Maintaining The Status of Hydration on Mr. G With Pneumonia in Fatmawati Hospital
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
Pneumonia is a health problem in the world with a high mortality rate both in developing countries and in developed countries such as America, Canada and European countries. In Indonesia, the number three cause of death after cardiovascular disease and tuberculosis. Low socioeconomic factors increase mortality. This infection is generally spread from someone who is exposed in the neighborhood or has direct contact with infected people through their hands or by breathing air (droplets) due to coughing or sneezing. In the pandemic era, pneumonia is very feared because it is related to respiratory diseases which are becoming a trend and issue, so it requires special treatment in this case. This case report aims to improve the provision of nursing care for pneumonia patients to mantaining hydration status with airway clearance problems. Nursing assessment of pneumonia patients was carried out on September 13, 2020, a 52-year-old man who has a history of DM and smoking comes with complaints of coughing but no phlegm, fever since one week ago has disappeared, the patient has diarrhea since 2 days before entering the house pain and stomach pain, the patient also has nausea and vomiting and has no appetite. Nursing intervention for 3 days in accordance with the established outcome criteria. From the nursing intervension carried out, the problem of clearing the airway was resolved, marked by no coughing, normal breathing, no ronchi, moist mucosa and no cyanosis. Nursing intervention to maintaining the patient's adequate hydration status can overcome the problem of ineffective airway clearance.
 
 Keywords: Pneumonia, Airway Clearance, Hydration Status
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it