Identifying predictive factors of rapid response/code blue: A retrospective study using logistic regression analysis Article Swipe

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Brittany C. Thomas , Herschel Knapp , Frances Patmon ·

YOU? · · 2020 · Open Access · · DOI: https://doi.org/10.21203/rs.3.rs-35696/v1

Background: Rapid response calls and cardiac arrests are often preceded by observable signs of clinical deterioration often hours prior to the adverse event. Objectives: The purpose of this retrospective study was to identify risk factors that provide predictive value in determining the likelihood of a Rapid Response Call on adult telemetry patients at a single-centre community hospital. Design: This was a retrospective study based on secondary data analysis. After approval by the Institutional Review Board was obtained (CANV DHIRB-2018-362), we utilized the electronic medical record system to extract de-identified quantitative data from patient medical records. Setting: This study utilized medical records from patients on the Telemetry unit at a single-centre, 230-bed community hospital. Participants: The sample consisted of 250 randomized de-identified medical records from both patients who did and did not require a rapid response between January and December, 2018. Patients who were less than 18 years of age and those who were transferred to another facility or to another hospital were excluded from the analyses. Methods: The variables that were collected included age, gender, race, primary admitting medical diagnosis, hemoglobin, potassium, magnesium, creatinine, lactic acid, and urine output. Additional variables collected in four-hour increments included the vital signs: temperature, heart rate, oxygen saturation, respirations, systolic and diastolic blood pressure, and level of consciousness which was scored using the adult Glasgow Coma Scale. Logistic regression analysis was used to identify which of these variables were statistically significant in predicting patient deterioration. Results: The following predictors were statistically significant ( a = 0.05 with 95% Confidence Intervals [CI]): For every one beat increase in heart rate 4 hours prior to a RRT, the odds of a RRT increased by 4.9% (p=0.003) (CI=95% 1.016, 1.084). For every one increase in respirations, the odds of a RRT increased by 42.8% (p=0.004) (95% CI 1.11, 1.82), 8 hours before the RRT, and by 47% (p=0.002) (95% CI 1.15, 1.87), 12 hours before a RRT. African Americans had 20.6 times the odds of experiencing an RRT compared to Caucasians (p<0.001) (95% CI 3.4, 124.6), Hispanics had 56.6 times the odds of experiencing a RRT compared to Caucasians (p<0.001) (95% CI 11.4, 280.4), and other races had 6.3 times the odds of a RRT compared to Caucasians (p=0.044) (95% CI 1.05, 38.5). Conclusions: Such predictors can be used to identify early signs of deterioration that can alert health care providers to early intervention.

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Medicine Vital signs Logistic regression Medical record Retrospective cohort study Emergency medicine Glasgow Coma Scale Blood pressure Community hospital Internal medicine Pediatrics Surgery Psychiatry

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Type: preprint
Language: en
Landing Page: https://doi.org/10.21203/rs.3.rs-35696/v1
PDF: https://www.researchsquare.com/article/rs-35696/v1.pdf?c=1631857978000
OA Status: green
References: 4
Related Works: 10
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DOI: https://doi.org/10.21203/rs.3.rs-35696/v1

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Title: Identifying predictive factors of rapid response/code blue: A retrospective study using logistic regression analysis

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Type: preprint

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Language: en

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Publication year: 2020

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Publication date: 2020-06-17

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Authors: Brittany C. Thomas, Herschel Knapp, Frances Patmon

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Landing page: https://doi.org/10.21203/rs.3.rs-35696/v1

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PDF URL: https://www.researchsquare.com/article/rs-35696/v1.pdf?c=1631857978000

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Concepts: Medicine, Vital signs, Logistic regression, Medical record, Retrospective cohort study, Emergency medicine, Glasgow Coma Scale, Blood pressure, Community hospital, Internal medicine, Pediatrics, Surgery, Psychiatry

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abstract_inverted_index.Design:	58
abstract_inverted_index.Glasgow	221
abstract_inverted_index.January	137
abstract_inverted_index.adverse	22
abstract_inverted_index.another	156, 160
abstract_inverted_index.arrests	7
abstract_inverted_index.between	136
abstract_inverted_index.cardiac	6
abstract_inverted_index.extract	88
abstract_inverted_index.factors	35
abstract_inverted_index.gender,	175
abstract_inverted_index.medical	84, 94, 100, 122, 179
abstract_inverted_index.output.	189
abstract_inverted_index.patient	93, 240
abstract_inverted_index.primary	177
abstract_inverted_index.provide	37
abstract_inverted_index.purpose	26
abstract_inverted_index.records	101, 123
abstract_inverted_index.require	132
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abstract_inverted_index.Logistic	224
abstract_inverted_index.Methods:	167
abstract_inverted_index.Patients	141
abstract_inverted_index.Response	47
abstract_inverted_index.Results:	242
abstract_inverted_index.Setting:	96
abstract_inverted_index.analysis	226
abstract_inverted_index.approval	70
abstract_inverted_index.clinical	15
abstract_inverted_index.compared	332, 350, 369
abstract_inverted_index.excluded	163
abstract_inverted_index.facility	157
abstract_inverted_index.hospital	161
abstract_inverted_index.identify	33, 230, 384
abstract_inverted_index.included	173, 196
abstract_inverted_index.increase	262, 287
abstract_inverted_index.obtained	77
abstract_inverted_index.patients	52, 103, 126
abstract_inverted_index.preceded	10
abstract_inverted_index.records.	95
abstract_inverted_index.response	3, 135
abstract_inverted_index.systolic	206
abstract_inverted_index.utilized	81, 99
abstract_inverted_index.(p=0.002)	311
abstract_inverted_index.(p=0.003)	280
abstract_inverted_index.(p=0.004)	298
abstract_inverted_index.(p=0.044)	372
abstract_inverted_index.Americans	322
abstract_inverted_index.December,	139
abstract_inverted_index.Hispanics	340
abstract_inverted_index.Intervals	256
abstract_inverted_index.Telemetry	106
abstract_inverted_index.admitting	178
abstract_inverted_index.analyses.	166
abstract_inverted_index.analysis.	68
abstract_inverted_index.collected	172, 192
abstract_inverted_index.community	56, 112
abstract_inverted_index.consisted	117
abstract_inverted_index.diastolic	208
abstract_inverted_index.following	244
abstract_inverted_index.four-hour	194
abstract_inverted_index.hospital.	57, 113
abstract_inverted_index.increased	277, 295
abstract_inverted_index.pressure,	210
abstract_inverted_index.providers	394
abstract_inverted_index.secondary	66
abstract_inverted_index.telemetry	51
abstract_inverted_index.variables	169, 191, 234
abstract_inverted_index.Additional	190
abstract_inverted_index.Caucasians	334, 352, 371
abstract_inverted_index.Confidence	255
abstract_inverted_index.diagnosis,	180
abstract_inverted_index.electronic	83
abstract_inverted_index.increments	195
abstract_inverted_index.likelihood	43
abstract_inverted_index.magnesium,	183
abstract_inverted_index.observable	12
abstract_inverted_index.potassium,	182
abstract_inverted_index.predicting	239
abstract_inverted_index.predictive	38
abstract_inverted_index.predictors	245, 379
abstract_inverted_index.randomized	120
abstract_inverted_index.regression	225
abstract_inverted_index.Background:	1
abstract_inverted_index.Objectives:	24
abstract_inverted_index.creatinine,	184
abstract_inverted_index.determining	41
abstract_inverted_index.hemoglobin,	181
abstract_inverted_index.saturation,	204
abstract_inverted_index.significant	237, 248
abstract_inverted_index.transferred	154
abstract_inverted_index.(p<0.001)	335, 353
abstract_inverted_index.Conclusions:	377
abstract_inverted_index.experiencing	329, 347
abstract_inverted_index.quantitative	90
abstract_inverted_index.temperature,	200
abstract_inverted_index.Institutional	73
abstract_inverted_index.Participants:	114
abstract_inverted_index.consciousness	214
abstract_inverted_index.de-identified	89, 121
abstract_inverted_index.deterioration	16, 388
abstract_inverted_index.intervention.	397
abstract_inverted_index.respirations,	205, 289
abstract_inverted_index.retrospective	29, 62
abstract_inverted_index.single-centre	55
abstract_inverted_index.statistically	236, 247
abstract_inverted_index.deterioration.	241
abstract_inverted_index.single-centre,	110
abstract_inverted_index.DHIRB-2018-362),	79
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