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SciELO-GL

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Introduction
Tuberculosis continues to be a threat worldwide.
Consequently, many healthcare workers HCW are at risk of being infected and acquiring this disease.
Good prevention programs should be established to avoid this undesirable outcome in healthcare facilities.
To evaluate such programs, quality indicators can be used to identify the level of compliance for recommended practices.
Quality indicator technology has been increasingly used for evaluating health care practices. They are quantitative measures of features or attributes of a given process or system, which may indicate the heath care quality provided, as well as specific needs for improvement. Three classical categories have been used for their classification: structure, process and outcome.The advantage of one over the other lies in the characteristics of the phenomenon to be measured.
Structure indicators refer to the features required, such as human resources, equipment, information systems, etc. Process indicators measure the dynamics of a given process, or how this particular process was performed. Outcome indicators measure the frequency in which event occurs, and assess final goals, such as mortality, morbidity or patient satisfaction.
Ideal indicators include features such as acceptability, objectivity, effectiveness, reliability, feasibility and availability, communication, interpretability, reproducibility, context, sensitivity to change, efficiency, and comparability.
In 2006, a group of researchers in Brazil constructed and validated a set of indicators designed to evaluate the quality of programs for healthcare-associated infection HAI prevention, including occupational tuberculosis. They can also be used to gauge the extent to which the control of HAI differs between different institutions.
Although the content was validated by professional experts, these indicators have not yet been fully tested.
Due to great difficulty in finding patterns for feasibility assessment in the literature, the best criteria for defining feasibility was previously discussed in a focus group with specialists.
The criterion "time" was chosen as a way of classifying these indicators as feasible.
Providing the extent of time spent in measuring the indicator is as short as possible, the indicator is considered feasible.
The shorter the time, the lower the human resources expense, and the more likely the indicator is to be widely use.
In the present study we aimed to analyze the feasibility of these quality indicators for the evaluation of programs for preventing occupational tuberculosis.
This descriptive, cross-sectional study tested the feasibility of quality indicators aimed at evaluating elements of structure, process and outcome of occupational tuberculosis prevention programs in different healthcare facilities.
Time required for the calculationof the indicators was assessed as a measure of feasibility.
The quality indicators are described in Figure 1, with a brief description, formula, ideal values, sources of information, components of analysis, evaluation criteria and sample.
Indicators were applied in six different institutions in the city of São Paulo, Brazil, which met the following requirements: a acute care hospital, b public or private setting, c caring for patients with suspected or confirmed pulmonary or laryngeal tuberculosis in the bacillary phase, and d having a formal Healthcare-associated Infection Control Committee HICC.
Selected variables were used to characterize the participant institutions and to identify the components that may contribute to the variations in the time required to calculate the indicators.
These variables included the number of active beds; the average prevalence of daily or monthly inpatients with pulmonary orlaryngeal tuberculosis bacillus and aerosol precautions indicated, number of employees in the institution, and nature of the institution public / private / philanthropic.
Data were collected using a standardized form, and the time was measured using a chronometer.
Secondary variables were collected in order to identify elements justifying the time spent to collect each indicator.
Periods of interruption and time intervals were deducted from the overall time span of the activity.
Also, the time spent on healthcare facility characterization, as well as the time required to access the hospital facilities reception, elevators, etc. was not included in data collection.
Indicators were tested by the same researcher in all healthcare facilities T.R.S..
The variables of analysis were the time spent on: a data collection, and b data consolidation and analysis.
We compared the time spent on testing of each indicator in the different institutions.
Data were collected from December 2010 to July 2012.
This period was required to complete data collection in all six institutions, due to the small number of inpatients having pulmonary or laryngeal tuberculosis who were placed in aerosol precautions in some of the hospitals.The data analysis was descriptive.
Among the six institutions in which the quality indicators were tested, four were general hospitals, one was a hospital specializing in infectious disease, and one was a general hospital, although it served as a reference site for tuberculosis treatment Table 1.
Among 2,655 beds in six institutions, 55.54% 1,480 were public.
Altogether, these institutions had approximately 24,271 health workers, 45.91% 11,145 in the public sector.
Among the 690 hospitalized patients with diagnosed or suspected pulmonary or laryngeal tuberculosis, 94.63% 653 were admittedtopublic institutions.
All evaluated facilities had the same recommendation for the use of a N95 particulate respirator: to put it on in the anteroom or in the hallway before entering the room of a patient with known or suspected pulmonary or laryngeal tuberculosis bacillus.
The TORPS indicator resulted in minimal effort and time spent on its application in all institutions Table 1 Regarding the TOSCI indicator, the information necessary for its calculation was not found in five of the six health institutions.
Several arguments were used to report the absence of the use of Tuberculosis Skin Test TST: lack of trained personnel to perform the test, the porosity of collection, frequent lack of HCW follow-up for appropriate characterization of the reaction; difficulty in identifying the exact time period of the HCW's exposure to the mycobacterium.
The TOI indicator was collected in five of the six institutions; there was only one healthcare facility in which data were not organized in such a way that it could be collected.
The time used to collect this indicator was not toolong, but depended on the level of data organization.
The TOPWC indicator required greater time for calculationTable 1.
To note, public hospitals were more likely to require less time to collect data than the private sector.
In public hospitals there are usually more patients admitted with tuberculosis, therefore it was possible to observe two or more patients simultaneously, thus reaching 51 observations more rapidly.
Discussion
Many quality indicators have been proposed in the literature, however few have been evaluated regarding their feasibility for application, which creates a gap between theory and practice.
Nevertheless, the recommendation for their use is quite frequent.
To our knowledge, the present study is the first to evaluate the feasibility of quality indicators, using as the criterion the time spent on administering / calculatingthem.
Information on quality of care depends upon data availability.
Therefore, quality is difficult to measure without correct and consistent information, which is often unavailable. A previous study evaluated the feasibility of quality indicators related to radical prostatectomy and concluded that indicators not obtaining more than 25.9% of the necessary information were considered unenforceable.
It has also been previously shown that quality indicators for antibiotic treatment of complicated urinary tract infections were considered feasible if the data necessary to score the indicator can be abstracted from the available data for >70% of cases. Indicators should require ease of obtaining data or ease of availability of the data as a condition of feasibility, resulting in minimal effort and additional cost.
Because time spent on data gathering and analysis reflects both on efforts and cost, less time means higherf easibility.
Although time spent on the application of quality indicators of an occupational tuberculosis prevention program may vary in different healthcare facilities, some common features were noted from this study.
For instance, the indicator that evaluated the structure of the program TORPS proved to be highly feasible.
This indicator has characteristics suggestive of being used for external audits and evaluations.
On the other hand, the process indicator TOPWC requires greater dedication of professional time for its application.
This indicator should be used preferentially by healthcare facilities that have a higher number of in-patients requiring special precautions for tuberculosis, aiming to evaluate compliance with the use of the N95 mask by HCWs.
As a suggestion, TOPWC could be applied biannually, or after major intervention and training programs.
It is a matter for discussion as to why, despite recommendations, some healthcare facilities in Brazil are not using the TST routinely, as we demonstrated in our sample.
As an outcome to be measured, it was shown that the indicator for skin conversion TOSCI was not feasible due to this lack of compliance.
The Centers for Disease Control recommends the use of the TST whenever there is the possibility of high exposure to tuberculosis.
HCWs should be periodically screened for latent tuberculosis infection using TST.
As pointed out, concerning the healthcare facilities, many operational issues can interfere in the process.
Among these issues, are the high turnover of HCWs, the limitations of the TST interpretation, and a potential booster effect of the BCG vaccine.In order to overcome the booster effect, a two-step TST has been suggested in the literature.The TST has a high sensitivity, but lacks specificity in a vaccinated population, such as the HCWs in Brazil.
Due to this feature, countries such as France and Japan are now recommending, with some restrictions, the gama-interferon release assays as a substitute for TST.
To note, in our sample, none of the healthcare facilities that were not using TST provided any other screening measure as a substitute.
The main outcome indicator TOI, which measures the incidence of cases of tuberculosis among HCW, is quite simple to obtain, provided the Occupational Medicine Service has a structured form to record such cases.
Usually cases of occupational tuberculosis are not as frequent as to warrant a great deal of effort in recording them.
Besides this, the number of exposed HCWs is, in general, quite steady and does not require a sophisticated system to collect the information.
Despite this, many healthcare facilities are not aware of monitoring the annual incidence of occupational cases of tuberculosis.
The World Health Organization WHO shows that tuberculosis mortality in Brazil in 2013 was 3.2/100.000 and the prevalence was 57/100.000.
Some authors have published similar results.
A Peruvian study found a tuberculin test conversion incidence in medical students of approximately 3%.
A Brazilian study conducted in Belo Horizonte, MG, Brazil, where the tuberculosis incidence rate is 23/100.000, had the cooperation of 251 HCWs.
The TST conversion was 5.1%, with the risk of infection of 1.4.
A study aimed to identify the TST conversion rate of HCWs with previously negative TST results who had been working for less than 1 year in a hospital in Botswana, where tuberculosis is highly endemic.
This population had a conversion rate of 4.2% for the entire group studied, or 6.87 per 1000 person-weeks.
A Chinese study showed that the health care workers' annual tuberculosis notification rates were lower than the general population.
Healthcare workers with tuberculosis were a mean of 35.5 years old, with females out numbering males 58.0%>42.0%.
The proportion of pulmonary tuberculosis was significantly higher among the women compared with men 88.5%>83.4%, p = 0.031.
This study suggested that the priority for tuberculosis prevention in healthcare institutions should be given to the young female HCWs.
An Argentinean study that included 15,276 HCWs from 15 centers found a mean incidence rate of tuberculosis in 111.3/100,000 HCWs; A Brazilian study demonstrated incidence rates in the general population of approximately 62/100,000, a prevalence of tuberculosis infection in HCW of 63.1% and an annual rate of tuberculin conversion of 10.7%.
In such an epidemiologic context, monitoring the incidence of occupational tuberculosis and the TST conversion can aid institutions in planning and evaluating strategies for occupational tuberculosis prevention, as demonstrated by other authors.
With 1.5 million deaths in 2013 and 5.7 million new cases of tuberculosis disease, the WHO goal is to dramatically reduce the global burden of tuberculosis by 2015.
For this control, it will be necessary to include the successful development and application of new drugs, diagnostics, vaccines, and prevention tools as well as a clearer understanding of the impact of social and economic determinants of this disease in the health sector.
The quality indicators of programs for prevention of occupational tuberculosis evaluated in the present study were shown to be feasible.
Since HCWs have 2- 50 times the chance of acquiring the disease than people in the general population, these indicators can help institutions prevent occupational tuberculosis.
Therefore, we recommend their application at least once a year in healthcare facilities that frequently deal with patients affected by tuberculosis.
The results are limited by the small amount of participant institutions, which only enables a suggestion of possible relationships between indicators and the institutional profile.
Further studies should include multiple institutions to enable the investigation of relationships between the nature of the institution and the feasibility of applying the quality indicators. , There were not many objective criteria found in the literature that allowed for the evaluation of the applicability of indicators, so it was decided to use time as a marker.
However, we understand that this is a specific perspective that limits the study.
This study brings new insight to the applicability of previously validated quality indicators, revealing that even a validated indicator may not have all the properties of applicability; this approach needs to be considered to suggest recommendations for their use.
Moreover, strengths in the structure assessment, and weaknesses in the process and outcomes assessments, have been identified.
Areas to be improved include maintaining periodic screening for latent tuberculosis using TST, monitoring the annual incidence of occupational cases of tuberculosis, and evaluating compliance with occupational prevention.
Conclusion
The indicators to evaluate the structure for occupational tuberculosis prevention are highly feasible.
The feasibility of applying indicators for process and outcome is limited, due to relevant differences in administrative issues at healthcare facilities, such as the system for data archiving and management.
ECG Comments
The ECG is a poorly specific method to determine the size of the myocardial infarction.
Several studies have shown how many errors are made when this type of assessment is used for this purpose.
Among them, the study by Yusuf et al. showed that there was no correlation between the maximum number of leads with ST-segment elevation, or of Q or QS waves and CKMB levels.
However, there is a situation in which the ECG can, with a good chance, identify the extensive myocardial infarction: when there are inactive areas in the I, aVL and V1 to V6 leads, followed by absence of R or a very small R, usually lower than 5mV.

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Dataset Card for Spanish–Galician / English–Galician Scientific Corpus (SciELO)

Dataset Summary

The SciELO Corpus, hosted in theOPUS repository, is a large-scale parallel resource composed of full scientific articles extracted from the Scientific Electronic Library Online (SciELO). It provides high-quality sentence pairs between Spanish, Portuguese, and English across diverse academic domains.

This corpus is particularly valuable for training machine translation models, as it offers specialized terminology density and complex grammatical structures that reflect real scientific and technical language usage in Latin America and Iberia.

To address the lack of publicly available Galician data in this domain, Portuguese segments were adapted into Galician using transliteration and localization tools found in our text pipeline and Apertium. The resulting texts were then normalized through our cleaning pipeline, ensuring consistency and readiness for model development.

The final resource is a parallel scientific corpus of ~300,000 aligned sentences for the pairs Spanish–Galician and English–Galician.

Dataset Creation

Apertium pt-gl: We translate original Portuguese segments into Galician using symbolic rules.
Transliteration and localization: Using port2gal, we improve Apertium's output by processing all leftover tags for out-of-vocabulary words, which we either transliterate to Spanish orthography or localize to a more common Galician word.
Encoding errors: The entire text was scanned for encoding errors ensuring it is utf-8 encoded.
Deduplication: The filtered datasets were deduplicated to remove redundant sentence pairs.
Pyplexity: We used pyplexity to filter texts that may contain non-linguistic content.
Normalization: The final Galician text present here was normalized (linguistically) to adhere to the autonomous standard of the Galician language.

Supported Tasks and Benchmarks

Machine Translation (MT): Training and evaluation of MT systems for Galician in scientific domains.
Terminology Extraction: Building specialized bilingual glossaries for scientific and technical fields.
Cross-lingual NLP: Supporting multilingual embeddings and semantic alignment in academic texts.
Evaluation: Benchmarking translation quality in specialized scientific corpora.

Languages

Spanish-Galician, English-Galician

Dataset Structure

Format: Parallel text segments (aligned sentences)
Domain: Scientific articles (multiple disciplines)
Size: ~300,000 lines

Use Cases

Training MT models for Galician in specialized scientific contexts.
Creating bilingual dictionaries and glossaries for academic terminology.
Supporting research in cross-lingual transfer for underrepresented languages.
Evaluating translation systems in scientific and technical domains.

Limitations

Domain-specific: Focused on scientific texts, which may not generalize to everyday language.
Automatically adapted Galician segments may contain transliteration or translation artifacts.

Funding

This work is funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project Desarrollo de Modelos ALIA. Esta publicación del proyecto Desarrollo de Modelos ALIA está financiada por el Ministerio para la Transformación Digital y de la Función Pública y por el Plan de Recuperación, Transformación y Resiliencia – Financiado por la Unión Europea – NextGenerationEU.

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