Proposed Plan of Home Based New Born Care in Kamis Mushayt, Saudi Arabia -Dr. Krishnavellie Chetty & Mary Johnson
Bibliographic record
Abstract
The global burden of neonatal deaths is estimated to be 2.6 million, of which 0.76 million—more than a quarter—occur in India. With a neonatal mortality rate (NMR) of 26 per 1000 live births and infant mortality rate of 39 per 1000 live births,2 deaths in the neonatal period alone contribute to two-thirds of infant deaths in India. Even among postneonatal infant deaths (1–12 months), a major proportion of deaths occur in the second month of life. Any further reduction in infant mortality is therefore intricately linked to a major reduction of neonatal and young infant (0–59 days) deaths. Various attempts have been made to implement innovative approaches for newborn care at community/home level. The Cochrane review on community- based interventions found a significant reduction—by about 25%—in neonatal mortality with community mobilisation and antenatal and postnatal home visits by health workers. The Lancet Every Newborn Study Group estimated that immediate scaling up of various community-based and primary care interventions can avert almost a third of all neonatal deaths by 2017 and one-fifth by 2025. Khamis Mushayt or Khamis Mushait city in south-west Saudi Arabia, located east of Abha, the provincial seat of the Asir province, It is the capital of the Shahran tribe. 8th largest in Saudi Arabia with an estimated population of 1,300,000. The infant mortality rate is a significant indicator of the quality of the health care provided to the population and gives insight into the factors that influence health. According to Millennium Development Goal 4, minimizing the infant mortality rate is a major challenge. Substantial efforts and resources are necessary to overcome these challenges, especially during the neonatal period, which is the main contributor to mortality figures for children under age five.The nursing team is striving to take initiative in promoting the new born care to the best possible so that the morbidity and mortality rates can come down even further and the new born wellbeing will be promoted in the areas of Khamis Mushait where the proposed plan of care is not available.
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How this classification was reachedexpand
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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".