Post-COVID-19 respiratory sequelae two years after hospitalization: an ambidirectional study.

Background: COVID-19 lung sequelae can impact the course of patient lives. We investigated the evolution of pulmonary abnormalities in post-COVID-19 patients 18-24 months after hospital discharge. Methods: A cohort of COVID-19 patients admitted to the Hospital das Clínicas da Faculdade de Medicina da USP in São Paulo, Brazil, between March and August of 2020, were followed-up 6-12 months after hospital discharge. A subset of patients with pulmonary involvement and chest computed tomography (CT) scans were eligible to participate in this second follow-up (18-24 months). Data was analyzed in an ambidirectional manner, including retrospective data from the hospitalization, and from the first follow-up (6-12 months after discharge), and compared with the prospective data collected in this new follow-up. Findings: From 348 patients eligible, 237 (68%) participated in this follow-up. Among participants, 139 (58%) patients presented ground-glass opacities and reticulations, and 80 (33%) presented fibrotic-like lesions (traction bronchiectasis and architectural distortion). Five (2%) patients improved compared to the 6-12-month assessment, but 20 (25%) of 80 presented worsening of lung abnormalities. For those with relevant assessments on both occasions, comparing the CT findings between this follow-up with the previous assessment, there was an increase in patients with architectural distortion (43 [21%] of 204 vs 57 [28%] of 204, p = 0.0093), as well as in traction bronchiectasis (55 [27%] of 204 vs 69 [34%] of 204, p = 0.0043). Patients presented a persistent functional impairment with demonstrated restrictive pattern in both follow-ups (87 [42%] of 207 vs 91 [44%] of 207, p = 0.76), as well as for the reduced diffusion capacity (88 [42%] of 208 vs 87 [42%] of 208, p = 1.0). Length of hospitalization (OR 1.04 [1.01-1.07], p = 0.0040), invasive mechanical ventilation (OR 3.11 [1.3-7.5] p = 0.011), patient's age (OR 1.03 [1.01-1.06] p = 0.0074 were consistent predictors for development of fibrotic-like lung lesions in post-COVID-19 patients. Interpretation: Post-COVID-19 lung sequelae can persist and progress after hospital discharge, suggesting airways involvement and formation of new fibrotic-like lesions, mainly in patients who were in intensive care unit (ICU). Funding: São Paulo Research Foundation (22/01769-5) and Instituto Todos pela Saúde (C1721).

¿Existe correlación metabólica hipoglucémica y el síndrome de Percheron? Reporte de caso

Introducción: El síndrome de Percheron es causa de lesiones isquémicas talamicas bilaterales ocasionando una serie de anomalías clínicas como: alteración del estado de conciencia, oftalmoplejias, y alteraciones de la memoria. Caso clínico: Presentamos el caso de una mujer de 49 años con diabetes mellitus, mal control metabólico, episodios hipoglucémicos e hiperglucemicos repetitivos, quien cursa con sintomatologia inespecífica, se realizan estudios imagenológicos no invasivos documentado lesiones talamica bilaterales. Conclusiones: Los cuadros subagudos e isquémicos parciales que involucran la región paramediana del Talamo bilateral podrían tener alguna relación con episodios hipoglucémicos e hiperglucemicos repetitivos, que pueden llegar a cursar con sintomatología leve e inespecífica, lo cual lo convierte un reto diagnóstico para este síndrome.

Introduction: Percheron syndrome is the cause of bilateral thalamic ischemic lesions, causing a series of clinical abnormalities such as an altered state of consciousness, ophthalmoplegia, and memory alterations. Clinical case: We present the case of 49-year-old woman with diabetes mellitus, poor metabolic control, and repetitive hypoglycemic and hyperglycemic episodes with nonspecific symptoms, non-invasive imaging studies were performed, which documented bilateral thalamic lesions. Conclusions: Subacute and partial ischemic symptoms that involve the paramedian region of the bilateral thalamus could have some relationship with repetitive hypoglycemic and hyperglycemic episodes, and can lead to mild and nonspecific symptoms, which makes it a diagnostic challenge for this syndrome.

Telemedicine in Brazil: Teleconsultations at the Largest University Hospital in the Country.

The coronavirus disease (COVID-19) pandemic leveraged telemedicine worldwide mainly due to the need for social distancing, patient safety, and infection prevention. The Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP) was a key reference site in the treatment of COVID-19 severe cases in the country. To continue patient's health care, it became necessary to increase the number of teleconsultations and standardize it institutionally. Herein, we briefly described how the HCFMUSP improved the teleconsultation health care service during the COVID-19 pandemic, highlighting the implementation of important innovations and the throughout standardization process, including patients and professional workflow. We also detailed the methodology used to implement or improve teleconsultation in a medical/multidisciplinary specialty at HCFMUSP. All these efforts made the HCFMUSP reach the goal of converting 15% of all face-to-face consultations into teleconsultations only in 2021. In addition, there were more than 370,000 teleconsultations until the end of 2022. Our experience has shown that having a supporting team, a digital certification process, and the data integration were key factors toward the successful implementation of the teleconsultation services. We believe that progressing toward teleconsultation will improve the population covered by health care services in Brazil, as well as contribute to a reduction of waiting time, and solving costs to health care institutions and patients. We expect this report of our experience in teleconsultation implementation could inspire and guide other health care institutions in the development of telemedicine.

Long-term respiratory follow-up of ICU hospitalized COVID-19 patients: Prospective cohort study.

BACKGROUND: Coronavirus disease (COVID-19) survivors exhibit multisystemic alterations after hospitalization. Little is known about long-term imaging and pulmonary function of hospitalized patients intensive care unit (ICU) who survive COVID-19. We aimed to investigate long-term consequences of COVID-19 on the respiratory system of patients discharged from hospital ICU and identify risk factors associated with chest computed tomography (CT) lesion severity. METHODS: A prospective cohort study of COVID-19 patients admitted to a tertiary hospital ICU in Brazil (March-August/2020), and followed-up six-twelve months after hospital admission. Initial assessment included: modified Medical Research Council dyspnea scale, SpO2 evaluation, forced vital capacity, and chest X-Ray. Patients with alterations in at least one of these examinations were eligible for CT and pulmonary function tests (PFTs) approximately 16 months after hospital admission. Primary outcome: CT lesion severity (fibrotic-like or non-fibrotic-like). Baseline clinical variables were used to build a machine learning model (ML) to predict the severity of CT lesion. RESULTS: In total, 326 patients (72%) were eligible for CT and PFTs. COVID-19 CT lesions were identified in 81.8% of patients, and half of them showed mild restrictive lung impairment and impaired lung diffusion capacity. Patients with COVID-19 CT findings were stratified into two categories of lesion severity: non-fibrotic-like (50.8%-ground-glass opacities/reticulations) and fibrotic-like (49.2%-traction bronchiectasis/architectural distortion). No association between CT feature severity and altered lung diffusion or functional restrictive/obstructive patterns was found. The ML detected that male sex, ICU and invasive mechanic ventilation (IMV) period, tracheostomy and vasoactive drug need during hospitalization were predictors of CT lesion severity(sensitivity,0.78±0.02;specificity,0.79±0.01;F1-score,0.78±0.02;positive predictive rate,0.78±0.02; accuracy,0.78±0.02; and area under the curve,0.83±0.01). CONCLUSION: ICU hospitalization due to COVID-19 led to respiratory system alterations six-twelve months after hospital admission. Male sex and critical disease acute phase, characterized by a longer ICU and IMV period, and need for tracheostomy and vasoactive drugs, were risk factors for severe CT lesions six-twelve months after hospital admission.

Wearable potentiometric biosensor for analysis of urea in sweat.

Herein, we introduce wearable potentiometric biosensors on screen-printed carbon electrodes (SPCEs) for on-body and on-site monitoring of urea in sweat. The biosensor architecture was judiciously designed to detect urea at different pHs and incorporate a pH sensor, thus containing polyaniline ink, urease bioink and a polyvinylchloride membrane. Urea detection could be performed in the wide range from 5 to 200 mM at pH 7.0, encompassing urea levels in human sweat. The biosensor response was fast (incubation time 5 min), with no interference from other substances in sweat. Reliable urea detection could be done in undiluted human sweat with a skin-worn flexible device using the pH correction strategy afforded by the pH sensor. The performance of the epidermal biosensor was not affected by severe bending strains. The feasibility of mass production was demonstrated by fabricating epidermal flexible biosensors using slot-die coating with a roll-to-roll technique.

Contrast phase recognition in liver computer tomography using deep learning.

Hepatocellular carcinoma (HCC) has become the 4th leading cause of cancer-related deaths, with high social, economical and health implications. Imaging techniques such as multiphase computed tomography (CT) have been successfully used for diagnosis of liver tumors such as HCC in a feasible and accurate way and its interpretation relies mainly on comparing the appearance of the lesions in the different contrast phases of the exam. Recently, some researchers have been dedicated to the development of tools based on machine learning (ML) algorithms, especially by deep learning techniques, to improve the diagnosis of liver lesions in imaging exams. However, the lack of standardization in the naming of the CT contrast phases in the DICOM metadata is a problem for real-life deployment of machine learning tools. Therefore, it is important to correctly identify the exam phase based only on the image and not on the exam metadata, which is unreliable. Motivated by this problem, we successfully created an annotation platform and implemented a convolutional neural network (CNN) to automatically identify the CT scan phases in the HCFMUSP database in the city of São Paulo, Brazil. We improved this algorithm with hyperparameter tuning and evaluated it with cross validation methods. Comparing its predictions with the radiologists annotation, it achieved an accuracy of 94.6%, 98% and 100% in the testing dataset for the slice, volume and exam evaluation, respectively.

Chronic lung lesions in COVID-19 survivors: predictive clinical model.

OBJECTIVE: This study aimed to propose a simple, accessible and low-cost predictive clinical model to detect lung lesions due to COVID-19 infection. DESIGN: This prospective cohort study included COVID-19 survivors hospitalised between 30 March 2020 and 31 August 2020 followed-up 6 months after hospital discharge. The pulmonary function was assessed using the modified Medical Research Council (mMRC) dyspnoea scale, oximetry (SpO2), spirometry (forced vital capacity (FVC)) and chest X-ray (CXR) during an in-person consultation. Patients with abnormalities in at least one of these parameters underwent chest CT. mMRC scale, SpO2, FVC and CXR findings were used to build a machine learning model for lung lesion detection on CT. SETTING: A tertiary hospital in Sao Paulo, Brazil. PARTICIPANTS: 749 eligible RT-PCR-confirmed SARS-CoV-2-infected patients aged ≥18 years. PRIMARY OUTCOME MEASURE: A predictive clinical model for lung lesion detection on chest CT. RESULTS: There were 470 patients (63%) that had at least one sign of pulmonary involvement and were eligible for CT. Almost half of them (48%) had significant pulmonary abnormalities, including ground-glass opacities, parenchymal bands, reticulation, traction bronchiectasis and architectural distortion. The machine learning model, including the results of 257 patients with complete data on mMRC, SpO2, FVC, CXR and CT, accurately detected pulmonary lesions by the joint data of CXR, mMRC scale, SpO2 and FVC (sensitivity, 0.85±0.08; specificity, 0.70±0.06; F1-score, 0.79±0.06 and area under the curve, 0.80±0.07). CONCLUSION: A predictive clinical model based on CXR, mMRC, oximetry and spirometry data can accurately screen patients with lung lesions after SARS-CoV-2 infection. Given that these examinations are highly accessible and low cost, this protocol can be automated and implemented in different countries for early detection of COVID-19 sequelae.

Implementation of Tele-ICU during the COVID-19 pandemic.

OBJECTIVE: To describe the implementation of a Tele-ICU program during the COVID-19 pandemic, as well as to describe and analyze the results of the first four months of operation of the program. METHODS: This was a descriptive observational study of the implementation of a Tele-ICU program, followed by a retrospective analysis of clinical data of patients with COVID-19 admitted to ICUs between April and July of 2020. RESULTS: The Tele-ICU program was implemented over a four-week period and proved to be feasible during the pandemic. Participants were trained remotely, and the program had an evidence-based design, the objective being to standardize care for patients with COVID-19. More than 100,000 views were recorded on the free online platforms and the mobile application. During the study period, the cases of 326 patients with COVID-19 were evaluated through the program. The median age was 60 years (IQR, 49-68 years). There was a predominance of males (56%). There was also a high prevalence of hypertension (49.1%) and diabetes mellitus (38.4%). At ICU admission, 83.7% of patients were on invasive mechanical ventilation, with a median PaO2/FiO2 ratio < 150. It was possible to use lung-protective ventilation in 75% of the patients. Overall, in-hospital mortality was 68%, and ICU mortality was 65%. CONCLUSIONS: Our Tele-ICU program provided multidisciplinary training to health care professionals and clinical follow-up for hundreds of critically ill patients. This public health care network initiative was unprecedented and proved to be feasible during the COVID-19 pandemic, encouraging the creation of similar projects that combine evidence-based practices, training, and Tele-ICU.

Novel Chest Radiographic Biomarkers for COVID-19 Using Radiomic Features Associated with Diagnostics and Outcomes.

COVID-19 is a highly contagious disease that can cause severe pneumonia. Patients with pneumonia undergo chest X-rays (XR) to assess infiltrates that identify the infection. However, the radiographic characteristics of COVID-19 are similar to the other acute respiratory syndromes, hindering the imaging diagnosis. In this work, we proposed identifying quantitative/radiomic biomarkers for COVID-19 to support XR assessment of acute respiratory diseases. This retrospective study used different cohorts of 227 patients diagnosed with pneumonia; 49 of them had COVID-19. Automatically segmented images were characterized by 558 quantitative features, including gray-level histogram and matrices of co-occurrence, run-length, size zone, dependence, and neighboring gray-tone difference. Higher-order features were also calculated after applying square and wavelet transforms. Mann-Whitney U test assessed the diagnostic performance of the features, and the log-rank test assessed the prognostic value to predict Kaplan-Meier curves of overall and deterioration-free survival. Statistical analysis identified 51 independently validated radiomic features associated with COVID-19. Most of them were wavelet-transformed features; the highest performance was the small dependence matrix feature of "low gray-level emphasis" (area under the curve of 0.87, sensitivity of 0.85, [Formula: see text]). Six features presented short-term prognostic value to predict overall and deterioration-free survival. The features of histogram "mean absolute deviation" and size zone matrix "non-uniformity" yielded the highest differences on Kaplan-Meier curves with a hazard ratio of 3.20 ([Formula: see text]). The radiomic markers showed potential as quantitative measures correlated with the etiologic agent of acute infectious diseases and to stratify short-term risk of COVID-19 patients.

Clinical evaluation of left ventricular function and morphology using an accelerated k-t sensitivity encoding method in cardiovascular magnetic resonance.

OBJECTIVES: To provide clinical validation of a recent 2D SENSE-based accelerated cardiovascular magnetic resonance (CMR) sequence (accelerated k-t SENSE), investigating whether this technique accurately quantifies left ventricle (LV) volumes, function, and mass as compared to 2D cine steady-state free precession (2D-SSFP). METHODS: Healthy volunteers (n = 16) and consecutive heart failure patients (n = 26) were scanned using a 1.5 T MRI system. Two LV short axis (SA) stacks were acquired: (1) accelerated k-t SENSE (5-6 breath-holds; temporal/spatial resolution: 37 ms/1.82 × 1.87 mm; acceleration factor = 4) and (2) standard 2D-SSFP (10-12 breath-holds; temporal/spatial resolution: 49 ms/1.67 × 1.87 mm, parallel imaging). Ascending aorta phase-contrast was performed on all volunteers as a reference to compare LV stroke volumes (LVSV) and validate the sequences. An image quality score for SA images was used, with lower scores indicating better quality (from 0 to 18). RESULTS: There was a high agreement between accelerated k-t SENSE and 2D-SSFP for LV measurements: bias (limits of agreement) of 2.4% (- 5.4% to 10.1%), 6.9 mL/m2 (- 4.7 to 18.6 mL/m2), - 1.5 (- 8.3 to 5.2 mL/m2), and - 0.2 g/m2 (- 11.9 to 12.3 g/m2) for LV ejection fraction, end-diastolic volume index, end-systolic volume index, and mass index, respectively. LVSV by accelerated k-t SENSE presented good agreement with aortic flow. Interobserver and intraobserver variabilities for all LV parameters were also high. CONCLUSION: The accelerated k-t SENSE CMR sequence is clinically feasible and accurately quantifies LV volumes, function, and mass, with short acquisition time and good image quality.

Innate Lymphoid Cells Have Decreased HLA-DR Expression but Retain Their Responsiveness to TLR Ligands during Sepsis.

Sepsis, one of the leading causes of death in intensive care units, is caused by a dysregulated host response to infection that leads to life-threatening organ dysfunction. The proinflammatory and anti-inflammatory responses activated by the infecting microorganism become systemic, and the sustained anti-inflammatory response induces a state of immunosuppression that is characterized by decreased expression of HLA-DR on monocytes, T cell apoptosis, and reduced production of TNF-α by monocytes and macrophages in response to TLR ligands. Innate lymphoid cells (ILCs) are lymphocytes that lack Ag-specific receptors and lineage-specific markers; they express HLA-DR and are activated by cytokines and by direct recognition of microbial molecules. In this study, we evaluated if ILCs are affected by the anti-inflammatory response during sepsis. We found that the number of peripheral blood ILCs was decreased in septic patients compared with healthy volunteers; this decrease was caused by a reduction in ILC1 and ILC3 and is associated with apoptosis, because ILCs from septic patients expressed active caspase 3. ILCs from septic patients had decreased HLA-DR expression but increased expression of the activating receptors NKp46 and NKp44; they also showed a sustained expression of CD127 (IL-7R α-chain) and retained their capacity to produce TNF-α in response to TLR ligands. These results indicate that during sepsis, ILCs have decreased HLA-DR expression and die via apoptosis, similar to monocytes and T cells, respectively. However, other effector functions of ILCs (activation through NKp46 and NKp44, TNF-α production) may remain unaffected by the immunosuppressive environment prevailing in septic patients.

Cerebral blood flow changes during intermittent acute hypoxia in patients with heart failure.

Objective Heart failure (HF) is associated with intermittent hypoxia, and the effects of this hypoxia on the cardiovascular system are not well understood. This study was performed to compare the effects of acute hypoxia (10% oxygen) between patients with and without HF. Methods Fourteen patients with chronic HF and 17 matched control subjects were enrolled. Carotid artery changes were examined during the first period of hypoxia, and brachial artery changes were examined during the second period of hypoxia. Data were collected at baseline and after 2 and 4 minutes of hypoxia. Norepinephrine, epinephrine, dopamine, and renin were measured at baseline and after 4 minutes hypoxia. Results The carotid blood flow, carotid systolic diameter, and carotid diastolic diameter increased and the carotid resistance decreased in patients with HF. Hypoxia did not change the carotid compliance, distensibility, brachial artery blood flow and diameter, or concentrations of sympathomimetic amines in patients with HF, but hypoxia increased the norepinephrine level in the control group. Hypoxia increased minute ventilation and decreased the oxygen saturation and end-tidal carbon dioxide concentration in both groups. Conclusion Hypoxia-induced changes in the carotid artery suggest an intensification of compensatory mechanisms for preservation of cerebral blood flow in patients with HF.

A method for cohort selection of cardiovascular disease records from an electronic health record system.

INTRODUCTION: An electronic healthcare record (EHR) system, when used by healthcare providers, improves the quality of care for patients and helps to lower costs. Information collected from manual or electronic health records can also be used for purposes not directly related to patient care delivery, in which case it is termed secondary use. EHR systems facilitate the collection of this secondary use data, which can be used for research purposes like observational studies, taking advantage of improvement in the structuring and retrieval of patient information. However, some of the following problems are common when conducting a research using this kind of data: (i) Over time, systems and data storage methods become obsolete; (ii) Data concerns arise since the data is being used in a context removed from its original intention; (iii) There are privacy concerns when sharing data about individual subjects; (iv) The partial availability of standard medical vocabularies and natural language processing tools for non-English language limits information extraction from structured and unstructured data in the EHR systems. A systematic approach is therefore needed to overcome these, where local data processing is performed prior to data sharing. METHOD: The proposed study describes a local processing method to extract cohorts of patients for observational studies in four steps: (1) data reorganization from an existing local logical schema into a common external schema over which information can be extracted; (2) cleaning of data, generation of the database profile and retrieval of indicators; (3) computation of derived variables from original variables; (4) application of study design parameters to transform longitudinal data into anonymized data sets ready for statistical analysis and sharing. Mapping from the local logical schema into a common external schema must be performed differently for each EHR and is not subject of this work, but step 2, 3 and 4 are common to all EHRs. The external schema accepts parameters that facilitate the extraction of different cohorts for different studies without having to change the extraction algorithms, and ensures that, given an immutable data set, can be done by the idempotent process. Statistical analysis is part of the process to generate the results necessary for inclusion in reports. The generation of indicators to describe the database allows description of its characteristics, highlighting study results. The set extraction/statistical processing is available in a version controlled repository and can be used at any time to reproduce results, allowing the verification of alterations and error corrections. This methodology promotes the development of reproducible studies and allows potential research problems to be tracked upon extraction algorithms and statistical methods RESULTS: This method was applied to an admissions database, SI3, from the InCor-HCFMUSP, a tertiary referral hospital for cardiovascular disease in the city of São Paulo, as a source of secondary data with 1116848 patients records from 1999 up to 2013. The cleaning process resulted in 313894 patients records and 27698 patients in the cohort selection, with the following criteria: study period: 2003-2013, gender: Male, Female, age:≥18years old, at least 2 outpatient encounters, diagnosis of cardiovascular disease (ICD-10 codes: I20-I25, I64-I70 and G45). An R script provided descriptive statistics of the extracted cohort. CONCLUSION: This method guarantees a reproducible cohort extraction for use of secondary data in observational studies with enough parameterization to support different study designs and can be used on diverse data sources. Moreover it allows observational electronic health record cohort research to be performed in a non-English language with limited international recognized medical vocabulary.

Healthcare-associated infections: Appropriate empirical antibiotic treatment / Infecciones asociadas a la atención de la salud: tratamiento antibiótico empírico apropiado

Background: Health-care Associated Infections (HAI) are one of the main causes of death in critically ill patients. The aim of this paper is to establish an appropriate empirical antibiotic treatment for the main HAI in an Intensive Care Unit (ICU). Methods: A retrospective, observational, descriptive and analytical study of the culture results from January, 2014 to December, 2015. The causative microorganisms were identified, as well as sensitivity and antibiotic resistance. Results: Of the three main HAI in the ICU were Ventilator Associated Pneumonia (VAP), whose most common germs were methicillin-resistant Staphylococcus aureus, Acinetobacter baumannii, Pseudomonas aeruginosa; Urinary Tract Infection Associated with Urinary Catheter (IVU-CU), Escherichia coli BLEE and Pseudomonas aeruginosa were isolated in 70%, and 56% of the bloodstream infections of the germs that caused this infection were three, the most frequent being Escherichia coli, followed by Klebsiella oxytoca and methicillin-resistant Staphylococcus aureus. Conclusions: VAP was the most frequent HAI and resistant methicillin Staphylococcus aureus was the most prevalent in this type of infection. The proposed empiric antibiotic treatment was as follows: VAP (vancomycin plus amikacin plus meropenem), IVU-CU (meropenem) and STIs (vancomycin plus cefepime).

Introducción: Las infecciones asociadas a la atención de la salud (IAAS) son una de las principales causas de muerte en pacientes en estado crítico. El objetivo de este trabajo fue identificar los gérmenes más frecuentemente asociados a las IAAS en la Unidad de Cuidados Intensivos (UCI) y determinar el tratamiento antibiótico empírico apropiado. Métodos: Estudio retrospectivo, observacional, descriptivo y analítico de los cultivos de enero de 2014 a diciembre de 2015. Se identificaron los microorganismos causantes de las IAAS, la sensibilidad y la resistencia antibiótica. Resultados: Las tres principales IAAS en la UCI fueron: la neumonía asociada a ventilador (NAV), y los gérmenes más habituales fueron Staphylococcus aureus meticilino resistente, Acinetobacter baumannii y Pseudomonas aeruginosa; la infección de vías urinarias asociada a catéter urinario (IVUCU) la Escherichia coli BLEE y Pseudomonas aeruginosa fueron aisladas en el 70% y en las infecciones del torrente sanguíneo (ITS) el 56% de los gérmenes fueron Escherichia coli, Klebsiella oxytoca y Staphylococcus aureus meticilino resistente. Conclusiones: La NAV fue la IAAS más frecuente y el Staphylococcus aureus meticilino resistente fue el más prevalente en este tipo de infección. La propuesta de tratamiento antibiótico empírico es: para NAV (vancomicina más amikacina más meropenem), IVU-CU (meropenem) y las ITS (vancomicina más cefepime).

Patellar tracking after isolated medial patellofemoral ligament reconstruction: dynamic evaluation using computed tomography.

PURPOSE: Medial patellofemoral ligament (MPFL) reconstruction offers good clinical results with a very low rate of instability recurrence. However, its in vivo effect on patellar tracking is not clearly known. The aim of this study is to investigate the effects of MPFL reconstruction on patellar tracking using dynamic 320-detector-row CT. METHODS: Ten patients with patellofemoral instability referred to isolated MPFL reconstruction surgery were selected and subjected to dynamic CT before and ≥6 months after surgery. Patellar tilt angles and shift distance were analysed using computer software specifically designed for this purpose. Kujala and Tegner scores were applied, and the radiation of the CTs was recorded. Two protocols for imaging acquisition were compared: a tube potential of 80 kV and 50 mA versus a tube potential of 120 kV and 100 mA, both with a slice thickness of 0.5 mm and an acquisition duration of 10 s. RESULTS: There were no changes in patellar tracking after MPFL reconstruction. There was no instability relapse. Clinical scores improved from a mean of 51.9 (±15.6)-74.2 (±20.9) on the Kujala scale (p = 0.011) and from a median of 2 (range 0-4) to 4 (range 1-6) on the Tegner scale (p = 0.017). The imaging protocols produced a dose-length product (DLP) of 254 versus 1617 mGycm and a radiation effective estimated dose of 0.2 versus 1.3 mSv, respectively. Both protocols allowed the analysis of the studied parameters without loss of precision. CONCLUSIONS: Reconstruction of the MPFL produced no improvement in patellar tilt or shift in the population studied. The low-radiation protocol was equally effective in measuring changes in patellar tracking and is recommended. Although the procedure successfully stabilized the patella, knee surgeons should not expect patellar shift and tilt correction when performing isolated patellofemoral ligament reconstruction in patients with recurrent patellar instability. LEVEL OF EVIDENCE: IV.