ELIZA

return kwic search for patient out of >500 occurrences
1057411 occurrences (No.2 in the rank) during 5 years in the PubMed. [cache]

271) Understanding mortality, derived from debilitations consisting of multiple diseases, is crucial for patient stratification.

--- ABSTRACT ---

PMID:34610032 DOI:10.1371/journal.pone.0257894

2021 PloS one

* Condensed trajectory of the temporal correlation of diseases and mortality extracted from over 300,000 patients in hospitals.

- Understanding mortality, derived from debilitations consisting of multiple diseases, is crucial for patient stratification. Here, in systematic fashion, we report comprehensive mortality data that map the temporal correlation of diseases that tend toward deaths in hospitals. We used a mortality trajectory model that represents the temporal ordering of disease appearance, with strong correlations, that terminated in fatal outcomes from one initial diagnosis in a set of patients throughout multiple admissions. Based on longitudinal healthcare records of 10.4 million patients from over 350 hospitals, we profiled 300 mortality trajectories, starting from 118 diseases, in 311,309 patients. Three-quarters (75%) of 59,794 end-stage patients and their deaths accrued throughout 160,360 multiple disease appearances in a short-term period (<4 years, 3.5 diseases per patient). This overlooked and substantial heterogeneity of disease patients and outcomes in the real world is unraveled in our trajectory map at the disease-wide level. For example, the converged dead-end in our trajectory map presents an extreme diversity of sepsis patients based on 43 prior diseases, including lymphoma and cardiac diseases. The trajectories involving the largest number of deaths for each age group highlight the essential predisposing diseases, such as acute myocardial infarction and liver cirrhosis, which lead to over 14,000 deaths. In conclusion, the deciphering of the debilitation processes of patients, consisting of the temporal correlations of diseases that tend towards hospital death at a population-wide level is feasible.

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[frequency of next (right) word to patient]

(1)34 and	(20)4 communication	(39)3 prognosis	(58)2 interactions
(2)28 outcomes	(21)4 experiences	(40)3 satisfaction,	(59)2 monitoring,
(3)26 care	(22)4 knowledge	(41)3 stratification	(60)2 outcomes,
(4)13 safety	(23)4 outcome	(42)3 who	(61)2 outcomes;
(5)12 with	(24)3 access	(43)3 xenograft	(62)2 participation
(6)10 null	(25)3 care,	(44)2 cell	(63)2 perceptions
(7)9 populations	(26)3 characteristics	(45)2 choice	(64)2 perspectives
(8)7 data	(27)3 education	(46)2 classification	(65)2 plasma
(9)7 population	(28)3 group	(47)2 condition	(66)2 population,
(10)7 satisfaction	(29)3 groups	(48)2 costs	(67)2 portals
(11)7 was	(30)3 had	(49)2 demographics,	(68)2 preferences
(12)6 samples	(31)3 is	(50)2 engagement	(69)2 reported
(13)5 characteristics,	(32)3 language	(51)2 expectations	(70)2 samples,
(14)5 cohort	(33)3 medical	(52)2 experience	(71)2 suffering
(15)5 factors	(34)3 monitoring	(53)2 fibroblasts	(72)2 survival,
(16)5 in	(35)3 needs	(54)2 goals	(73)2 that
(17)5 management	(36)3 of	(55)2 groups,	(74)2 to
(18)5 navigation	(37)3 or	(56)2 health	(75)2 tumors
(19)5 survival	(38)3 perspective,	(57)2 information	(76)2 underwent

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--- WordNet output for patient --- =>がまん強い, 忍耐強い, 辛抱強い, 根気よく働く, 患者, 病人, 忠者 Overview of noun patient The noun patient has 2 senses (first 1 from tagged texts) 1. (73) patient -- (a person who requires medical care; "the number of emergency patients has grown rapidly") 2. affected role, patient role, patient -- (the semantic role of an entity that is not the agent but is directly involved in or affected by the happening denoted by the verb in the clause) Overview of adj patient The adj patient has 1 sense (first 1 from tagged texts) 1. (3) patient -- (enduring trying circumstances with even temper or characterized by such endurance; "a patient smile"; "was patient with the children"; "an exact and patient scientist"; "please be patient") --- WordNet end ---