12 research outputs found

    Classifying complications: Assessing adult spinal deformity 2-year surgical outcomes

    Get PDF
    STUDY DESIGN: Retrospective review of prospective database. OBJECTIVE: Complication rates for adult spinal deformity (ASD) surgery vary widely because there is no accepted system for categorization. Our objective was to identify the impact of complication occurrence, minor-major complication, and Clavien-Dindo complication classification (Cc) on clinical variables and patient-reported outcomes. METHODS: Complications in surgical ASD patients with complete baseline and 2-year data were considered intraoperatively, perioperatively (\u3c6 weeks), and postoperatively (\u3e6 weeks). Primary outcome measures were complication timing and severity according to 3 scales: complication presence (yes/no), minor-major, and Cc score. Secondary outcomes were surgical outcomes (estimated blood loss [EBL], length of stay [LOS], reoperation) and health-related quality of life (HRQL) scores. Univariate analyses determined complication presence, type, and Cc grade impact on operative variables and on HRQL scores. RESULTS: Of 167 patients, 30.5% (n = 51) had intraoperative, 48.5% (n = 81) had perioperative, and 58.7% (n = 98) had postoperative complications. Major intraoperative complications were associated with increased EBL ( CONCLUSION: The Cc Scale was most useful in predicting changes in patient outcomes; at 2 years, patients with raised perioperative Cc scores and postoperative complications saw reduced HRQL improvement. Intraoperative and perioperative complications were associated with worse short-term surgical and inpatient outcomes

    Neurodevelopmental disorders in children aged 2-9 years: Population-based burden estimates across five regions in India.

    Get PDF
    BACKGROUND: Neurodevelopmental disorders (NDDs) compromise the development and attainment of full social and economic potential at individual, family, community, and country levels. Paucity of data on NDDs slows down policy and programmatic action in most developing countries despite perceived high burden. METHODS AND FINDINGS: We assessed 3,964 children (with almost equal number of boys and girls distributed in 2-<6 and 6-9 year age categories) identified from five geographically diverse populations in India using cluster sampling technique (probability proportionate to population size). These were from the North-Central, i.e., Palwal (N = 998; all rural, 16.4% non-Hindu, 25.3% from scheduled caste/tribe [SC-ST] [these are considered underserved communities who are eligible for affirmative action]); North, i.e., Kangra (N = 997; 91.6% rural, 3.7% non-Hindu, 25.3% SC-ST); East, i.e., Dhenkanal (N = 981; 89.8% rural, 1.2% non-Hindu, 38.0% SC-ST); South, i.e., Hyderabad (N = 495; all urban, 25.7% non-Hindu, 27.3% SC-ST) and West, i.e., North Goa (N = 493; 68.0% rural, 11.4% non-Hindu, 18.5% SC-ST). All children were assessed for vision impairment (VI), epilepsy (Epi), neuromotor impairments including cerebral palsy (NMI-CP), hearing impairment (HI), speech and language disorders, autism spectrum disorders (ASDs), and intellectual disability (ID). Furthermore, 6-9-year-old children were also assessed for attention deficit hyperactivity disorder (ADHD) and learning disorders (LDs). We standardized sample characteristics as per Census of India 2011 to arrive at district level and all-sites-pooled estimates. Site-specific prevalence of any of seven NDDs in 2-<6 year olds ranged from 2.9% (95% CI 1.6-5.5) to 18.7% (95% CI 14.7-23.6), and for any of nine NDDs in the 6-9-year-old children, from 6.5% (95% CI 4.6-9.1) to 18.5% (95% CI 15.3-22.3). Two or more NDDs were present in 0.4% (95% CI 0.1-1.7) to 4.3% (95% CI 2.2-8.2) in the younger age category and 0.7% (95% CI 0.2-2.0) to 5.3% (95% CI 3.3-8.2) in the older age category. All-site-pooled estimates for NDDs were 9.2% (95% CI 7.5-11.2) and 13.6% (95% CI 11.3-16.2) in children of 2-<6 and 6-9 year age categories, respectively, without significant difference according to gender, rural/urban residence, or religion; almost one-fifth of these children had more than one NDD. The pooled estimates for prevalence increased by up to three percentage points when these were adjusted for national rates of stunting or low birth weight (LBW). HI, ID, speech and language disorders, Epi, and LDs were the common NDDs across sites. Upon risk modelling, noninstitutional delivery, history of perinatal asphyxia, neonatal illness, postnatal neurological/brain infections, stunting, LBW/prematurity, and older age category (6-9 year) were significantly associated with NDDs. The study sample was underrepresentative of stunting and LBW and had a 15.6% refusal. These factors could be contributing to underestimation of the true NDD burden in our population. CONCLUSIONS: The study identifies NDDs in children aged 2-9 years as a significant public health burden for India. HI was higher than and ASD prevalence comparable to the published global literature. Most risk factors of NDDs were modifiable and amenable to public health interventions

    Multivariable logistic regression analysis for risk factors for NDDs<sup>#</sup>.

    No full text
    <p>Multivariable logistic regression analysis for risk factors for NDDs<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002615#t005fn001" target="_blank"><sup>#</sup></a>.</p

    Study recruitment profile.

    No full text
    <p>Study recruitment profile.</p

    Background characteristics of study participants.

    No full text
    <p>Background characteristics of study participants.</p
    corecore