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Artificial Neural Networks Applied to Prediction to Assess the Likelihood of Surgical Site Infection in Different Surgeries
- Flávio Souza, Braulio Couto, Felipe Leandro Andrade da Conceição, Gabriel Henrique Silvestre da Silva, Igor Gonçalves Dias, Rafael Vieira Magno Rigueira, Gustavo Maciel Pimenta, Maurilio Martins, Julio Cesar Mendes, Vladimir Alexei Rodrigues Rocha, Ana Luiza de Oliveira Rocha, Breno Henrique Colares Silva, Bruna Stella Vieira do Nascimento, Carolina Nunes Dutra, Luiza Pedrosa Gomes, Maria Clara Vilaça, Julia D. O. Matias, Laís L. de Araújo, Luaan S. Rossati, Layna R. Polidoro
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, p. s129
- Print publication:
- October 2020
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Background: Based on data obtained from hospitals in the city of Belo Horizonte (population ~3,000,000), we evaluated relevant factors such as death, age, duration of surgery, potential for contamination and surgical site infection, plastic surgery, and craniotomy. The possibility of predicting surgical site infection (SSI) was then analyzed using pattern recognition algorithms based on MLP (multilayer perceptron). Methods: Data were collected by the hospital infection control committees (CCIHs) in hospitals in Belo Horizonte between 2016 and 2018. The noisy records were filtered, and the occurrences were analyzed. Finally, the predictive power of SSI of 5 types MLP was evaluated experimentally: momentum, backpropagation standard, weight decay, resilient propagation, and quick propagation. The model used 3, 5, 7, and 10 neurons in the occult layer and with resamples varied the number of records for testing (65% and 75%) and for validation (35% and 25%). Comparisons were made by measuring the AUC (area under the curve (range, 0–1). Results: From 1,096 records of craniotomy, 289 were usable for analysis. Moreover, 16% died; averaged age was 56 years (range, 40–65); mean time of surgery was 186 minutes (range, 95–250 minutes); the number of hospitalizations ranged from 1 (90.6%) to 8 (0.3%). Contamination among these cases was rated as follows: 2.7% contaminated, 23.5% potentially contaminated, 72.3% clean. The SSI rate reached 4%. The prediction process in AUCs ranged from 0.7 to 0.994. In plastic surgery, from 3,693 records, 1,099 were intact, with only 1 case of SSI and no deaths. The average age for plastic surgery was 41 years (range, 16–91); the average time of surgery was 218.5 minutes (range, 19–580 minutes); the number of hospitalizations ranged from 1 (77.4%) to 6 times (0.001%). Contamination among these cases was rated as follows: 27.90% potential contamination, 1.67% contaminated, and 0.84% infected. The prediction process ranged in AUCs from 0.2 to 0.4. Conclusions: We identified a high noise index in both surgeries due to subjectivity at the time of data collection. The profiles of each surgery in the statistical analyses were different, which was reflected in the analyzed structures. The MLP for craniotomy surgery demonstrated relevant predictive power and can guide intelligent monitoring software (available in www.sacihweb.com). However, for plastic surgeries, MLPs need more SSI samples to optimize outcomes. To optimize data collection and to enable other hospitals to use the SSI prediction tool, a mobile application was developed.
Disclosures: None
Funding: None
Automated Risk Analysis of Surgical Site Infection in Hip Arthroplasty Surgeries
- Flávio Souza, Braulio Couto, Felipe Leandro Andrade da Conceição, Gabriel Henrique Silvestre da Silva, Igor Gonçalves Dias, Rafael Vieira Magno Rigueira, Gustavo Maciel Pimenta, Maurilio Martins, Julio Cesar Mendes, Ana Flavia Viana Quintão, Camila Vieira Brandão, Débora Martins Borges, Eduarda Muzzi Torres Lage, Luiza da Conceição Sabadini, Sabrina de Almeida Lopes
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, pp. s135-s136
- Print publication:
- October 2020
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Background: In 7 hospitals in Belo Horizonte, a city with >3,000,000 inhabitants, a survey was conducted between July 2016 and June 2018, focused on surgical site infection (SSI) in patients undergoing arthroplasty surgery procedures. The main objective is to statistically evaluate such incidences and enable a study of the prediction power of SSI through pattern recognition algorithms, the MLPs (multilayer perceptron). Methods: Data were collected on SSI by the hospital infection control committees (CCIHs) of the hospitals involved in the research. All data used in the analysis during their routine SSI surveillance procedures were collected. The information was forwarded to the NOIS (Nosocomial Infection Study) Project, which used SACIH automated hospital infection control system software to collect data from a sample of hospitals participating voluntarily in the project. After data collection, 3 procedures were performed: (1) a treatment of the database collected for the use of intact samples; (2) a statistical analysis on the profile of the hospitals collected; and (3) an assessment of the predictive power of 5 types of MLP (backpropagation standard, momentum, resilient propagation, weight decay, and quick propagation) for SSI prediction. MLPs were tested with 3, 5, 7, and 10 hidden layer neurons and a database split for the resampling process (65% or 75% for testing and 35% or 25% for validation). The results were compared by measuring AUC (area under the curve; range, 0–1) presented for each of the configurations. Results: Of 1,246 records, 535 were intact for analysis. We obtained the following statistics: the average surgery time was 190 minutes (range, 145–217 minutes); the average age of the patients was 67 years (range, 9–103); the prosthetic implant index was 98.13%; the SSI rate was 1.49%, and the death rate was 1.21%. Regarding the prediction power, the maximum prediction power was 0.744. Conclusions: Despite the considerable loss rate of almost 60% of the database samples due to the presence of noise, it was possible to perform relevant sampling for the profile evaluation of hospitals in Belo Horizonte. For the predictive process, some configurations have results that reached 0.744, which indicates the usefulness of the structure for automated SSI monitoring for patients undergoing hip arthroplasty surgery. To optimize data collection and to enable other hospitals to use the SSI prediction tool (available in www.sacihweb.com ), a mobile application was developed.
Funding: None
Disclosures: None
The “CHROME criteria”: Tool to optimize and audit prescription quality of psychotropic medications in institutionalized people with dementia
- Ruben Muñiz, Alia I. Pérez-Wehbe, Francisco Couto, María Pérez, Noemí Ramírez, Alejandro López, Javier Rodríguez, Teresa Usieto, Lietzan Lavin, Ana Rigueira, Luis Agüera-Ortiz, Jorge López-Alvarez, Manuel Martín-Carrasco, Javier Olazarán
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- Journal:
- International Psychogeriatrics / Volume 32 / Issue 3 / March 2020
- Published online by Cambridge University Press:
- 22 October 2019, pp. 315-324
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Objective:
Describe and validate the CHROME (CHemical Restraints avOidance MEthodology) criteria.
Design:Observational prospective longitudinal study.
Setting:Single nursing home in Las Palmas de Gran Canaria, Spain.
Participants:288 residents; mean age: 81.6 (SD 10.6). 77.4% had dementia.
Intervention:Multicomponent training and consultancy program to eliminate physical and chemical restraints and promote overall quality care. Clinicians were trained in stringent diagnostic criteria of neuropsychiatric syndromes and adequate psychotropic prescription.
Measurements:Psychotropic prescription (primary study target), neuropsychiatric syndromes, physical restraints, falls, and emergency room visits were semi-annually collected from December 2015 to December 2017. Results are presented for all residents and for those who had dementia and participated in the five study waves (completer analysis, n=107).
Results:For the study completers, atypical neuroleptic prescription dropped from 42.7% to 18.7%, long half-life benzodiazepines dropped from 25.2% to 6.5%, and hypnotic medications from 47.7% to 12.1% (p<0.0005). Any kind of fall evolved from 67.3 to 32.7 (number of falls by 100 residents per year). Physicians’ diagnostic confidence increased, while the frequency of diagnoses of neuropsychiatric syndromes decreased (p<0.0005).
Conclusions:Implementing the CHROME criteria reduced the prescription of the most dangerous medications in institutionalized people with dementia. Two independent audits found no physical or chemical restraint and confirmed prescription quality of psychotropic drugs. Adequate diagnosis and independent audits appear to be the keys to help and motivate professionals to optimize and reduce the use of psychotropic medication. The CHROME criteria unify, in a single compendium, neuropsychiatric diagnostic criteria, prescription guidelines, independent audit methodology, and minimum legal standards. These criteria can be easily adapted to other countries.