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Washington, D. Free blacks were moving in, eventually outnumbering the city's slaves — a. August storm: the Soviet strategic offensive in Manchuria. Thus began one of the most significant. Start studying Isaac's Storm Questions. Learn vocabulary, terms, and more with flashcards, games, and other study tools. September 8, What is the age of Isaac's oldest daughter at the opening of the book. For whom does Isaac record weather. He works for the U.

Weather Bureau. Where does the storm reach on August Search the world's most comprehensive index of full-text books. My library. As one might suspect, August 2nd was no different. KG on Facebook. Log In. In Stumbling Colossus, David Glantz explored why the Red Army was unprepared for the German blitzkrieg that nearly destroyed it and left more than four million of its soldiers dead by the end of.

Last edited by Gasida. Colossus reborn the Red Army at war : by David M. Subjects: Soviet Union. Statement David M. G The Physical Object Pagination xix, p. Share this book. Young Peoples League. The Warrior. The righteous mans vveal and the vvicked mans vvoe.

Kreso, M. Pyne, M. Wissler, M. The rates of severe maternal morbidity and severe newborn morbid- Jennifer Fichter, M. Gloff, M. Both the severe maternal morbidity model and the severe newborn models exhibited acceptable levels of dis- Andrew W.

Dick, Ph. Hospital risk-adjusted rates of severe maternal Anesthesiology ; —53 morbidity were poorly correlated with hospital rates of severe newborn mor- bidity intraclass correlation coefficient, 0. This can be done using a childbirth composite measure What This Article Tells Us That Is New alongside separate measures of maternal and newborn outcomes.

This editorial accompanies the article on p. This article has a related Infographic on p. Supplemental Digital Content is available for this article. This article has an audio podcast. This article has a visual abstract available in the online version. Submitted for publication May 3, Accepted for publication March 22, All Rights Reserved.

Anesthesiology ; — DOI: Wolters Kluwer Health, Inc. Unauthorized reproduction of this article is prohibited. Measuring Childbirth Outcomes high- and low-quality care, we need statistical models Study Population that adjust for differences in patient risk and that properly This study was based on , obstetric deliveries in account for statistical noise due to random variation.

Deliveries with missing maternal or newborn dis- of severe maternal morbidity and severe newborn mor- charge status 10, , maternal age , gestational age bidity in the mother and her newborn based on admin- 20, , and height or weight 31, were excluded istrative and birth certificate data.

Although the Maternal from the analyses. We also excluded maternal—infant dyads Quality Improvement Program intends to base perfor- with maternal body mass index less than 15 or greater than mance reporting on electronic quality measures, claims- 80 84 , age less than 12 yr or greater than 55 yr 31 , parity based measures may be useful because the penetration of greater than 12 , gestational age more than 44 weeks the Maternal Quality Improvement Program—compliant 12, , or less than 28 weeks 4, , newborn con- electronic medical records among U.

In developing a composite measure of child- newborn hospital identifier were not the same Relying on Measure Development and Validation administrative instead of clinical data presents an oppor- tunity to develop a measure for national reporting sim- Our outcomes of interest were severe maternal morbid- ilar to the Centers for Medicare and Medicaid Hospital ity and severe newborn morbidity to focus on the most Compare without having to wait for electronic medical severe complications of childbirth.

We used the Centers for records—based clinical data to become widely available. Disease Control and Prevention Atlanta, Georgia algo- This measure could serve as a team-based shared account- rithm based on International Classification of Diseases, ability measure for anesthesiologists, obstetricians, pedia- Ninth Revision—Clinical Modification diagnostic and tricians, and intensivists. We supplemented the Centers for Disease Control and Prevention algorithm using Materials and Methods birth certificate data and also included maternal mortal- ity in severe maternal morbidity.

This measure is used by hospitals records were linked with birth certificate data. For patients who were transferred out, maternal status, maternal and newborn intensive care unit admission , and newborn outcomes were based on both the index and and hospital identifiers and characteristics. The California transfer hospital discharge data and were attributed to the Office of Statewide Health Planning and Development index admission. This also incentivizes Anesthesiology Glance et al.

The predicted We first constructed a patient-level nonhierarchical hospital severe maternal morbidity rate is calculated using multivariable logistic regression model for severe mater- both the patient-level regression coefficients and the hos- nal morbidity using data from The list of potential pital random effect to include the hospital contribution covariates was adapted from a comorbidity index developed to patient outcomes.

The hospital predicted-to-expected by Bateman et al. By construction, data. We pected ratio is greater than 1.

We use the predicted-to-expected ratio instead of the We then constructed a separate model for severe newborn observed-to-expected ratio because the use of hierarchical morbidity using the same approach. We evaluated model modeling results in more stable estimates of hospital per- fit using the C statistic, Hosmer—Lemeshow statistic, and formance and better predicts future hospital performance. Model fit was assessed in 1 the develop- We calculated the risk-standardized rate of severe mater- ment data set and 2 the validation data set nal morbidity by multiplying the predicted-to-expected using the model coefficients estimated in the data.

We excluded morbidity rate. We then calculated the risk-standardized severe newborn outcomes because we found empirically that the maternal morbidity rate using the approach described by magnitude of the association between patient-level risk fac- Krumholz et al. This rate tion between the same risk factors and newborn outcomes. We calculated the Table 1.

Calculation of Risk-Standardized Rate of Severe Maternal Morbidity Predicted hospital rate of severe This is the estimated rate of complications if the patients at a specific hospital are treated in that particular maternal morbidity hospital. This is calculated using the patient-level and hospital-specific regression coefficients. This is calculated using only the patient-level regression coefficients and does not include the hospital-specific regression coefficient in the calculation.

This is analogous to the observed-to-expected ratio calculated using nonhierarchical modeling. Hospital risk-standardized rate of This is the product of the predicted-to-expected ratio of severe maternal morbidity with the overall rate of severe maternal morbidity severe maternal morbidity in all of the hospitals. The risk-standardized rate of severe newborn morbidity is calculated in a similar fashion.

Downloaded from anesthesiology. Measuring Childbirth Outcomes composite risk-standardized rate as the geometric mean of maternal morbidity and severe newborn morbidity. Conceptually, performance measures that implies that most of the variation in the risk-standardized predict subsequent hospital performance have face valid- rate is due to differences in performance between hospi- ity as quality measures because patients can use them for tals as opposed to uncertainty in the estimate of individ- selecting providers with the expectation that hospital per- ual hospital performance.

Low levels of reliability, on the formance remains relatively stable over time. We then repeated this analysis using severe newborn morbidity Reliability increases with higher annual delivery volumes as the outcome of interest to determine whether hospi- and higher outcome rates.

Glantz, Jonathan M. The Battle of Kursk. Glantz, , available at Book Depository with free delivery worldwide. House seek to separate myth from fact to show what really happened at Kursk and how it affected the outcome of World War II. This is because the maneuvers are described in excruciating detail. When the kufsk kicks off, Col Glantz does a good job of telling just what the Soviet defenses did to the German assaults.

The author states that both Guderian and Von Manstein urged Hitler to cancel the operation. The Tigers would roll in and devastate a hundred Soviet tanks and maybe lose four or five tanks sometimes because Soviet soldiers managed to run up and place explosives on them, sometimes because the engines broke down, sometimes because they got stuck in swampy ground.

All these are worth revisiting just to see how men and women on both sides, fighting with tenacity for the most odious totalitarian regimes ever foisted on humanity, demonstrated their ability to lift themselves out of truly inhuman conditions to prevail or fail, survive or succumb. House Immense in scope, ferocious in nature, and epic in consequence, the Battle of Kursk witnessed at Prokhorovka one of the largest tank engagements in world history and led to staggering losses—including nearlySoviet and 50, German casualties—within the first ten days of fighting.

They also provide figures of combat strengths and losses, along with 32 maps that clarify troop and tank movements. By using our website you agree to our use of cookies. I wish Jason Mark would take this up and drill down to the unit actions similar to his books on the Leaping Horseman. It is meticulously researched, persuasively argued, full of new and important findings, and written with verve and pathos.