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National ALS Registry Makes a Difference | CDC Features |
The ATSDR National ALS Registry contributes to a better understanding of ALS and helps create a better future for the next generation of persons living with ALS. Learn more about ALS and the ALS Registry at www.cdc.gov/als. If you have ALS, make a difference in ALS research by participating in the ALS Registry. |
| potential causes | 0.335656 |
| Mortality Weekly Report | 0.368618 |
| data | 0.340843 |
| ALS | 0.958614 |
| brief risk factor | 0.369879 |
| Turner ALS Foundation | 0.524515 |
| new clinical trials | 0.425088 |
| amyotrophic lateral sclerosis | 0.451514 |
| biomarker identification | 0.337126 |
| great resource | 0.338502 |
| local chapters | 0.335799 |
| clinical trials | 0.451319 |
| better detection | 0.336613 |
| funds research | 0.338032 |
| earlier report | 0.336398 |
| risk factors | 0.45921 |
| Neuromuscular diseases | 0.374908 |
| secure web portal | 0.371273 |
| epidemiological data | 0.336815 |
| ultimate value | 0.339838 |
| nerve cells | 0.340774 |
| Muscular Dystrophy Association | 0.362805 |
| possible etiology | 0.334959 |
| sample specimens | 0.336385 |
| new data | 0.338385 |
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| CDC’s Morbidity | 0.338148 |
| ALS Association | 0.495514 |
| fatal neurological disease | 0.378993 |
| environmental exposures | 0.336956 |
| ALS research | 0.592336 |
| United States | 0.419652 |
| annual report | 0.337406 |
| Lou Gehrig | 0.342546 |
| Mayo Clinic | 0.373373 |
| national attention | 0.344824 |
| Eric J. Sorenson | 0.437154 |
| Registry enrollees | 0.352988 |
| ALS advocacy | 0.495716 |
| National ALS Biorepository | 0.562435 |
| common disease | 0.336638 |
| unknown factors | 0.337569 |
| Division Chair | 0.373364 |
| ALS registers | 0.514434 |
| support groups | 0.371526 |
| people | 0.347424 |
| U.S. Congress | 0.337402 |
| biological material | 0.336758 |
| National ALS Registry | 0.855184 |
| famous baseball player | 0.377999 |
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Understanding the production of population health and the role of paying for population health |
null |
| incentive structures | 0.588997 |
| health insurance | 0.579351 |
| various incentives | 0.574401 |
| Mullahy J. Understanding | 0.566592 |
| mental health | 0.58201 |
| health production functions | 0.663384 |
| PPH strategy | 0.577569 |
| empiric work | 0.574898 |
| opportunity sets | 0.588386 |
| health production relationships | 0.61561 |
| various PPH strategies | 0.579356 |
| specific empiric meaning | 0.568546 |
| health production | 0.747488 |
| improved population health | 0.633205 |
| health capital | 0.632807 |
| conceptual framework | 0.582005 |
| health production activities | 0.618877 |
| population health | 0.996636 |
| PPH strategies | 0.593815 |
| PPH research agenda | 0.574261 |
| stronger incentives | 0.569857 |
| health-producing activities | 0.577377 |
| health-producing choices | 0.571602 |
| health status | 0.609304 |
| Population Health Sciences | 0.630995 |
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| health-producing incentives | 0.590264 |
| various health | 0.582052 |
| health-related choices | 0.575726 |
| nontrivial empiric impediments | 0.573821 |
| choices | 0.666436 |
| personal health production | 0.611562 |
| better health outcomes | 0.63443 |
| considerable population heterogeneity | 0.591328 |
| reduced-form health production | 0.613037 |
| health production function | 0.739572 |
| empiric impediments | 0.578086 |
| incentives | 0.699588 |
| successful PPH strategy | 0.572097 |
| Community Health | 0.573127 |
| better population health | 0.740896 |
| people | 0.647048 |
| medical care | 0.608575 |
| general household production | 0.569552 |
| Grossman model | 0.713561 |
| various social sectors | 0.589759 |
| health care sector | 0.602564 |
| population health outcomes | 0.817201 |
| various sectors | 0.61988 |
| choices people | 0.567815 |
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Barium chloride (as Ba) - NIOSH Pocket Guide to Chemical Hazards |
null |
| MPEG | 0.378858 |
| search | 0.263099 |
| PDF | 0.261307 |
| PPT | 0.446092 |
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| DOC | 0.368812 |
| information | 0.262482 |
| different file formats | 0.938484 |
| page | 0.276773 |
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Number of Swine Origin H3 Infections in Pennsylvania Rises to Three |
Number of Swine Origin H3 Infections in Pennsylvania Rises to Three. |
| human influenza | 0.519139 |
| little seasonal influenza | 0.49165 |
| influenza infection | 0.492987 |
| Purple-coded RNA segments | 0.420632 |
| avian influenza viruses | 0.635624 |
| H3N2 influenza virus | 0.524136 |
| CDC′s Influenza Division | 0.507003 |
| human cases | 0.412028 |
| swine exposure | 0.411734 |
| seasonal flu illness | 0.379813 |
| different influenza viruses | 0.668711 |
| triple reassortant viruses | 0.519943 |
| H1N1 virus | 0.44915 |
| center virus | 0.4506 |
| influenza antiviral medications | 0.491627 |
| triple-reassortant swine influenza | 0.552912 |
| positive influenza test | 0.49268 |
| Green-coded RNA segments | 0.419148 |
| seasonal influenza vaccine | 0.495668 |
| Washington County Agricultural | 0.382047 |
| swine origin influenza | 0.712739 |
| viruses | 0.970215 |
| RNA segments | 0.712985 |
| cases | 0.41755 |
|
| human seasonal viruses | 0.50272 |
| North American swine | 0.437579 |
| PB1 segments | 0.389365 |
| seasonal influenza | 0.497409 |
| CDC laboratory testing | 0.380799 |
| red-coded RNA segments | 0.423685 |
| human origin HA | 0.383309 |
| virus hasn′t | 0.378501 |
| center viruses | 0.478299 |
| suspect influenza | 0.460879 |
| Pennsylvania | 0.401245 |
| Influenza Division′s Associate | 0.503719 |
| H1N1 viruses | 0.462801 |
| human seasonal flu | 0.492619 |
| influenza viruses | 0.962026 |
| seasonal flu viruses | 0.533356 |
| left virus | 0.417234 |
| new influenza viruses | 0.605873 |
| Eurasian swine | 0.406827 |
| swine viruses | 0.519898 |
| human infection | 0.439078 |
| humans | 0.391035 |
| influenza virus reassortment | 0.522341 |
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| 6894 |
Centers for Disease Control and Prevention |
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Frequently Asked Questions (FAQ) About Extreme Heat|Extreme Heat |
Information on extreme heat. Provided by the Centers for Disease Control and Prevention (CDC). |
| high body temperatures | 0.557729 |
| hot environment | 0.583683 |
| life-threatening emergency | 0.410397 |
| low salt level | 0.479576 |
| strenuous activity | 0.487879 |
| body | 0.631612 |
| Health Studies Branch | 0.472998 |
| victim alcohol | 0.429979 |
| emergency medical personnel | 0.502787 |
| heat exhaustion | 0.679446 |
| immediate medical assistance | 0.502131 |
| heat stroke | 0.563187 |
| body’s salt | 0.433338 |
| extremely hot weather | 0.521231 |
| mental illness | 0.451918 |
| elderly people | 0.410836 |
| body fluids | 0.430117 |
| cool water | 0.635077 |
| excessive sweating | 0.442107 |
| cool area | 0.516413 |
| strongest protective factor | 0.466961 |
| heat-related illness | 0.953321 |
| old age | 0.420751 |
| cool indoors | 0.513487 |
|
| Drink cool | 0.548372 |
| heat rash | 0.587437 |
| cool place | 0.533066 |
| emergency treatment | 0.408488 |
| air conditioning | 0.467214 |
| temperature control | 0.432971 |
| cool shower | 0.714428 |
| hospital emergency room | 0.494701 |
| heat cramps | 0.67253 |
| body’s ability | 0.513607 |
| body’s temperature | 0.461574 |
| medical attention | 0.649058 |
| heart disease | 0.413706 |
| victim | 0.433861 |
| humid environment | 0.41041 |
| Seek medical attention | 0.486603 |
| Heavy sweating removes | 0.509993 |
| sweating mechanism | 0.452394 |
| prescription drug | 0.41131 |
| Drink fruit juice | 0.482298 |
| schedule outdoor activities | 0.473918 |
| people | 0.445922 |
| painful cramps | 0.444886 |
| high blood pressure | 0.495602 |
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National Center for Environmental Health - About the Program |
NCEH provides leadership to promote health & quality of life by preventing or controlling those diseases or disabilities resulting from interaction between people and the environment. Site has information/education resources on a broad range of topics, including asthma, birth defects, radiation, sanitation, lead in blood, and more. |
| emergency department management | 0.569361 |
| asthma quality measures | 0.608265 |
| state grantees | 0.519231 |
| emergency department visits | 0.703486 |
| emergency involving radiation | 0.551193 |
| Climate Ready States | 0.560549 |
| state partners | 0.518379 |
| Funding state programs | 0.593343 |
| Health Studies Branch | 0.604279 |
| present surveillance data | 0.578057 |
| national data sources | 0.593863 |
| man-made disasters | 0.577326 |
| human behavior | 0.562028 |
| public health consequences | 0.615779 |
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| public’s health | 0.548034 |
| human health effects | 0.631869 |
| Environmental Health | 0.563643 |
| multiple research activities | 0.576295 |
| environmental hazards | 0.65205 |
| integrated health | 0.544398 |
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| health care collaboration | 0.624967 |
| health effects | 0.694272 |
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| EHHE | 0.520861 |
| harmful exposures | 0.518493 |
| environmental public health | 0.800544 |
| United States | 0.658917 |
| national radiologic emergency | 0.578864 |
| EHHE researches | 0.518272 |
| harmful environmental exposures | 0.60525 |
| major public health | 0.617215 |
| future health effects | 0.62898 |
| Public Health Tracking | 0.63682 |
| environmental conditions | 0.534317 |
| public health | 0.915006 |
| city health department | 0.633396 |
| current health study | 0.610891 |
| radiation-related health research | 0.608727 |
| poisoning prevention | 0.516641 |
| Tracking Network | 0.634142 |
| public health capacity | 0.67273 |
| emergency response drills | 0.556393 |
| state indoor air | 0.592615 |
| local capacity | 0.564591 |
| carbon monoxide poisoning | 0.612418 |
| national organizations | 0.509141 |
| state requests | 0.517715 |
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Bartonella - Clinicians |
Bartonella bacteria cause several diseases in humans. The three most common are cat scratch disease, caused by B. henselae; trench fever, caused by B. quintana; and Carrión's disease, caused by B. bacilliformis.
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| Raoult D. Recommendations | 0.507628 |
| infectious diseases | 0.366733 |
| typical signs | 0.41015 |
| children | 0.25432 |
| Koehler JE | 0.390398 |
| serology | 0.386535 |
| Dolan MJ | 0.384741 |
| first-line treatment | 0.409089 |
| mg | 0.262892 |
| Health care providers | 0.511873 |
| antibiotic treatment | 0.400845 |
| direct observation | 0.38772 |
| chocolate agar | 0.397695 |
| patients | 0.266685 |
| diagnosis | 0.270757 |
| azithromycin | 0.301948 |
| Bartonella infections | 0.914072 |
| acute phase | 0.380561 |
| Endocarditis | 0.259997 |
| aminoglycosides | 0.252913 |
| antibiotics | 0.282665 |
| B. henselae | 0.574479 |
| Oroya fever | 0.426606 |
| PCR | 0.275467 |
| Bartonella species | 0.764407 |
|
| blood samples | 0.409563 |
| cross-reactivity | 0.255344 |
| peripheral blood | 0.400884 |
| Int J Antimicrob | 0.380074 |
| heart valve tissue | 0.533386 |
| CSD | 0.45042 |
| Bartonella spp. | 0.575309 |
| Trench fever | 0.831756 |
| B. quintana | 0.402968 |
| kg | 0.265688 |
| blood culture | 0.400919 |
| Rolain JM | 0.380366 |
| cases | 0.266124 |
| Antimicrob Agents Chemother | 0.511769 |
| Raoult D. Pathogenicity | 0.515923 |
| lymph node aspiration | 0.698628 |
| severe pain | 0.400019 |
| lymph node volume | 0.620258 |
| human infections | 0.456929 |
| lymph node | 0.832834 |
| slow-growing bacterium | 0.421171 |
| treatment options | 0.384763 |
| compatible exposure history | 0.580247 |
| cat scratch disease | 0.544219 |
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National Influenza Vaccination Disparities Partnership |
National Influenza Vaccination Disparities Partnership (NIVDP) is a national multi-sector campaign, spearheaded by local influential partners who commit to promote the importance of flu vaccination among underserved populations - CDC |
| Claire Hannan | 0.686192 |
| Initiatives | 0.362742 |
| Topics | 0.337626 |
| resources | 0.336294 |
| Dr. Arlene Lester | 0.92312 |
| Josana Tonda | 0.667569 |
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| Best practices | 0.540312 |
| underserved communities | 0.588427 |
| Effective strategies | 0.535274 |
| Catherine Martin | 0.597659 |
| flu vaccination | 0.941325 |
| high-risk populations | 0.614836 |
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Breast Cancer in Young African American Women |
Breast Cancer - Gateway to Health Communication - CDC |
| young women | 0.37733 |
| african american women | 0.779274 |
| young woman | 0.323351 |
| battle breast cancer | 0.325918 |
| higher co-morbidity | 0.232987 |
| effective method | 0.231862 |
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| higher-grade tumors | 0.232454 |
| key barriers | 0.230739 |
| early menopause | 0.229773 |
| survival rate | 0.259713 |
| generational health | 0.233953 |
| breast health | 0.42517 |
| significant implications | 0.233185 |
| risk factors | 0.23367 |
| lower survival rates | 0.255339 |
| financial stability | 0.229312 |
| abnormal breast health | 0.375397 |
| Younger women | 0.244505 |
| breast health course | 0.345246 |
| aggressive breast cancers | 0.334433 |
| poverty deter | 0.231778 |
| potentially life-threating situation | 0.252865 |
| woman’s story | 0.228974 |
| breast cancer diagnosis | 0.383742 |
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| larger tumor sizes | 0.257421 |
| breast cancer rates | 0.355194 |
| breast abnormality | 0.301956 |
| breast cancer screenings | 0.339379 |
| young age | 0.239198 |
| impact breast cancer | 0.32651 |
| higher risk | 0.255766 |
| harsh outcomes | 0.231506 |
| unique challenges | 0.262697 |
| breast malignancy | 0.301767 |
| breast cancer | 0.902674 |
| breast milk | 0.29792 |
| Caucasian women | 0.268053 |
| older women | 0.264498 |
| lymph node involvement | 0.259224 |
| doctor | 0.238196 |
| cultural barriers | 0.230958 |
| increased risks | 0.230198 |
| later stages | 0.230905 |
| late stage diagnosis | 0.25778 |
| risk | 0.264129 |
| five-year breast cancer | 0.344263 |
| body image | 0.228851 |
| breast cancer statistics | 0.328621 |
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Hearing Loss in Infants with Microcephaly and Evidence ofCongenital Zika Virus Infection - Brazil, November 2015-May 2016 |MMWR |
The Morbidity and Mortality Weekly Report (MMWR) Series is prepared by the Centers for Disease Control and Prevention (CDC). |
| hearing testing | 0.276548 |
| behavioral auditory testing | 0.244367 |
| late-onset hearing impairment | 0.299403 |
| initial screening tests | 0.259239 |
| Congenital infection | 0.302141 |
| presumed Zika-virus infection | 0.25074 |
| congenital zika virus | 0.682541 |
| auditory brainstem response | 0.244994 |
| sensorineural auditory impairment | 0.285436 |
| children | 0.278102 |
| maternal rash | 0.252942 |
| auditory function | 0.24542 |
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| gestational age | 0.24899 |
| behavioral auditory evaluation | 0.241022 |
| infants | 0.291174 |
| hearing thresholds | 0.279519 |
| Hospital Agamenon Magalhães | 0.303025 |
| laboratory evidence | 0.272789 |
| decibels normal hearing | 0.296759 |
| pregnancy | 0.243224 |
| Zika virus disease | 0.264535 |
| auditory deficits | 0.245 |
| Infant Hearing | 0.281392 |
| diagnostic hearing tests | 0.300572 |
|
| congenital rubella | 0.246645 |
| congenital sensorineural hearing | 0.373835 |
| hearing loss | 0.993342 |
| head circumference | 0.255857 |
| sensorineural hearing loss | 0.899997 |
| profound sensorineural hearing | 0.379222 |
| severe microcephaly | 0.287351 |
| congenital Zika syndrome | 0.280183 |
| Zika virus infection | 0.916696 |
| congenital infections | 0.288479 |
| auditory evaluation | 0.243387 |
| unilateral sensorineural hearing | 0.332721 |
| auditory testing | 0.244424 |
| Zika virus-specific immunoglobulin | 0.243827 |
| hearing deficit | 0.27401 |
| auditory screening programs | 0.240772 |
| auditory function evaluation | 0.242992 |
| hearing evaluation | 0.274787 |
| normal initial screening | 0.259644 |
| risk factor | 0.245958 |
| conductive hearing loss | 0.323039 |
| congenital viral infections | 0.392888 |
| congenital hearing loss | 0.347143 |
| familial hearing loss | 0.312671 |
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