<b> Perfil dos diagnósticos de enfermagem de pacientes internados em unidade de clínica médica/ Profile of nursing diagnoses of patients hospitalized at a medical clinic unit<b>
Bibliographic record
Abstract
O objetivo foi identificar a frequência dos diagnósticos de enfermagem em clientes hospitalizados em unidade de clínica médica. Tratou-se de um estudo quantitativo do tipo descritivo-exploratório realizado na unidade de clínica médica do Hospital Universitário Regional de Maringá (HURM) com amostra de 25 participantes. Dos 13 domínios descritos pela NANDA-I, todos foram representados por pelo menos um diagnóstico. Foram levantados 530 diagnósticos, com uma média de 21,2 por paciente. Os diagnósticos predominantes foram risco de infecção (100%), integridade da pele prejudicada (88%), manutenção ineficaz da saúde (76%), deambulação prejudicada (76%), conforto prejudicado (76%), padrões de sexualidade ineficazes (72%), mobilidade física prejudicada (68%), integridade tissular prejudicada (68%), déficit no autocuidado para banho (64%), para higiene íntima (64%), para vestir-se (64%) e mobilidade prejudicadano leito (60%). Esses resultados contribuíram para a identificação das necessidades mais afetadas dos pacientes internados facilitando a elaboração de planos de cuidados de enfermagem mais eficazes.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".