatric neutropenic and bone marrow transplant patient
Bibliographic record
Abstract
Background: Children with haematological malignancy have a high risk of infection during the course of their treatment.The Institution follows fluconazole prophylaxis for all patients with Hematologic malignancy and indwelling catheters.Co-Trimoxazole prophylaxis is used for all patients with Acute lymphoblastic leukemia(ALL).Fluoroquinolone prophylaxisis given during neutropenia for all patients with Hematologic Malignancies.Patients with Acute Myeloid Leukemia(AML) receive Posaconazole as fungal prophylaxis during neutropenia.We conducted an auditof infectionsdocumented in children with hematological malignancy at our institution in the year 2021.AIMS: To analyse the spectrum and the immediate outcome of documented infections in children with haematological malignancies in the year 2021.Methods: After Institutional research board approval,electronic medical records of all visits of patients between 1 and 18 years of age with hematological malignancies treated at the institution in 2021 were screened.All investigations done for identifying infection were reviewed.Positive reports of Blood and Urine cultures,Broncho alveolar lavage Culture,Nasal/ oropharyngeal swab Polymerase Chain Reaction,Tzanck smear, Histopathological examination were noted.Every infection was documented and the immediate outcome recorded.The data was compiled and analysed using Microsoft office Excel 2019 version.Results: There were 47 patients between 1 and 18 years.The cohort comprised of 37 patients with ALL, 6 patients with AML and 4 patients with Hodgkins Lymphoma.A total of 183 admissions were recorded.Of 87 documented febrile neutropenia during these admissions, 44 had documented infections.There were equal number of documented Bacterial and Viral infections in the cohort (n¼20;45%).The commonest isolated bacterial species was Burkholderia(n¼5;11%).SARS COVID 19 was the commonest viral infection(n¼10;22.7%).Aspergillus species was the commonest Fungal isolate(n¼4;9%).All patients were alive at last follow up.Conclusions: SARS Covid 19 was the commonest documented infection in the cohort.Burkholderia species was the commonest Gramnegative isolate and Aspergillus was the predominant fungal isolate as against Klebsiella, Pseudomonas and Candida species respectively in other studies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".