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The combination with corticosteroids as immunomodulators has been the subject of debate in different infectious syndromes. The main objective of this study is to evaluate the efficacy (the percentage of patients hospitalised with influenza with a status of 3 or higher according to the Hospital Recovery Scale (HRS) on day 7 after the start of treatment) and safety of dexamethasone.
Investigator-initiated multicentre, blinded, randomised placebo-controlled trial with two parallel treatment arms. The study population will consist of adult patients (over 18 years of age) hospitalised with severe influenza. One arm will receive one capsule of 6 mg of dexamethasone for 7 days, and the other arm will receive one capsule of placebo for 7 days of antibiotic treatment for 7 days or longer. Both groups will receive oseltamivir (75 mg/12 hours orally) for 5 days, extendable to 10 days depending on the investigator decision. Randomisation will occur in equal proportion (1:1). Patients with bronchial hyper-responsiveness that requires systemic corticosteroids for more than 24 hours, preinclusion treatment with corticosteroids for more than 24 hours at a dose equal to or higher than 1 mg/kg methylprednisolone (0.2 mg/kg dexamethasone or 1.25 mg/kg prednisone), inability to administer oral oseltamivir, patients with severe comorbidity with a life expectancy of
The study is approved by the Institutional Review Board of Alicante Health Department—Dr. Balmis General University Hospital (LOC-100061146). The results of the main trial and each of the secondary endpoints will be submitted for publication in a peer-reviewed journal
The Puerto Rico Department of Health (PRDH) seeks to identify dengue epidemics as early as possible with high specificity.
Development and prospective application of an early warning system for dengue epidemics using routine historical surveillance data. A weekly intercept-only negative binomial regression model was fitted using historical probable and confirmed dengue data. A range of threshold definitions was explored using three model-estimated percentiles of weekly dengue case counts.
Dengue is endemic in Puerto Rico with irregular occurrence of large epidemics with substantial impact on health burden and health systems. Probable and confirmed dengue data are routinely collected from all hospitals and private clinics.
A total of 86 282 confirmed or probable dengue virus cases were reported from 1 January 1986 to 30 June 2024, with an annual mean of 2212 cases (median: 1533; range: 40–10 356).
The model was fitted retrospectively to mimic real-time epidemic detection and assessed based on sensitivity and specificity of epidemic detection.
The 75th percentile threshold aligned best with historical epidemic classifications, balancing false alarms and missed detections. This model provides a robust method for defining thresholds, accounting for skewed data, using all historical data and improving on traditional methods like endemic channels.
In March 2024, PRDH declared a public health emergency due to an early, out-of-season surge in cases that exceeded the epidemic alert threshold developed in this study. This real-time application highlights the value of these thresholds to support dengue epidemic detection and public health response. Integrating thresholds with other tools and strategies can enhance epidemic preparedness and management.
With ambient listening systems increasingly adopted in healthcare, analyzing clinician-patient conversations has become essential. The Omaha System is a standardized terminology for documenting patient care, classifying health problems into four domains across 42 problems and 377 signs/symptoms. Manually identifying and mapping these problems is time-consuming and labor-intensive. This study aims to automate health problem identification from clinician-patient conversations using large language models (LLMs) with retrieval-augmented generation (RAG).
Using the Omaha System framework, we analyzed 5118 utterances from 22 clinician-patient encounters in home healthcare. RAG-enhanced LLMs detected health problems and mapped them to Omaha System terminology. We evaluated different model configurations, including embedding models, context window sizes, parameter settings (top k, top p), and prompting strategies (zero-shot, few-shot, and chain-of-thought). Three LLMs—Llama 3.1-8B-Instruct, GPT-4o-mini, and GPT-o3-mini—were compared using precision, recall, and F1-score against expert annotations.
The optimal configuration used a 1-utterance context window, top k = 15, top p = 0.6, and few-shot learning with chain-of-thought prompting. GPT-4o-mini achieved the highest F1-score (0.90) for both problem and sign/symptom identification, followed by GPT-o3-mini (0.83/0.82), while Llama 3.1-8B-Instruct performed worst (0.73/0.72).
Using the Omaha System, LLMs with RAG effectively automate health problem identification in clinical conversations. This approach can enhance documentation completeness, reduce documentation burden, and potentially improve patient outcomes through more comprehensive problem identification, translating into tangible improvements in clinical efficiency and care delivery.
Automating health problem identification from clinical conversations can improve documentation accuracy, reduce burden, and ensure alignment with standardized frameworks like the Omaha System, enhancing care quality and continuity in home healthcare.
The rapid growth in the cancer survivor population in Chile and Latin America raises new challenges in addressing their care needs. This study assesses the health status and compares the quality of care and quality of life in cancer survivors at a primary care network and a private cancer centre in Santiago, Chile.
Retrospective cohort study.
Three primary care clinics and one cancer centre in Chile.
All breast and colorectal cancer patients identified from a primary care retrospective cohort of 61 174 were followed from 2018 to 2023 and compared with an equivalent sample of patients from a university cancer centre identified during the same period.
Quality of care was assessed based on American Cancer Society standards, while quality of life was measured using the EuroQol 5 Dimensions-5 Levels survey instrument.
A total of 420 cancer survivors participated in the study; 208 from primary care and 212 from the cancer centre. All participants received substandard care. Patients in primary care had lower educational levels and higher rates of comorbidity. They reported a lower quality of life score (72.22 vs 78.43, p
Cancer survivors face a significant disease burden and receive substandard care in Chile. As the primary source of care for this population, primary care is challenged to better integrate with speciality care to develop an effective shared care model for cancer survivors.
Introducción. La punción arterial para el análisis gasométrico provoca dolor de intensidad variable. Este dolor podría alterar la dinámica ventilatoria y, por tanto, los parámetros respiratorios de la muestra sanguínea. Objetivos. Determinar la posible relación entre el dolor inducido por la punción arterial y los parámetros obtenidos del análisis gasométrico de estas muestras de sangre. Como objetivos secundarios, obtener la prevalencia del dolor provocado en la muestra estudiada y la posible asociación con el número de intentos. Metodología. Estudio transversal que incluyó 100 muestras arteriales de 61 pacientes durante el primer semestre de 2024. La intensidad del dolor, reportada mediante la escala NRS-11, fue la variable principal de estudio. Se analizó la asociación de esta variable con variables gasométricas (por ejemplo, pH, pO2, pCO2 y lactato) y con otras variables sociodemográficas y relacionadas con punción arterial. Resultados. La edad fue de 69,43 ± 13,07 y el 68% eran hombres. Respecto a la variable principal de resultado, la puntuación media del dolor fue de 4,03 ± 2,61. La intensidad del dolor no mostró asociación con ninguna variable gasométrica. Sin embargo, el número de intentos de obtener con éxito una muestra arterial mostró significación. Tras ajustar por otras variables, cada intento adicional aumentaba el dolor en 1,14 puntos. Discusión. No se encontró asociación entre el dolor de la punción arterial y los parámetros del análisis gasométrico, por lo que los resultados pueden interpretarse de forma robusta en situaciones en las que no es posible un manejo adecuado del dolor.
ABSTRACT
Introduction. Arterial puncture for gasometrical analysis causes pain of varying intensity. This pain could alter the ventilatory dynamics and therefore the respiratory parameters of the blood sample. Objectives. To determine the possible relationship between the pain induced by arterial puncture and the parameters obtained from the gasometrical analysis of these blood samples. As secondary objectives, to obtain the prevalence of pain caused in the sample studied and the possible association with the number of attempts. Methodology. Cross-sectional study involving 100 arterial samples from 61 patients during the first half of 2024. Pain intensity reported by the NRS-11 was the main study variable. The association of this variable with gasometrical variables (for example: pH, pO2, pCO2, lactate) and with other variables of different nature (sociodemographic and related to the arterial puncture itself) was analyzed. Results. The age was 69,43 ± 13,07 and 68% were men. Regarding the main outcome variable, the mean pain score was 4.03 ± 2.61. Pain intensity showed no association with any of the gasometric variables. However, the number of attempts to successfully obtain an arterial sample showed significance. After adjustment for other variables, each additional attempt increased pain by 1.14 points. Discussion. No association was found between arterial puncture pain and gasometric analysis parameters, so the results can be robustly interpreted in situations where adequate pain management is not possible.
To examine how family caregivers of deceased nursing home residents scored and justified their ratings for each item on the Quality of Dying in Long-Term Care scale and to identify the consistencies and discrepancies between their perceptions and the scores assigned when assessing the residents' end-of-life experience.
A convergent mixed-methods design, comprising a cross-sectional study and a thematic analysis for quantitative and qualitative phases, respectively.
Quantitative and qualitative data were collected simultaneously between May 2018 and February 2019. The two sets of data were analysed separately. For the quantitative component, family caregivers completed the quality of dying in long-term care scale and a single-item question assessing the final month of the residents' life. Descriptive statistics, Mann–Whitney U-tests for comparative analyses and Spearman's correlations were applied to the quantitative data, while deductive thematic analysis was conducted for the qualitative data obtained through semi-structured interviews.
Sixty-nine family caregivers completed the QoD-LTC, and 11 participated in qualitative interviews. The mean overall QoD-LTC score was 39.29 (SD = 7.58). The highest-rated domain was ‘Personhood’ (M = 4.32; SD = 0.68), while the lowest was ‘Preparatory Tasks’ (M = 2.66; SD = 1.26). Interviewed family caregivers reported effective management of pain and other symptoms, satisfaction with the care provided and respectful and appropriate treatment. However, they identified significant shortcomings in communication concerning end-of-life issues, coping with death and advance care planning. Residents with cognitive impairment had significantly lower scores on the ‘closure’ (p < 0.01) and ‘preparatory tasks’ (p = 0.03) domains as well as on the overall QoD-LTC score (p = 0.01).
The findings demonstrate consistency between the quantitative and qualitative data, with high scores reported across most domains of the QoD-LTC scale, with the exception of the ‘Preparatory Tasks’ domain. Cognitive impairment among residents was associated with lower perceived quality of the dying process from the perspective of family members.
Aspects related to closure and preparatory tasks were often overlooked. Strategies to enhance end-of-life communication and advance care planning are needed.
The study adhered to the EQUATOR guidelines. The Mixed Methods Reporting in Rehabilitation & Health Sciences (MMR-RHS) checklist for mixed-methods studies, the STROBE checklist for cross-sectional studies, and the Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines for qualitative studies were used for reporting.
No funding was received for the completion of this study.
Differentiated thyroid cancer (DTC) is the most common endocrine malignancy, with a high 5-year survival rate of approximately 98%. Despite advances in diagnosis and treatment, up to 20% of patients experience recurrence, adversely affecting their quality of life. Predictive models have been developed to assess recurrence risk and guide clinical decision-making, but these models often face limitations such as retrospective design, lack of diversity in study populations and absence of external validation. The primary aim is to externally validate existing predictive models for DTC recurrence using prospective data from a diverse Latin American cohort. The secondary aim is to explore opportunities for model recalibration to improve their performance in our population.
The CaTaLiNA study is a multicentre prospective observational study conducted across 10 hospitals in five Latin American countries, including Ecuador, Peru, Uruguay and Mexico. Patients aged 18 years or older receiving treatment for DTC, such as the first thyroid surgery, active surveillance or radiofrequency ablation will be included. Recruitment will occur from November 2023 to June 2025, with follow-up extending until June 2028. Data collection will include baseline clinical, surgical and histological characteristics, treatment details and follow-up outcomes. Statistical analysis will follow the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis guidelines, using imputation strategies for missing data and evaluating calibration and discrimination of the prediction models. Calibration measures include the ratio of expected and observed events, calibration slope and calibration plot, while discrimination will be assessed using the C-index and area under the receiver operating characteristic curve.
This study protocol was approved by Comité de Ética de Investigación en Seres Humanos de la Universidad San Francisco de Quito USFQ ‘CEISH-USFQ’ APO-010–2023-CEIHS-USFQ Oficio No. 161-2023-CA-23030M-CEISH-USFQ. Results will be disseminated via peer-reviewed publications.
Little is known about the range and frequency of symptoms among older adult home healthcare patients with urinary incontinence, as this information is predominantly contained in clinical notes. Natural language processing can uncover symptom information among older adults with urinary incontinence to promote holistic, equitable care.
We conducted a secondary analysis of cross-sectional data collected between January 1, 2015, and December 31, 2017, from the largest HHC agency in the Northeastern United States. We aimed to develop and test a natural language processing algorithm to extract symptom information from clinical notes for older adults with urinary incontinence and analyze differences in symptom documentation by race or ethnicity.
Symptoms were identified through expert clinician-driven Delphi survey rounds. We developed a natural language processing algorithm for symptom identification in clinical notes, examined symptom documentation frequencies, and analyzed differences in symptom documentation by race or ethnicity using chi-squared tests and logistic regression models.
In total, 39,179 home healthcare episodes containing 1,098,419 clinical notes for 29,981 distinct patients were included. Nearly 40% of the sample represented racially or ethnically minoritized groups (i.e., 18% Black, 14% Hispanic, 7% Asian/Pacific Islander, 0.3% multi-racial, and 0.2% Native American). Based on expert clinician-driven Delphi survey rounds, the following symptoms were identified: anxiety, dizziness, constipation, syncope, tachycardia, urinary frequency/urgency, urinary hesitancy/retention, and vision impairment/blurred vision. The natural language processing algorithm achieved excellent performance (average precision of 0.92). Approximately 29% of home healthcare episodes had symptom information documented. Compared to home healthcare episodes for White patients, home healthcare episodes for Asian/Pacific Islander (odds ratio = 0.74, 95% confidence interval [0.67–0.80], p < 0.001), Black (odds ratio = 0.69, 95% confidence interval [0.64–0.73], p < 0.001), and Hispanic (odds ratio = 0.91, 95% confidence interval [0.85–0.97], p < 0.01) patients were less likely to have any symptoms documented in clinical notes.
We found multidimensional symptoms and differences in symptom documentation among a diverse cohort of older adults with urinary incontinence, underscoring the need for comprehensive assessments by clinicians. Future research should apply natural language processing to other data sources and investigate symptom clusters to inform holistic care strategies for diverse populations.
Knowledge of symptoms of older adult home healthcare patients with urinary incontinence can facilitate comprehensive assessments, health equity, and improved outcomes.
by Eva Maria C. Cutiongco-de la Paz, Jose B. Nevado Jr., Elizabeth T. Paz-Pacheco, Gabriel V. Jasul Jr., Aimee Yvonne Criselle L. Aman, Mark David G. Francisco
Type 2 diabetes mellitus leads to debilitating complications that affect the quality of life of many Filipinos. Genetic variability contributes to 30% to 70% of T2DM risk. Determining genomic variants related to type 2 diabetes mellitus susceptibility can lead to early detection to prevent complications. However, interethnic variability in risk and genetic susceptibility exists. This study aimed to identify variants associated with type 2 diabetes mellitus among Filipinos using a case-control design frequency matched for age and sex. A comparison was made between 66 unrelated Filipino adults with type 2 diabetes mellitus and 121 without. Genotyping was done using a candidate gene approach on genetic variants of type 2 diabetes mellitus and its complications involving allelic association and genotypic association studies with correction for multiple testing. Nine (9) significant variants, mostly involved in glucose and energy metabolism, associated with type 2 diabetes mellitus in Filipinos were found. Notably, a CDKAL1 variant (rs7766070) confers the highest level of risk while rs7119 (HMG20A) and rs708272 (CETP) have high risk allele frequencies in this population at 0.77 and 0.66, respectively, making them potentially good markers for type 2 diabetes mellitus screening. The data generated can be valuable in developing genetic risk prediction models for type 2 diabetes mellitus to diagnose and prevent the condition among Filipinos.The healthcare industry increasingly values high-quality and personalized care. Patients with heart failure (HF) receiving home health care (HHC) often experience hospitalizations due to worsening symptoms and comorbidities. Therefore, close symptom monitoring and timely intervention based on risk prediction could help HHC clinicians prevent emergency department (ED) visits and hospitalizations. This study aims to (1) describe important variables associated with a higher risk of ED visits and hospitalizations in HF patients receiving HHC; (2) map data requirements of a clinical decision support (CDS) tool to the exchangeable data standard for integrating a CDS tool into the care of patients with HF; (3) outline a pipeline for developing a real-time artificial intelligence (AI)-based CDS tool.
We used patient data from a large HHC organization in the Northeastern US to determine the factors that can predict ED visits and hospitalizations among patients with HF in HHC (9362 patients in 12,223 care episodes). We examined vital signs, HHC visit details (e.g., the purpose of the visit), and clinical note–derived variables. The study identified critical factors that can predict ED visits and hospitalizations and used these findings to suggest a practical CDS tool for nurses. The tool's proposed design includes a system that can analyze data quickly to offer timely advice to healthcare clinicians.
Our research showed that the length of time since a patient was admitted to HHC and how recently they have shown symptoms of HF were significant factors predicting an adverse event. Additionally, we found this information from the last few HHC visits before the occurrence of an ED visit or hospitalization were particularly important in the prediction. One hundred percent of clinical demographic profiles from the Outcome and Assessment Information Set variables were mapped to the exchangeable data standard, while natural language processing–driven variables couldn't be mapped due to their nature, as they are generated from unstructured data. The suggested CDS tool alerts nurses about newly emerging or rising risks, helping them make informed decisions.
This study discusses the creation of a time-series risk prediction model and its potential CDS applications within HHC, aiming to enhance patient outcomes, streamline resource utilization, and improve the quality of care for individuals with HF.
This study provides a detailed plan for a CDS tool that uses the latest AI technology designed to aid nurses in their day-to-day HHC service. Our proposed CDS tool includes an alert system that serves as a guard rail to prevent ED visits and hospitalizations. This tool can potentially improve how nurses make decisions and improve patient outcomes by providing early warnings about ED visits and hospitalizations.
This study examines whether racism exists among Jewish and Arab patients in Israel, as reflected in patient preference for receiving treatment from a nurse with the same ethnic background.
We examine the relationship between racism and the level of trust in a nurse from a different ethnic group than the patient, as well as the preferred level of social distance, in the context of ongoing conflicts between the Jewish majority and the Arab minority in Israel.
A cross-sectional study was conducted using a unique study questionnaire that asked 534 Jewish and 478 Arab respondents to express their preference for an Arab and a Jewish nurse.
Among both the Jews and the Arabs, there is a similar tendency of racism toward nurses of the dissimilar ethnic group. This racism was also prevalent among participants who live in a mixed environment or those who studied or are studying and worked or work in a mixed environment. As the trust in nursing staff members from the other group increases, the level of racism decreases. The greater the social distance the participants felt from the members of the other group, the more racist the attitudes they expressed.
Both Jews and Arabs preferred to be treated by nurses of their own ethnic group. In contrast to the contact hypothesis theory, participants who live in a mixed environment did not express fewer racist preferences. We conclude with some useful practical suggestions aimed at decreasing racism in health care.
Findings imply that prospective patients prefer to receive nursing care from nurses of their own ethnic group and trust these nurses more than they trust nurses of different ethnic group.
Identifying health problems in audio-recorded patient–nurse communication is important to improve outcomes in home healthcare patients who have complex conditions with increased risks of hospital utilization. Training machine learning classifiers for identifying problems requires resource-intensive human annotation.
To generate synthetic patient–nurse communication and to automatically annotate for common health problems encountered in home healthcare settings using GPT-4. We also examined whether augmenting real-world patient–nurse communication with synthetic data can improve the performance of machine learning to identify health problems.
Secondary data analysis of patient–nurse verbal communication data in home healthcare settings.
The data were collected from one of the largest home healthcare organizations in the United States. We used 23 audio recordings of patient–nurse communications from 15 patients. The audio recordings were transcribed verbatim and manually annotated for health problems (e.g., circulation, skin, pain) indicated in the Omaha System Classification scheme. Synthetic data of patient–nurse communication were generated using the in-context learning prompting method, enhanced by chain-of-thought prompting to improve the automatic annotation performance. Machine learning classifiers were applied to three training datasets: real-world communication, synthetic communication, and real-world communication augmented by synthetic communication.
Average F1 scores improved from 0.62 to 0.63 after training data were augmented with synthetic communication. The largest increase was observed using the XGBoost classifier where F1 scores improved from 0.61 to 0.64 (about 5% improvement). When trained solely on either real-world communication or synthetic communication, the classifiers showed comparable F1 scores of 0.62–0.61, respectively.
Integrating synthetic data improves machine learning classifiers' ability to identify health problems in home healthcare, with performance comparable to training on real-world data alone, highlighting the potential of synthetic data in healthcare analytics.
This study demonstrates the clinical relevance of leveraging synthetic patient–nurse communication data to enhance machine learning classifier performances to identify health problems in home healthcare settings, which will contribute to more accurate and efficient problem identification and detection of home healthcare patients with complex health conditions.
Home healthcare (HHC) enables patients to receive healthcare services within their homes to manage chronic conditions and recover from illnesses. Recent research has identified disparities in HHC based on race or ethnicity. Social determinants of health (SDOH) describe the external factors influencing a patient's health, such as access to care and social support. Individuals from racially or ethnically minoritized communities are known to be disproportionately affected by SDOH. Existing evidence suggests that SDOH are documented in clinical notes. However, no prior study has investigated the documentation of SDOH across individuals from different racial or ethnic backgrounds in the HHC setting. This study aimed to (1) describe frequencies of SDOH documented in clinical notes by race or ethnicity and (2) determine associations between race or ethnicity and SDOH documentation.
Retrospective data analysis.
We conducted a cross-sectional secondary data analysis of 86,866 HHC episodes representing 65,693 unique patients from one large HHC agency in New York collected between January 1, 2015, and December 31, 2017. We reported the frequency of six SDOH (physical environment, social environment, housing and economic circumstances, food insecurity, access to care, and education and literacy) documented in clinical notes across individuals reported as Asian/Pacific Islander, Black, Hispanic, multi-racial, Native American, or White. We analyzed differences in SDOH documentation by race or ethnicity using logistic regression models.
Compared to patients reported as White, patients across other racial or ethnic groups had higher frequencies of SDOH documented in their clinical notes. Our results suggest that race or ethnicity is associated with SDOH documentation in HHC.
As the study of SDOH in HHC continues to evolve, our results provide a foundation to evaluate social information in the HHC setting and understand how it influences the quality of care provided.
The results of this exploratory study can help clinicians understand the differences in SDOH across individuals from different racial and ethnic groups and serve as a foundation for future research aimed at fostering more inclusive HHC documentation practices.
Objetivo principal: identificar qué actividades guían el trabajo de la enfermera en una unidad de cuidados intensivos para adultos. Metodología: revisión integradora, realizada sobre la base de Literatura Latinoamericana y del Caribe en Ciencias de la Salud y Sistema de Análisis y Recu-peración de Literatura Médica en línea, entre enero y febrero de 2019. La búsqueda resultó en 15 producciones, que fueron analizadas a través del análisis de contenido temático. Resultados principales: a partir del análisis de los estudios, surgió la siguiente categoría temática: “Actividades que guían el trabajo de la enfermera en una unidad de cuidados intensivos para adultos”, destacando: observación y vigilancia constantes, manejo de instrumentos tecnológicos e interpretación de información de estos dispositivos, desempeño y comunicación entre un equipo multidisciplinario, realizando una evaluación y plan de atención al paciente. Conclusión principal: aunque algunas actividades pueden caracterizarse como técnicas, también existen aquellas que involucran la subjetividad de las enfermeras, dirigidas a una atención más individualizada y guiadas por el ejercicio de la autonomía.
Objetivo principal: Determinar los aspectos educativos de la diabetes mellitus tipo 2 en la etapa infanto-juvenil. Metodología: Revisión bibliográfica narrativa, en inglés y español, publicada en los últimos 10 años e indexada en diferentes bases de datos de Ciencias de la Salud (MEDLINE, ScienceDirect, SciELO y CUIDEN). Resultados principales: La diabetes mellitus tipo 2 una enfermedad emergente en la población infantil. Las intervenciones de enfermería consisten en educación para la saluden la adquisición de hábitos de vida saludables. La familia supone un eje fundamental en la estrategia de cuidados. Conclusión principal: Las intervenciones enfermeras deben estar encaminadas a la Educación para la Salud y, en caso de diagnóstico de la enfermedad, realizar entrevistas terapéuticas, fomentando la motivación y autoconfianza, con el apoyo de la familia.
Introducción. La quimioterapia produce el efecto secundario más temido por los pacientes con cáncer, la alopecia, que podría evitarse con gorros de crioterapia del cuero cabelludo. Objetivo principal. Evaluar la crioterapia del cuero cabelludo como método preventivo para la alopecia inducida por quimioterapia. Metodología. Se ha realizado una revisión bibliográfica narrativa, seleccionándose 22 artículos, introduciendo ecuaciones de búsqueda en varias bases de datos. Desarrollo. Su eficacia es difícil de determinar y la efectividad es muy variable, aprobándose en pacientes con cánceres sólidos. Sin embargo, existen ciertos efectos secundarios, requiriéndose de cuidados de enfermería independientemente de la técnica utilizada. Conclusiones. Estudios han demostrado que el uso de este método es eficaz y efectivo, y que su uso no aumenta el riesgo de metástasis en el cuero cabelludo, contraindicándose en pacientes con tumores hematoló-gicos.
Objetivos: Caracterizar el estado emocional y la percepción del paso del tiempo en el paciente con enfermedad crónica avanzada, y compararlo con la Escala de Ansiedad y Depresión Hospitalaria. Metodología: Es un estudio cuantitativo de tipo observacional descriptivo y transversal, mediante el cual profundizamos en el estado emocional del paciente. Basado en la administración de un cuestionario para recoger variables demográficas y clínicas, en el que se integró el Índice de Karnofsky, Escala de percepción subjetiva del tiempo de Bayés, Escala Breve de Introspección del Estado de Ánimo, Escala de Evaluación de Síntomas de Edmonton y Ansiedad y Depresión Hospitalaria. Resultados: Los pacientes con enfermedad crónica avanzada presentaron altos niveles de sintomatología ansiosa y depresiva, y una predominancia de los estados de ánimo negativos, existiendo correlación entre las respuestas de los pacientes a la escala de Ansiedad y Depresión Hospitalaria y los estados emocionales identificados mediante la Escala Breve de Introspección del Estado de Ánimo. Respecto al paso del tiempo estos pacientes lo perciben como lento o muy lento, existiendo correlación con la presencia de sintomatología ansiosa y depresiva. Conclusiones: La percepción subjetiva del tiempo y la descripción de los estados de ánimo evaluados mediante la Escala Breve de Introspección del Estado de Ánimo pueden ser una buena herramienta para la detección de malestar emocional.
FreshRSS 