Publications by authors named "Praneeth Sadda"

9 Publications

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Increases in female academic productivity and female mentorship highlight sustained progress in previously identified neurosurgical gender disparities.

Neurosurg Focus 2021 03;50(3):E3

3Department of Neurological Surgery, NewYork-Presbyterian Hospital, Weill Cornell Medical College; and.

Objective: A meta-analysis was performed to understand disparities in the representation of female authorship within the neurosurgical literature and implications for career advancement of women in neurosurgery.

Methods: Author names for articles published in 16 of the top neurosurgical journals from 2002 to 2019 were obtained from MEDLINE. The gender of each author was determined using automated prediction methods. Publication trends were compared over time and across subdisciplines. Female authorship was also compared to the proportionate composition of women in the field over time.

Results: The metadata obtained from 16 major neurosurgical journals yielded 66,546 research articles. Gender was successfully determined for 96% (127,809/133,578) of first and senior authors, while the remainder (3.9%) were unable to be determined through prediction methods. Across all years, 13.3% (8826) of articles had female first authorship and 9.1% (6073) had female senior authorship. Female first authorship increased significantly over time from 5.8% in 2002 to 17.2% in 2019 (p < 0.001). Female senior authorship also increased significantly over time, from 5.5% in 2002 to 12.0% in 2019 (p < 0.001). The journals with the highest proportions of female first authors and senior authors were the Journal of Neurosurgery: Pediatrics (33.5%) and the Asian Journal of Neurosurgery (23.8%), respectively. Operative Neurosurgery had the lowest fraction of female first (12.4%) and senior (4.7%) authors. There was a significant difference between the year-by-year proportion of female neurosurgical trainees and the year-by-year proportion of female neurosurgical first (p < 0.001) and senior (p < 0.001) authors. Articles were also more likely to have a female first author if the senior author of the article was female (OR 2.69, CI 2.52-2.86; p < 0.001). From 1944 to 2019, the Journal of Neurosurgery showed a steady increase in female first and senior authorship, with a plateau beginning in the 1990s.

Conclusions: Large meta-analysis techniques have the potential to effectively leverage large amounts of bibliometric data to quantify the representation of female authorship in the neurosurgical literature. The proportion of female authors in major neurosurgical journals has steadily increased. However, the rate of increase in female senior authorship has lagged behind the rate of increase in first authorship, indicating a disparity in academic advancement in women in neurosurgery.
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http://dx.doi.org/10.3171/2020.12.FOCUS20939DOI Listing
March 2021

Price transparency implementation: Accessibility of hospital chargemasters and variation in hospital pricing after CMS mandate.

Healthc (Amst) 2020 Sep 4;8(3):100443. Epub 2020 Jul 4.

Yale School of Medicine, New Haven, CT, USA.

Background: National regulations have increasingly focused on transparency in hospital billing and pricing practices. A January 2019 federal mandate required hospitals to publicize lists of billable procedures and items known as chargemasters.

Methods: We identified the 500 top self-pay/uninsured revenue grossing hospitals nationally and searched each hospital's website for a chargemaster. Corresponding items were matched across chargemasters. Intrahospital and interhospital price variation were calculated. To investigate variation in item naming, a name variant and fuzzy matching search was conducted for fifteen common chargemaster items.

Results: Of 500 hospitals in this study, 69 (13.8%) had chargemasters that were inaccessible and 30 (6.0%) had chargemasters that did not meet mandated requirements. Among the remaining 431 hospitals, the mean interhospital and intrahospital variation in pricing for identical items was 18% (SD 28%) and 28% (SD 29%), respectively. 388 hospitals listed multiple prices for the same item, with a mean of 687.3 duplicated items (SD 1157.7). Among fifteen common chargemaster items, each item was associated with an average of 275 (SD 213) unique name variants. Interhospital price variation of these items ranged from 53% (transthoracic echocardiogram) to 243% (furosemide 40 mg).

Conclusions: Many chargemasters have barriers to access, and item naming is inconsistent across chargemasters. There is significant interhospital price variation for similar items.

Implications: Chargemasters are uninterpretable for the purpose of patient price comparison in their current form. Further regulatory efforts are necessary to increase price transparency and enhance the ability of patients to compare hospital prices.
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http://dx.doi.org/10.1016/j.hjdsi.2020.100443DOI Listing
September 2020

Synthesis of fracture radiographs with deep neural networks.

Health Inf Sci Syst 2020 Dec 30;8(1):21. Epub 2020 May 30.

Department of Emergency Medicine, Yale School of Medicine, New Haven, CT USA.

Purpose: We describe a machine learning system for converting diagrams of fractures into realistic X-ray images. We further present a method for iterative, human-guided refinement of the generated images and show that the resulting synthetic images can be used during training to increase the accuracy of deep classifiers on clinically meaningful subsets of fracture X-rays.

Methods: A neural network was trained to reconstruct images from programmatically created line drawings of those images. The images were then further refined with an optimization-based technique. Ten physicians were recruited into a study to assess the realism of synthetic radiographs created by the neural network. They were presented with mixed sets of real and synthetic images and asked to identify which images were synthetic. Two classifiers were trained to detect humeral shaft fractures: one only on true fracture images, and one on both true and synthetic images.

Results: Physicians were 49.63% accurate in identifying whether images were synthetic or real. This is close to what would be expected by pure chance (i.e. random guessing). A classifier trained only on real images detected fractures with 67.21% sensitivity when no fracture fixation hardware was present. A classifier trained on both real images and synthetic images was 75.54% sensitive.

Conclusion: Our method generates X-rays realistic enough to be indistinguishable from real X-rays. We also show that synthetic images generated using this method can be used to increase the accuracy of deep classifiers on clinically meaningful subsets of fracture X-rays.
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http://dx.doi.org/10.1007/s13755-020-00111-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7261299PMC
December 2020

Real-time computerized video enhancement for minimally invasive fetoscopic surgery.

Laparosc Endosc Robot Surg 2018 Sep 22;1(2):27-32. Epub 2018 Jun 22.

Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06510, USA.

Background: The only definitive treatment for twin-to-twin transfusion syndrome is minimally invasive fetoscopic surgery for the selective coagulation of placental blood vessels. Fetoscopic surgery is a technically challenging operation, mainly due to the poor visibility conditions in the uterine environment. We present the design of an algorithm for the computerized enhancement of fetoscopic video and show that the enhanced video increases the ability of human users to identify blood vessels within fetoscopic video rapidly and accurately.

Methods: A computer algorithm for the enhancement of fetoscopic video frames was created. First, optical fiber artifacts were removed via a modification of unsharp masking. Second, image contrast was increased via Contrast Limited Adaptive Histogram Equalization (CLAHE). Third, the effect of contrast enhancements on stationary features was removed by normalizing to a windowed mean of the video frames. Fourth, color information was reincorporated by combining the mean-normalized result with the unnormalized contrast enhanced image using the soft light blending algorithm. Medical trainees ( = 16) were recruited into a study to validate the algorithm. Subjects were shown enhanced or unenhanced fetoscopic video frames on a screen and were asked to identify whether a randomly placed marker fell on a blood vessel or on background. The accuracy of their responses was recorded.

Results: On the subset of images where subjects had the lowest mean accuracy in identifying the placement of the marker, subjects performed better when viewing video frames enhanced by the computer (accuracy 74.27%; SE 0.97) than when viewing unenhanced video frames (accuracy 63.78%; SE 2.79). This result was statistically significant ( < 0.01).

Conclusion: Real-time computerized enhancement of fetoscopic video has the potential to ease the readability of video in poor lighting conditions, thus providing a benefit to the surgeon intraoperatively.
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http://dx.doi.org/10.1016/j.lers.2018.06.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6508886PMC
September 2018

Deep-learned placental vessel segmentation for intraoperative video enhancement in fetoscopic surgery.

Int J Comput Assist Radiol Surg 2019 Feb 27;14(2):227-235. Epub 2018 Nov 27.

Yale University School of Medicine, New Haven, USA.

Introduction: Twin-to-twin transfusion syndrome (TTTS) is a potentially lethal condition that affects pregnancies in which twins share a single placenta. The definitive treatment for TTTS is fetoscopic laser photocoagulation, a procedure in which placental blood vessels are selectively cauterized. Challenges in this procedure include difficulty in quickly identifying placental blood vessels due to the many artifacts in the endoscopic video that the surgeon uses for navigation. We propose using deep-learned segmentations of blood vessels to create masks that can be recombined with the original fetoscopic video frame in such a way that the location of placental blood vessels is discernable at a glance.

Methods: In a process approved by an institutional review board, intraoperative videos were acquired from ten fetoscopic laser photocoagulation surgeries performed at Yale New Haven Hospital. A total of 345 video frames were selected from these videos at regularly spaced time intervals. The video frames were segmented once by an expert human rater (a clinician) and once by a novice, but trained human rater (an undergraduate student). The segmentations were used to train a fully convolutional neural network of 25 layers.

Results: The neural network was able to produce segmentations with a high similarity to ground truth segmentations produced by an expert human rater (sensitivity = 92.15% ± 10.69%) and produced segmentations that were significantly more accurate than those produced by a novice human rater (sensitivity = 56.87% ± 21.64%; p < 0.01).

Conclusion: A convolutional neural network can be trained to segment placental blood vessels with near-human accuracy and can exceed the accuracy of novice human raters. Recombining these segmentations with the original fetoscopic video frames can produced enhanced frames in which blood vessels are easily detectable. This has significant implications for aiding fetoscopic surgeons-especially trainees who are not yet at an expert level.
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http://dx.doi.org/10.1007/s11548-018-1886-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6438174PMC
February 2019

Real-Time Medical Video Denoising with Deep Learning: Application to Angiography.

Int J Appl Inf Syst 2018 May;12(13):22-28

Yale University, School of Medicine, Cedar St, New Haven, CT, USA.

This paper describes the design, training, and evaluation of a deep neural network for removing noise from medical fluoroscopy videos. The method described in this work, unlike the current standard techniques for video denoising, is able to deliver a result quickly enough to be used in real-time scenarios. Furthermore, this method is able to produce results of a similar quality to the existing industry-standard denoising techniques.
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http://dx.doi.org/10.5120/ijais2018451755DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5985814PMC
May 2018

A cluster randomized trial to determine the effectiveness of a novel, digital pendant and voice reminder platform on increasing infant immunization adherence in rural Udaipur, India.

Vaccine 2018 10 20;36(44):6567-6577. Epub 2017 Nov 20.

India Institute of Health Management Research, 1, Prabhudayal Marg, Near Sanganer Airport, Jaipur, Rajasthan 302029, India.

Background: Five hundred thousand children under the age of 5 die from vaccine preventable diseases in India every year. More than just improving coverage, increasing timeliness of immunizations is critical to ensuring infant health in the first year of life. Novel, culturally appropriate community engagement strategies are worth exploring to close the immunization gap. In our study, a digital NFC (Near Field Communication) pendant worn on black thread and voice call reminder system was tested for the effectiveness in improving DTP3 adherence within 2 monthly camps from DTP1 administration.

Method: A cluster randomized controlled trial was conducted in which 96 village health camps were randomized to 3 arms: NFC sticker, NFC pendant, and NFC pendant with voice call reminder in local dialect. Randomization was done across 5 blocks in the Udaipur District serviced by Seva Mandir from August 2015 to April 2016.

Results: In terms of our three primary outcomes related to DTP3 adherence, point estimates show conflicting results. Two outcomes presented adherence in the control. DTP3 completion within two camps after DTP1 showed higher adherence in the Control (Sticker) (74.2%) arm compared to the Pendant (67.2%) and Pendant and Voice arms (69.3%). Likewise, the estimate for DTP3 completion within 180 days of birth in the Control (Sticker) (69.4%) arm was higher than estimates in the Pendant (57.4%) and Pendant and Voice arms (58.7%). However, one outcome displayed higher adherence in the intervention. DTP3 completion within two months from the time of registration was higher in the Pendant (37.7%) and Pendant and Voice arms (38.7%) compared to the Control (Sticker) arm (27.4%). In all primary outcomes, differences in adherence were statistically insignificant both before and after controlling for confounding factors. In terms of secondary outcomes, our results suggest that providing a necklace generated significant community discussion (H = 8.8796, df = 2, p = .0118), had strong satisfaction among users (χ2=26.039, df = 4, p < .0001), and resulted in increased visibility within families (grandmothers:χ2=34.023, df = 2, p < .0001, fathers: χ2=34.588, df = 2, p < .0001).

Conclusion: Neither the NFC necklace nor the necklace with additional voice call reminders in the local dialect directly resulted in an increase in infant immunization timeliness through DTP3, the primary outcome. Still our process outcomes suggest that our culturally symbolic necklace has potential to be an assistive tool in immunization campaigns. Follow-on work will seek to examine whether positive behavior change towards vaccines can be fostered with earlier engagement of this platform beginning in the prenatal stage, under a continuum of care framework.
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http://dx.doi.org/10.1016/j.vaccine.2017.11.023DOI Listing
October 2018

Versatile genetic assembly system (VEGAS) to assemble pathways for expression in S. cerevisiae.

Nucleic Acids Res 2015 Jul 8;43(13):6620-30. Epub 2015 May 8.

Department of Biochemistry and Molecular Pharmacology, New York University Langone School of Medicine, New York City, NY 10016, USA Institute for Systems Genetics, New York University Langone School of Medicine, New York City, NY 10016, USA High Throughput Biology Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA

We have developed a method for assembling genetic pathways for expression in Saccharomyces cerevisiae. Our pathway assembly method, called VEGAS (Versatile genetic assembly system), exploits the native capacity of S. cerevisiae to perform homologous recombination and efficiently join sequences with terminal homology. In the VEGAS workflow, terminal homology between adjacent pathway genes and the assembly vector is encoded by 'VEGAS adapter' (VA) sequences, which are orthogonal in sequence with respect to the yeast genome. Prior to pathway assembly by VEGAS in S. cerevisiae, each gene is assigned an appropriate pair of VAs and assembled using a previously described technique called yeast Golden Gate (yGG). Here we describe the application of yGG specifically to building transcription units for VEGAS assembly as well as the VEGAS methodology. We demonstrate the assembly of four-, five- and six-gene pathways by VEGAS to generate S. cerevisiae cells synthesizing β-carotene and violacein. Moreover, we demonstrate the capacity of yGG coupled to VEGAS for combinatorial assembly.
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http://dx.doi.org/10.1093/nar/gkv466DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4513848PMC
July 2015

Surgical navigation with a head-mounted tracking system and display.

Stud Health Technol Inform 2013 ;184:363-9

Dept. of Computer Science, Johns Hopkins University, Baltimore, MD USA.

We present the design of a self-contained head-mounted surgical navigation system, which consists of an optical tracking system and an optical see-through head-mounted display (HMD). While the current prototype is bulky, we envision a more compact solution via the eventual integration of the tracking camera(s) into the HMD goggles. Rather than attempting to accurately overlay preoperative models onto the field of view, we adopted a simpler approach of displaying a small "picture-in-picture" virtual view in the HMD. We believe this approach will provide suitable assistance for some image-guided procedures, such as tumor resection, while improving the ergonomics by reducing the need for the surgeon to look away from the patient to view an external monitor. We report the results of initial experiments performed with this system, while preparing for a more clinically realistic study.
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July 2013